IC-ITECHS

An Enhancement of Haar Cascade Algorithm Applied to Face Recognition for Gate Pass Security

2024-12-05T03:36:52+00:00

This study is focused on enhancing the Haar Cascade algorithm to decrease the false positive and false negative rate of face recognition in images with variations in lighting, facial expressions, and occlusions to increase accuracy. The face recognition library was applied with Haar Cascade where 128-dimensional vectors representing the unique features of a face were encoded. The Enhanced Haar Cascade Algorithm produced a 98.39% accuracy rate, in comparison, the Haar Cascade Algorithm achieved a 46.70% - 77.00% accuracy rate. Both algorithms used the Confusion Matrix Test with 301,950 comparisons using the same dataset of 550 images. The 98.39% accuracy rate shows a significant decrease in false positive and false negative rates in facial recognition in images with complex conditions

Empowering Sustainable Software Engineering Education with Artificial Intelligence and Immersive Technology

2024-12-05T03:37:28+00:00

This research investigates the impact of integrating artificial intelligence (AI) and immersive technologies, such as virtual reality (VR) and augmented reality (AR), in software engineering education to promote continuous and adaptive learning. The purpose of this study was to explore how these technologies increase student engagement, personalize the learning experience, and enhance practical skills essential in software development. A mixed methods approach was used, combining a quantitative survey with qualitative interviews of 20 students and 5 educators actively engaged in AI and VR powered courses. Findings revealed that AI-based adaptive learning systems encourage personalized feedback and help address individual knowledge gaps, leading to increased engagement and retention. VR based simulations enable hands-on learning, which significantly improves skill acquisition in coding, debugging, and system analysis. Despite these benefits, challenges such as high costs, data privacy concerns, and limited infrastructure remain a barrier to widespread implementation. This study contributes original insights by identifying strategies to mitigate these challenges, including gradual adoption of technology, cloud-based solutions to reduce costs, prioritizing data security, and continuous educator training. The findings underscore the transformative potential of AI and immersive technologies in creating sustainable, accessible and adaptive learning environments and equipping students with the skills needed for the innovation driven software industry.

Challenges of Online Language and Literature Learning to the BSE-English Students of Pangasinan State University-Bayambang

2024-12-05T03:37:43+00:00

This descriptive research aimed to identify challenges in online language and literature learning faced by Bachelor of Secondary Education - Major in English students at Pangasinan State University, Bayambang Campus, and to propose coping strategies. The study surveyed 153 students using a structured questionnaire with three sections: sociodemographic profile, challenges in online learning, and coping strategies. Data collection was facilitated online via Google Forms, and a non-experimental descriptive approach was applied to analyze the responses.

Results indicated that most respondents were female, second-year students from low-income families (earning Php 10,000 or less monthly). The majority relied on mobile phones for online learning and expressed a preference for traditional, face-to-face classes. Key challenges impacting academic performance included difficulties in language and literature learning, self-regulation, technological literacy and competency, technological sufficiency, and learning environment—all rated as having a “Great Extent” effect on learning outcomes.

The most effective coping strategies identified were self-discipline (79.1% of respondents), self-study (78.4%), and adaptation (73.2%). These strategies enabled students to navigate the demands of online learning. The study suggests further research to examine the relationship between student profiles and challenges in online education to deepen understanding of specific factors influencing academic experiences and outcomes.

A feature selection algorithm for PNN optimized by binary PSO and applied to smart city intrusion detection system

2024-12-05T03:37:58+00:00

In the smart city construction and development process, network security is a vital link that must be addressed. As a critical technology to ensure the security of smart cities, intrusion detection systems play multiple roles, such as real-time monitoring, threat identification, and event response. By deploying and optimizing efficient intrusion detection mechanisms, smart cities can effectively resist various network attacks and ensure the safety and stability of urban operations. Therefore, this paper proposes a PNN feature selection model based on binary particle swarm algorithm optimization (BiPSO) to select features for network traffic data and remove a large amount of redundant information; then, a variety of classifiers (random forest, KNN, Adaboost, BPNN) are used to classify the data after feature selection. We use NSL-KDD for experiments. The experimental results show that the BiPSO-PNN proposed in this paper not only achieves accurate selection of data set features but also guarantees high accuracy on other classifiers, which has vital practical significance.

Improve Healthcare Accessibility via a Mobile App for Health Facility Search Utilizing Location-Based Services

2024-12-05T03:38:14+00:00

Access to health facilities is an important aspect of individual well-being but many communities, especially in remote areas, face difficulties in finding and accessing health services. Location-Based Services (LBS) technology in mobile applications offers a solution to this problem. This research aims to develop and test an LBS-based mobile application to improve the accessibility of health facilities. Using applied design, applications are developed for Android platforms. The sample consisted of 100 respondents in areas with limited access to health facilities, divided into experimental and control groups. Data is collected through application usage logs and questionnaires, analyzed using appropriate statistical techniques to evaluate accessibility and user satisfaction. The results show that the LBS application significantly increases the accessibility of health facilities. The experimental group found and accessed health facilities 30% faster than the control group. As many as 85% of experimental group respondents were satisfied with the ease of use and speed of application access. The LBS application is effective in increasing the accessibility of health services by providing real-time information about nearby health facilities. This research has practical implications for app developers, healthcare providers, and policymakers.

An Automated Rack Storage System for Railway Devices and Equipment Using QR Code and Cloud Database Technology

2024-12-05T03:38:27+00:00

This research project aims to develop an automated storage rack system for railway devices and equipment using QR codes and cloud-based database technology. The automated rack system can precisely store railway devices and equipment using the cloud-based QRC/QR Code database. It explores the drawbacks of conventional storage management methods in the railway industry, like lack of order, inefficiency, and security issues. Using QR codes to track and monitor all tools, equipment, and components, the proposed system includes a cloud-based database providing real-time inventory visibility and data analysis capabilities. Additionally, the system features CCTV surveillance for added security level and mobile phone integration to ensure that only you, as the end user, get access. Based on the study's findings, automated storage rack systems promise significant improvements in efficiency, security, and operational effectiveness for railway maintenance.

A Modular Track and Signaling Simulation Trainer for Railway Technology Program

2024-12-05T03:38:38+00:00

The modular railway track and signaling simulation trainer research project was developed to provide an enjoyable and educational tool to train railway students and professionals upon recognizing the need for effective training in traffic and signaling safety-critical areas. It provides a miniature model that accurately replicates railway switch points and signaling systems with modules depicting track layouts and signaling conditions created using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). The prototype's accurate and efficient miniature railway model showed that the simulation trainer was very effective. The survey demonstrated that railway students and professionals were satisfied with the trainer's performance and various use and educational potential for students. This simulation trainer design successfully changes railway training programs because it offers a relatively safe and exciting environment that allows learners to get practical experience and understanding of railway operations. The modular design of the trainer will facilitate future expansion and customization, making it adaptable to railway training needs and technology. The simulation trainer should include level crossings, track circuits, and train detection systems for further investigation. This would provide an improvement in the comprehensiveness and flexibility of the trainer, therefore helping with providing skilled railway workers.

A Train Driving Simulator to Enhance Railway Technology Student’s Learning Experience Using Prototype Method and OpenBVE

2024-12-05T03:38:49+00:00

A Train Driving Simulator is a software application that tries to replicate the experience of operating a train. This unique equipment minimizes the expense of using actual rolling stock to teach future railway staff. The research aims to create a Train Driving Simulator with OpenBVE for Railway Technology students. The research focused on making a simulator that simulates the feeling of driving a train, which involved detailed physics modeling and control of the train. The simulator was built to be user-friendly and accessible, with features such as the 3D representation of the LRT Line 1 route and its compact, portable architecture. The simulator was built from commercial off-shelf parts and tested for usefulness, safety, and durability. The simulator's performance was tested using the TUP evaluation metrics. The research aimed to enhance the learning experience of students undergoing railway technology by providing on-site training in operating a train. The simulator will likely provide students and instructors with maximum benefit in courses like Railway Signaling, Rolling Stocks, and Railway Facilities

The Digital Learning Revolution: AI-Powered Adaptive Learning in PGSD Lectures

2024-12-05T03:38:59+00:00

The development of digital technology has significantly impacted education, including PGSD (Primary School Teacher Education) lectures. AI-powered adaptive learning offers vast potential to revolutionize digital learning in PGSD, particularly in the course on Digital Learning. This study aims to explore the use of AI-powered adaptive learning in the context of fifth-semester PGSD students enrolled in Digital Learning courses for elementary schools. This research employs a qualitative approach with a case study method. Data were collected through observations, in-depth interviews with lecturers and students, and document analysis. Data were analyzed thematically to identify the benefits, challenges, and effective strategies for implementing AI-powered adaptive learning. The findings reveal that AI-powered adaptive learning has significant potential to enhance the effectiveness of digital learning in PGSD lectures. This system can provide personalized learning tailored to the needs and abilities of each student. It also boosts learning motivation, fosters independence, and optimizes study time. However, the study also highlights several challenges, such as resource availability, technology access, and lecturers' readiness to implement this system. This research recommends that universities consider integrating AI-powered adaptive learning as an integral part of digital learning in PGSD lectures. It also serves as a reference for developing strategies and policies that support the effective and sustainable implementation of AI-powered adaptive learning in higher education.

A Literature Review: Examining Visual Design and Multimedia Elements Role in Fighting Misinformation and Strengthening Media Trust

2024-12-05T03:39:09+00:00

The development of digital media has presented new challenges in maintaining the credibility of information, especially amidst the increasing prevalence of misinformation and hoaxes that spread rapidly through social platforms. This study aims to explore how visual design and multimedia elements can contribute to building audience trust in media and encouraging engagement in disseminating credible information. Using the Systematic Literature Review (SLR) method, the research follows a selection procedure based on PRISMA 2020 guidelines to ensure the validity and quality of the included studies. From 20 articles that meet the inclusion criteria, the key findings indicate that consistent and aesthetically pleasing visual design, particularly those capable of touching the emotional aspects of the audience, plays a crucial role in enhancing media credibility and brand loyalty. Additionally, interactive multimedia approaches, such as dynamic infographics and narrative-based short videos, not only capture audience interest but also strengthen their intention to share credible information.

This study concludes that the application of strong visual elements and emotion-based multimedia strategies can help counter misinformation by strengthening media brand equity. Recommendations for future research include developing interactive designs that can educate audiences in identifying credible information and collaborating with media professionals to ensure broader impact. These findings provide practical guidance for media in integrating visual design as an effective tool to build trust and enhance information literacy in the digital age.

Empowering ESL Learning: Motivation in Acquiring English as a Second Language

2024-12-06T01:53:44+00:00

ABSTRACT: This study investigates the role of motivation in enhancing English as a Second Language (ESL) acquisition among Grade 7 students. It employs a qualitative-descriptive method as it analyzes the complex dynamics of motivation in the context of English as a Second Language (ESL) learning, providing a nuanced grasp of the motivational elements that influence ESL learners' language acquisition journeys. The study investigates the varied nature of motivation using interviews and thematic analysis, with the goal of uncovering ESL learners' subjective experiences, challenges, and attitudes. Grasping the complexities of motivation within the ESL context is dominant, as it can influence students' engagement and language proficiency. Results of the study have shown that English as a Second Language Learning (ESL) is one of the common factors that affects students learning in a classroom setting. Motivation also plays a significant role in determining students’ academic performance and overall accomplishment in acquiring proficiency in English as a Second Language (ESL). The study assessed the motivational factors among Grade 7 students, focusing on Integrative Orientation with a composite mean of (5.14) and Instrumental Orientation with a composite mean (5.07) respectively. Problems encountered were evaluated through Survey Questionnaires (composite mean: 3.65) and Interviews. Integrative Orientation significantly influences English as a Second Language motivation, while difficulties in English language usage emerge as primary issues. Grade 7 students, undergoing a transitional academic phase, face challenges in adjusting to learning. Recommendations of the researchers focus on academic importance that will help enhance and increase learning motivation of the students in English as a Second Language.

An Enhancement of Eigenface Algorithm Applied for Identifying Spoofing Attacks in Facial Recognition

2024-12-05T03:39:29+00:00

Facial recognition is a biometric authentication technology that identifies individuals using their facial features in images and videos. The rise of spoofing attacks poses significant risks, especially for facial recognition, as malicious actors are impersonating individuals by misusing their identities. The accuracy of facial recognition can be impacted by factors like face occlusions, image low-resolution, and the distance of the user's face from the camera, leading to potential misidentification. This research enhanced the Eigenface Algorithm applied to identify spoofing attacks in facial recognition. The algorithm extracts facial features and transforms them into eigenvectors for improved accuracy. Previous studies showed limitations in face detection at varying distances, prompting the incorporation of a distance-based scale in the enhanced algorithm, targeting a range of 30 cm to 60 cm from the camera. In this study, the researchers implemented OpenCV2 and stored the trained dataset in a YAML file. The dataset was generated by capturing multiple images with varying environments and distances, which were then preprocessed to resize and convert them to grayscale. Results showed a confidence level of 93.83% for the enhanced algorithm, a significant improvement from 57.38% with the existing one, and a faster average recognition time of 0.0141 seconds compared to 0.0216 seconds, demonstrating a 36.45% increase in confidence and a speed improvement of 0.0075 seconds. The distance-based scaling improves the efficiency of the Eigenface Algorithm by preventing recognition attempts at unsuitable distances, thus enhancing usability in practical applications.

Enhancing ResNet with Ghost Weight Normalization For Improved Retina Disease Classification

2024-12-05T03:39:37+00:00

Retinal disease is a dangerous disease. If left untreated, it can cause blurred vision and even cause permanent blindness. Recently, deep learning approaches are widely used to classify medical diseases. A widely used model to classify medical diseases is ResNet. To train the ResNet model, the data used is data obtained from Kaggle with the name Retinal OCT Images (Optical Coherence Tomography) consisting of 4 classes namely choroidal neovascularization (CNV), DRUSEN, diabetic macular edema (DME), and Normal with a total of 83,600 data. The ResNet base model showed accuracy and f1-score of 92%. Modifying the ResNet Base model with the addition of Ghost Weight Normalization (GWN) which aims to provide more weight normalization opportunities shows an increase in accuracy and f1-score to 94%. GWN can also increase the accuracy of CNN Base from 77% to 81%. This improvement shows that GWN can improve the accuracy of Deep learning models with its weight normalization variation technique. Although the training load and training time when using GWN can increase, the accuracy and f1-score of the ResNet model with GWN of 94% can make the chance of misclassification of retinal diseases smaller.

Intelligent Visual Inspection System of Ship Draft Based on UAV

2024-12-05T03:39:46+00:00

Accurately calculating the weight of cargo after shipping is an important issue in ocean transportation. Existing methods mainly indirectly calculate the weight of cargo by obtaining the draft of the ship. To estimate the draft of ships passing through waterways and ports, it is necessary to collect sounding line data. However, the current methods for collecting sounding line data mainly rely on manual measurement, which is inefficient, inaccurate, and has safety hazards. To address these issues, this paper combines artificial intelligence and deep learning technologies to design an unmanned aerial vehicle-based intelligent detection system for ship drafts. Detailed research is conducted on image acquisition, image segmentation, image recognition algorithms, etc., and an intelligent measurement platform for ship drafts is developed.

Optimized Scheme for the Combination of Shared Energy Storage Business Models

2024-12-05T03:39:58+00:00

The Stackelberg game model between shared energy storage stations and renewable energy generators optimizes pricing strategies to maximize both parties' profits. The energy storage station, acting as the leader, sets pricing strategies for capacity leasing, peak-valley arbitrage, and frequency regulation services, while the renewable energy generator, as the follower, selects the optimal service package based on the station's pricing schemes. This paper employs a Genetic Algorithm (GA) to optimize the energy storage station’s profits and applies NSGA-II to assist the generators in finding the optimal package combination, thereby improving overall profitability. The study demonstrates that this approach effectively facilitates optimal collaboration under complex market conditions and in the experimental validation, the interactions between the energy storage station and the generators were simulated under different market scenarios. The results show that the proposed game model significantly improves station profitability and optimizes generator strategies. The model’s potential applications and future optimization possibilities are discussed, providing theoretical support for the practical operation of shared energy storage business models.

Leveraging Data Science and AI-Based Analytics to Enhance Immersive Learning Experiences in Education

2024-12-06T01:54:26+00:00

Technology-based learning faces challenges in effectively increasing student engagement, motivation, and understanding in the context of continuing education. This study aims to explore the role of data science and AI-based analytics in supporting immersive learning experiences to improve learning outcomes. The research method used is descriptive and correlational statistical analysis of data from 50 students with various metrics, such as engagement scores, motivation, understanding, retention, AI feedback accuracy, VR content quality, learning duration, device compatibility, and network stability. The results showed that the average student engagement score was 77.45, motivation 78.57, and understanding 81.16, with each showing a significant positive relationship to learning retention (average 61.11). AI feedback accuracy had an average score of 84.66, indicating the significant contribution of AI technology in improving student understanding. VR content quality had an average score of 89.76, indicating that well-designed content can improve students' learning experiences. The average learning duration was 84.26 minutes, with a moderate correlation to understanding (r = 0.72). However, technical challenges were found, such as a weak negative correlation between learning duration and network stability, indicating that connectivity issues may affect the learning process. The regression results showed that the model was only able to explain 17.86% of the variance in the dependent variable, so additional variables are needed for a more comprehensive understanding. This study concludes that the integration of AI and VR in education has great potential to improve learning experiences and outcomes, although there are still technical obstacles that need to be overcome to maximize its impact.

Designing Sign System in Sirah Kencong Blitar as A Tourists Information Media

2024-12-05T03:41:10+00:00

Blitar Regency, which is located in East Java Province, offers interesting natural and cultural riches. According to Detik Travel, as of April 2023, there are 35 tourist attractions that attract the attention of visitors, making Blitar a popular destination. One of them is Sirah Kencong, a tourist area with unique advantages. However, the current sign system is still traditional and less effective in providing clear guidance to visitors. By applying visual communication design and semiotic theory, this redesign is expected to improve navigation, provide more complete information, and increase a satisfying tourist experience. Significant visit data shows the need to improve information infrastructure to support sustainable tourism growth. It is hoped that the implementation of an innovative, consistent and inclusive sign system can optimize the natural tourism potential of Sirah Kencong by presenting clear information and supporting the overall visitor experience.

System Security Testing Using The Penetration Testing Method on The Palapa Vocational School Library Website

2024-12-05T03:41:32+00:00

The Palapa Library utilizes its website as the primary platform for providing information and services to users. However, the presence of vulnerabilities in the website poses significant threats to data and system security. This study aims to identify and analyze vulnerabilities on the Palapa Library website using the Penetration Testing method based on the NIST SP 800-115 standard. This method involves four stages: planning, discovery, attack, and reporting. The testing results identified two major vulnerabilities: sensitive information disclosure and SQL Injection. Once the vulnerabilities were identified, their severity levels were assessed using the Common Vulnerability Scoring System (CVSS) version 3.1. CVSS provides scores for the vulnerabilities, helping prioritize remediation efforts from the highest to the lowest risk. Based on the assessment results, appropriate remediation measures were developed to enhance the security of the Palapa Library website. This study is expected to serve as a reference for preventing similar security threats in the future and assisting other institutions facing similar challenges in improving the security of their information systems.

Student ID Validation Monitoring System

2024-12-05T03:43:48+00:00

The Student ID Validation Monitoring System (SIVMS) is a web-based system aimed to monitor students' ID validation status at Iloilo Science and Technology University Miagao Campus. This system was created to address the challenge faced by the Office of Student Affairs and Services Miagao Campus in ensuring only students with validated ID are in the campus, enhancing safety, and security. By utilizing QR code scanning technology, the system ensures quick and accurate tracking of student validation status. The main objective of the study was to develop a system that manages student profiles, generates unique QR codes for each student, and enables security personnel to monitor student ID validation status. The system also has the ability to generate reports and was evaluated using the ISO 25010 software quality model. Built with HTML, CSS, PHP, and MySQL, the system followed the Iterative Software Development Methodology, ensuring continuous improvements through user feedback. The evaluation results, based on the ISO/IEC 25010 criteria, showed an overall rating of "excellent," with a mean score of 4.52. The system met the standards for functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability. In conclusion, the study successfully achieved its goal of developing the SIVMS, improving campus security, and supporting university policy enforcement.

QuranVision

2024-12-05T03:44:39+00:00

Tajweed is a set of rules, which is required for every Muslim to learn in order to recite the holy Quran. These rules are needed to guide Quran’s reciters from making any errors, such as mispronouncing words which are strictly prohibited when reciting Quran. The conventional learning process on Tajweed rules, which comes in the form of face-to-face learning between instructor and the students, although considered the most effective way to learn Quran, may be tedious and time consuming due to the need for prolonged session of direct contact for learning. On that note, a mobile application which can detect and recognize the feature of Tajweed rules via image processing in al-Quran using a deep learning technology is proposed. Convolutional Neural Network or CNN is the commonly used technology when it comes to object detection and image classification. Model based on CNN architectures will be utilized in developing a real-time detection and recognition mobile application, focusing on Meem Sakinah-based Tajweed rules which include Idgham, Ikhfa’ and Izhar Shafawee. The key benefits of this application is in its ability to detect Tajweed rules in a real-time scenario and works in both black and white and color-coded Quran. This application provides an alternative way for new Quran’s learners from varying backgrounds and age to learn about Tajweed rules on their own time through visual and audio learning as well as detailed descriptions of the Tajweed rules which can aid in understanding the material more effectively.

Development of a Financial Management Application for Boarding Students Using the Waterfall Method An Effective Solution for Managing Budgets and Expenses

2024-12-05T03:45:11+00:00

Financial management is a considerable difficulty for students residing in boarding homes, who often possess restricted revenue sources and diverse expenditure requirements. An extravagant lifestyle coupled with inadequate financial literacy frequently results in students encountering difficulties with budgeting and experiencing financial crises at month’s end. This study seeks to create a web-based financial management tool employing the Waterfall methodology, intended to assist students in documenting income and expenditures, managing budgets, and enhancing their financial literacy. The Waterfall technique is methodically executed through the phases of requirements analysis, design utilising UML, implementation employing tools such as Vscode and MySQL, and testing to verify the application's operation. This program has transaction recording capabilities, financial reporting, and profile management, enabling students to efficiently track cash flow and assess spending habits. The research findings indicate that this application assists students residing in boarding homes in managing their funds more systematically, mitigates the danger of extravagance, and enhances awareness of the significance of effective financial management. This application aims to enhance students' independence in money management and facilitate their preparation for a secure financial future

AI- A Distance Learning Tool

2024-12-05T03:47:12+00:00

With the development of information technology, artificial intelligence (AI) has shown great potential in the field of distance learning. This article focuses on AI as a distance learning tool and explores its intelligent learning assistance features, including providing students with personalized learning paths, real-time Q&A, and more. It also explains the role of AI in the generation and optimization of teaching content, such as using technology to generate high-quality course text and materials, and optimizing content based on feedback. Research shows that AI is revolutionizing remote learning and can dramatically improve learning outcomes.

Research on Financial Investment Risk in Enterprise Financial Management

2024-12-05T03:47:25+00:00

This paper focuses on the financial investment risk in the financial management of enterprises, analyzes its causes, types and potential threats to the financial security of enterprises. It is pointed out that the main causes of financial investment risk are the lack of perfect risk management system, the insufficient ability of financial managers and the change of external environment. To deal with these risks, this paper puts forward a series of strategies, including building a comprehensive financial risk investment system, improving the professional quality of financial management team, balancing returns and risks, and strengthening internal control. The effectiveness of the proposed strategy is verified by case analysis. The research results of this paper not only enrich the theoretical system of financial investment risk management, but also provide practical guidance for enterprises, which is helpful to improve the level of financial security of enterprises and ensure steady development.

A Normative Study of Generative Artificial Intelligence in Higher Education and Implications

2024-12-05T03:48:05+00:00

Generative Artificial Intelligence (AI) has been developing rapidly and its application in higher education is becoming more and more widespread. The action research project of generative AI application by teachers in Tianhe District, Guangzhou City and the application case of Chat Generative Pre-trained Transformer are selected to illustrate that generative AI has brought unprecedented changes to many aspects of education and teaching, academic research, student management and services, and intelligent campus construction. However, along with these extensive applications, a series of ethical risk issues have gradually come to the fore. According to existing research, four major ethical risks of generative AI have been proposed: technology ontology risk, educational data risk, machine algorithm risk, and educational application risk. Combined with the literature "Eco-ethics and Risk Mitigation of Generative Artificial Intelligence Educational Applications", we conduct an in-depth analysis and put forward countermeasure suggestions for the risks faced by generative artificial intelligence in higher education. It helps to promote the healthy and sustainable development of generative AI in higher education and the improvement of education quality.

Update Modeling and Decision Analysis of Product Data Based on MATLAB

2024-12-05T03:48:19+00:00

In this paper, the automatic pricing and replenishment decision of vegetable commodities in fresh supermarket are quantitatively analyzed, and a revenue maximization model of vegetable commodities is established, which considers demand forecast, sales revenue, cost plus pricing, replenishment quantity and sales mix. Based on grey prediction and correlation analysis, this paper determined the key factors affecting the demand of vegetable commodities. A model of vegetable commodity income maximization was established by using linear programming, and specific schemes of different replenishment and pricing levels were given. Based on historical sales data and wholesale price data, the daily replenishment volume and pricing strategy of each category and item in the coming week are provided. According to the actual situation, the limit of sales space and the upper limit of production capacity are determined.

Research on the Application of NLP-Driven Opinion Sentiment Tendency Analysis in Precision Marketing of New Energy Vehicles

2024-12-05T03:48:32+00:00

In today's online new media era, online public opinion often influences consumers' purchasing decisions. This dissertation discusses the strategies to promote the development of domestic new energy passenger cars, and combines the comment data of major media platforms, so that enterprises can more accurately understand the public's attitudes and perceptions towards new energy vehicles, and formulate more effective marketing strategies to increase the sales of new energy vehicles. This paper utilizes the nlp sentiment analysis technique, and incorporates 15 original papers to collect nearly 20,000 comments from major websites. It is found that the sales of new energy vehicles continue to rise despite a high proportion of negative online opinions about new energy vehicles, which is closely related to scientific and technological innovations, policy promotion, and consumers' increased acceptance of the concept of green mobility.

Smart sports immersive martial arts teaching mode analysis

2024-12-05T03:48:46+00:00

This paper aims to deeply explore the immersive martial arts teaching mode under the background of intelligent sports. By analyzing the connotation and characteristics of the immersive martial arts teaching mode, its construction elements under the support of intelligent sports technology, including the application of virtual reality (VR), augmented reality (AR), intelligent equipment and other scientific and technological equipment in teaching. Study the influence of this mode on students' learning effect, interest cultivation and wushu inheritance, and put forward corresponding countermeasures for the possible problems in the implementation process, so as to explore a new teaching mode for the innovation and development of martial arts teaching in the new era.

The Sustainable Innovation Impact of AI and Immersive Technology in Information System Management on Education Development

2024-12-05T03:49:02+00:00

Abstract This paper describes the development of artificial intelligence and immersive technology in the field of education. The background of the research was introduced, including the analysis of its application in education from relevant international and domestic research. There are also application status, such as the data processing advantages of AI in education and the role of the squirrel Ai large model, as well as the pilot application of immersive technology in some fields and the improvement of the management of educational information systems. Then, the data generated by the integration of the two in the educational information system and the use of analysis are explained. It also highlights the sustainable innovations that this integration brings, such as optimizing resource allocation, improving educational effectiveness, reducing costs, and promoting educational equity. At the same time, it pointed out the challenges faced by technology convergence and proposed countermeasures to address these challenges.

Literature Review: Immersive Technology as a Teaching Aid in the Health Sector

2024-12-05T03:49:17+00:00

The increasing complexity of healthcare education and the limitations of traditional teaching methods necessitate innovative approaches to meet global demands for skilled professionals. Immersive technologies, including Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and Extended Reality (XR), offer transformative potential by providing interactive, lifelike simulations that bridge theoretical knowledge and practical skills. This study employs a systematic literature review alongside case studies and interviews with educators and students to assess the effectiveness of these technologies in healthcare training. Results reveal significant improvements in learner engagement, conceptual understanding, skill acquisition, and empathy, with particular benefits for inclusive and adaptive learning. However, barriers such as high costs, accessibility challenges, and ethical concerns persist, limiting widespread implementation. Practical recommendations are proposed to overcome these challenges through scalable, cost-effective solutions and interdisciplinary collaboration. This research highlights the global potential of immersive technologies to revolutionize healthcare education, fostering equity, inclusivity, and the development of a competent and empathetic healthcare workforce.

Assistive Eyewear: Arduino Powered Eyeglasses for Blind Individuals

2024-12-05T03:49:51+00:00

The quality of life for individuals with visual impairments has been significantly enhanced by assistive technologies. This paper introduces a new solution called Arduino Powered Eyeglasses (APE) for Blind Individuals tailored specifically for blind individuals. APE integrates sophisticated sensors, microcontrollers, and audio feedback systems into a wearable device, enhancing spatial awareness and navigation capabilities. Utilizing ultrasonic sensors, the system detects obstacles in the user's path and delivers real-time audio feedback through a buzzer embedded in the eyeglasses frame.

Furthermore, it has an embedded vibration motor that acts as a feedback system as well when navigating an outdoor and indoor environment that is noisy. The design, implementation, and preliminary evaluation of APE are presented herein, emphasizing its effectiveness in aiding blind individuals with various daily tasks and promoting independence and mobility. APE's affordability and user-friendly interface position it as a promising solution for empowering individuals with visual impairments to navigate the world with increased confidence and autonomy.

The Role of Data Science in Optimizing Business Decisions in the Digital Era

2024-12-05T03:50:36+00:00

Data science has become a key element in business transformation in the digital era. With the ability to analyze large and diverse datasets, data science helps organizations identify patterns, make predictions, and support strategic decision-making. The application of technologies such as machine learning, big data, and artificial intelligence enables companies to enhance operational efficiency, understand consumer behavior, and create relevant innovations. This article discusses the role of data science in supporting the growth of digital businesses, the challenges faced, and the opportunities companies can leverage to achieve a competitive advantage.

Intelligence Book Recommendation System Using Collaborative Filtering

2024-12-05T03:50:50+00:00

The rapid growth of online literary material has changed the way users discover books, revealing the limitations of traditional recommendation algorithms. This paper presents a review about an intelligent book recommendation system that uses collaborative filtering (CF) and artificial intelligence techniques to address major obstacles such as cold-start issues, data scarcity, and privacy concerns. The suggested method guarantees customized, accurate, and diversified recommendations by merging hybrid approaches such as CF with content-based filtering and matrix factorization. To measure performance, the researchers employ publicly accessible datasets, rigorous preprocessing approaches, and assessment criteria like as accuracy, recall, and F1-score. This project intends to rethink the book discovery process by solving basic issues and applying a privacy-conscious design, while also providing a scalable and user-friendly platform for tailored recommendations.

Cryptocurrency Price Forecasting Using ARIMAX: Conceptual Framework

2024-12-05T03:51:09+00:00

Cryptocurrency, a digital or virtual currency secured by cryptography, has become a dynamic and volatile asset class, presenting both opportunities and challenges for traders and investors. This study aims to develop a web-based application prototype for forecasting Bitcoin prices using the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model. The ARIMAX model, known for its ability to integrate external factors into time series forecasting, is applied to historical Bitcoin price data, utilizing the Crypto Fear and Greed Index as an exogenous variable. By addressing the inherent volatility and unpredictability of Bitcoin's price movements, this study seeks to enhance the reliability of price predictions. Model performance will be evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The resulting web application will deliver real-time price forecasts and analyses, empowering users to make informed decisions and manage risks more effectively in cryptocurrency trading. This research ultimately aims to contribute to advancements in predictive modeling techniques within financial technology, providing traders and investors with a valuable tool for navigating the complex cryptocurrency market.

SHIELD: Symptom-Based Hybrid Intelligent Early Learning for Disease Prediction

2024-12-05T03:51:19+00:00

Traditional diagnostic approaches often face delays and inaccuracies, while standalone machine learning models fail to account for individual uniqueness. The SHIELD system leverages hybrid machine-learning models to enhance disease prediction based on patient symptoms. This study integrates Gradient Boosting, Decision Trees, and Random Forest models, combining their strengths using an ensemble voting approach. A comprehensive dataset from Kaggle, enriched with symptom severity mappings, enables accurate and personalized predictions. The system delivers practical outputs, including disease names, descriptions, and home remedies, through a user-friendly web interface. Achieving an accuracy of approximately 99.59% with the ensemble model, SHIELD demonstrates its potential to revolutionize early disease detection, aligning with global health objectives.

Deep Learning for Meal Recognition and Calorie Estimation

2024-12-05T04:09:35+00:00

Accurate calorie estimates from foods are prerequisite for diet following and health monitoring. Manual calorie estimations according to age-old methods mostly tend to be inaccurate. This paper proposes the use of convolutional neural networks (CNNs) for precise identification from food images and prediction of meal calories to solve the concern. Therefore, the objective is to create a model capable of recognizing foodstuff besides estimating their caloric content. Developing a model that could correctly identify food ingredients and calculate their energy value through training and testing was important in this project. Our aim here was to verify the accuracy of the model using systematic reviewing means as well as an interface where it can be tested. A dataset of 1,337 high-quality images divided into 12 culinary classes cake, hamburger, noodles, spaghetti, pizza, chicken curry, croissant, French fries, fried chicken, roast chicken, lobster nasi goreng, and waffle was obtained from Roboflow Universe and used for this project. The selection of technique which is YOLO (You Only Look Once) model architecture and flow design because it proved to be highly efficient for real-time object recognition.

Early Detection on Company Bankruptcy: a Comparison of Neural Networks and Logistic Regression

2024-12-05T04:12:17+00:00

Detecting firm insolvency at an early stage is crucial for financial analysis and risk management. This study compares the efficacy of two widely used bankruptcy prediction techniques: Neural Networks (NN) and Logistic Regression (LR). We evaluate each approach based on its accuracy, computing efficiency, and interpretability, aiming to identify a suitable predictive model that aligns with specific objectives, data characteristics, and the need for interpretability in financial decision-making. This research indicates that NN provides superior prediction accuracy but is accompanied by increased computing demands and reduced interpretability. In contrast, LR offers more speed, requires fewer processing resources, and provides explicit understanding of variable correlations; however, it may not perform well with intricate and nonlinear data. This study confirms the significance of choosing a suitable predictive model that balances competing demands of accuracy, efficiency, and interpretability in financial decision-making.

Early Prediction of Mental Health Disorder Among Higher Education Students Using Machine Learning

2024-12-06T01:55:39+00:00

In spite of the fact that mental health illnesses are quite common among students in higher education, early detection continues to be a difficult task. This study seeks to determine the use of machine learning to forecast the occurrence of mental health issues in this group. Various machine learning methods were explored to analyze the data collected from higher education students and to identify potential risk factors associated with mental health issues. Through the development of a model that is capable of accurately predicting the risk of mental health illnesses, the project intends to facilitate early intervention and improve the overall well-being of their student population.

Automated Recognition of Medicinal Plants in the Wild: A Leaf-centric Approach

2024-12-06T01:55:57+00:00

This study explores the use of technology to simplify the identification of medicinal plants in the wild by focusing on leaf characteristics. Using convolutional neural networks (CNNs), the research aims to develop a mobile-friendly system tailored to Malaysia’s rich biodiversity and traditional medicine heritage. Key steps include collecting a diverse range of plant data, enhancing image quality through pre-processing, and testing various CNN models to determine the most effective one. Designed for use by both experts and non-experts, such as rural communities and herbalists, the tool integrates advanced AI with traditional knowledge to preserve cultural practices, promote safe natural remedies, and raise awareness about medicinal plants’ role in healthcare and conservation. By addressing the decline in herbal knowledge, this project aims to deliver a practical and accessible solution that supports public health and environmental sustainability.

Implementation of Fish and Plant Nutrition Technology On Aquaponic Systems

2024-12-06T01:56:12+00:00

Catfish farming often faces challenges due to high stress levels in fish caused by instability in water pH and temperature, which disrupt metabolism, reduce appetite, and harm their health. This can lead to nutrient deficiencies for plants in aquaponic systems, causing ecological imbalances. Many farmers still rely on instinct to monitor pond conditions, making it difficult to detect changes in pH, temperature, and nutrient levels promptly, resulting in suboptimal water conditions and high fish mortality rates. To address this, a device equipped with sensors for real-time monitoring of pH, water temperature, and nutrient levels is necessary, helping farmers maintain ecological balance and reduce fish mortality. This research aims to ease catfish farming by integrating an automatic feeding system controlled by a servo and RTC and monitoring critical parameters like pH, temperature, and plant color through Thingspeak. Using the prototype method, the system was developed with ESP32, Arduino Microcontroller, pH sensor, DS18B20 temperature sensor, TCS3200 color sensor, buzzer, and servo. The aquaponics system design included scheduled nutrient supply for fish feed and an accurate feeding process activated at 12:00 PM, running the servo for 2 seconds with a buzzer alert. Testing confirmed the sensors’ ability to transmit data to Thingspeak and display it via LCD. However, the temperature sensor requires periodic calibration, as weather conditions significantly influence readings. During the rainy season, the lowest temperature recorded was 27.10°C, while the highest temperature during summer reached 29.32°C, demonstrating the system’s adaptability across seasons.

Embedding the Management System Information into Circular Education System through the Smart IoT: A Front Analysis

2024-12-06T01:58:22+00:00

This research explored how to embed the management system information into circular education system through the smart IoT. Besides, the front analysis of this research aimed to determined what form of IoT that educators need to help them in organized their system information. This research involving qualitative descriptive methods to get the analytical profound through survey technic within cross sectional design. To harvest the front analysis, this research employed 54 educators from any background study within 54 different school’s department consist of public and private schools. The results show that 85.19% of respondents has been including IoT in their school activity, 5.56% occasionally used IoT, and 9.26% not using IoT yet. The majority of IoT that used are projectors, laptop and CCTV. Besides, the platform that usually used are google and YouTube. In the context of information systems management, 100% of educators argue that they need for specialized IoT that can integrate all learning information systems including learning materials, grades, attendance, and tracking students’ activities. This will enable the information systems management to be transparent and easily accessible to all stakeholders in a circular education system. Based on survey data analysis, teachers expressed a desire for a specialized platform that could involve parents more actively. Additionally, by involving parents, educational transparency can be synergized effectively, ensuring a more robust circular education system. In conclusion, this research recommends for future IoT development to create the IoT that consist of a complete school information management system, and it can be used by students, teachers, and parents, while keeping everyone's information private.

A practical approach to the development of English education in remote areas of China enabled by AI technology

2024-12-06T01:58:36+00:00

With the development of economic globalization, the international status of English is becoming increasingly prominent. Especially in remote areas, the need for English basic education is more urgent. In recent years, the innovation of AI technology has promoted the development of higher quality English education in remote areas, including personalized English learning, intelligent English tutoring system, virtual English learning environment and so on. In the issue of AI-enabled English education, whether it is the technology itself, or the cultivation of ideas and methods, it is global. Therefore, it is necessary to form broader, more comprehensive and deeper cooperation on the network platform on a global scale to promote large-scale innovative talent training.

Digitalization empowers the innovative development of agricultural vocational education

2024-12-06T01:58:52+00:00

AI-empowered high-quality innovation and development of agricultural vocational education is a key step to optimize the allocation of agricultural vocational education resources and improve the level of agricultural vocational education, and it is also an inevitable choice to promote the breakthrough development of agricultural innovation. AI as a means of shortcut, with its unique role, is constantly filling the gap of agricultural talents. At the same time, in the process of the continuous integration and development of AI and agricultural vocational education, certain educational risks have also arisen, and how to correctly avoid risks and promote the high-quality innovation and development of agricultural vocational education is a new topic of the times.

AI empowers the high-quality development of financial and economic college education: opportunities, dilemmas and solutions

2024-12-06T01:59:06+00:00

With the development of the digital economy, AI has gradually given full play to its advantages, improved the overall development of the financial industry, and enhanced the momentum of the industry. For college students in the contemporary financial industry, it is both an opportunity and a challenge. On the basis of analyzing the changes in the financial industry, this paper puts forward the corresponding measures that college students should take for the reference of relevant personnel

Interactive Book Design as a Development Media Children's Fine Motor Skills at Nusa Ceria Islamic Kindergarten

2024-12-06T01:59:21+00:00

Early Childhood Education (PAUD) in Indonesia is very crucial, in accordance with Law No. 20 of 2003 which stipulates early childhood as the period from birth to six years. At this stage, early childhood is a golden period, where the child's brain experiences rapid development to support the child's physical and mental development. However, research shows that children at the Nusa Ceria Islamic Kindergarten, Sumberrejo Village, Lumajang Regency, face difficulties in developing fine motor skills, such as delays in activities such as sticking paper or dry leaves. This difficulty is caused by learning methods that rely too much on basic learning. In addition, the lack of opportunities for environmental exploration and overly protective parenting patterns are also inhibiting factors. To overcome this problem, collaboration between educators and parents in providing stimulation through fun activities and creative media is needed. One proposed solution is the use of interactive books designed to improve children's fine motor, cognitive, language, and social skills as a whole. This book is expected to be an effective external impetus in supporting early childhood development.

Community Archive of Social Culture in FISIP UNPAR Through Communication Visual of Zine Creation “Buku, Pesta, Cinta”

2024-12-06T01:59:53+00:00

This study explores the role of zines as a medium for archiving the socio-cultural heritage of FISIP UNPAR through the creation of Buku, Pesta, Cinta by the community GRAND BUPESTA. Employing a qualitative descriptive methodology, the research examines how visual communication design is utilized to preserve and convey cultural narratives. The zine features photography and narrative text inspired by the urban legends of FISIP UNPAR, employing provocative yet reflective headlines to engage its audience. Results indicate that zines, as grassroots publications, effectively serve as tools for documenting and disseminating cultural identity, showcasing the potential of visual communication in community archiving efforts.

Practical Exploration of College Students' Career Planning in the Perspective of Artificial Intelligence - Analysis Based on the GROW

2024-12-06T02:00:07+00:00

With the rapid advancement of artificial intelligence technology, college students are facing unprecedented opportunities and challenges in career planning. This paper aims to explore how college students can effectively plan their careers in the context of the artificial intelligence era, and conducts practical exploration based on the GROW model. The GROW model is a widely used framework in coaching and consulting fields for setting goals and solving problems, which covers four key stages: goal (Goal), reality (Reality), options (Options), and will (Will). The article analyzes the impact of artificial intelligence on the job market and discusses how college students should use artificial intelligence for career assessment, how to accurately understand the current situation of themselves and the career environment, how to master the application of artificial intelligence in personalized career planning, and how to combine artificial intelligence for education and training related to job seeking. The research results show that the GROW model can assist college students in organizing their career planning in the artificial intelligence era, thereby enhancing their employment competitiveness and career adaptability. In addition, the theoretical guidance and practical paths of career planning in the artificial intelligence era have significant practical significance and application value for college students.

Automated Detection of Hazardous Areas in Railway Stabling Depots Utilizing Passive Infrared Motion Sensors

2024-12-06T02:00:23+00:00

This research project aims to construct a motion sensor indication of hazardous railway depot areas to improve the safety of the crew. The project proposes a localized, solar-powered safety system that will govern the inherent dangers of railway station operations and avert possible accidents. The focus was developing and building a prototype incorporating motion sensor technology that uses visual and audio alerts to alert staff of impending dangers in real-time. This method would therefore design a system that consisted of a Passive Infrared (PIR) motion sensor, a siren alarm, a Light Emitting Diode (LED) indicator, and a manual push button that could activate the alarm, along with a Closed-Circuit Television (CCTV) camera for surveillance purposes and a wireless monitor to improve visibility. The prototype was seen to operate correctly in the experiment, where the motion sensor PIR easily sensed any movement and activated the siren alarm and the LED lights. The CCTV camera plus the wireless monitor supplemented and increased surveillance and visibility factors in the danger zone of safety. In this, this research provides a means of significant enhancement in terms of railway station safety that is through using a locally powered, solar motion sensor activation. The real-time detection and alarm of the system can potentially inform staff of potential dangers in time, thereby preventing accidents and creating a safer environment. Further research should be conducted to upgrade the capabilities and usability in different railway depot scenarios. This may involve evaluating different motion sensors, including additional safety devices, and making field tests to evaluate the system's effectiveness in real application cases.

Navigating the Quantum Era: Exploring Lightweight Quantum-Resistant Cryptography

2024-12-06T02:00:42+00:00

In the realm of cybersecurity, the emergence of quantum computing poses a significant threat to traditional cryptographic methods. Quantum algorithms such as Shor's algorithm challenge the security of widely used cryptographic schemes like ECC. As quantum computers advance, there is an urgent need to develop quantum-resistant cryptographic techniques. This research project aims to address this need by focusing on the development of lightweight quantum-resistant cryptography. The project aims to develop a National Institute of Standards and Technology (NIST) Approved lightweight quantum-resistant cryptographic algorithm that aligns with the resource constraints inherent in diverse applications and devices. By navigating the quantum era, the project seeks to provide practical, efficient, and deployable cryptographic solutions aligned with the resource constraints of diverse applications and devices.

Generalization of Data Science in Financial Management

2024-12-06T02:00:56+00:00

With the rapid development of information technology, data science has been increasingly applied in various fields, and financial management is no exception. As a comprehensive discipline, data science brings new opportunities and challenges to financial management through its powerful data processing and analyzing capabilities. The purpose of this paper is to explore the ubiquity of data science in financial management, and to analyze its impact on financial management and future development trends.

Articles Illustration of “Semangat Pelanusa” on Pelanusa Community Merchandise as a Promotional Media

2024-12-06T02:01:31+00:00

Pelanusa is a community in Malang that focuses on crafts and community empowerment. However, from the many activities carried out by this community, there are still many people who do not know about the Pelanusa community and also ineffective promotional media. This research aims to design illustrations on Pelanusa community merchandise as a promotional medium to introduce the values and identity of the community to the wider community. The research methodology uses a qualitative approach with data collection through interviews and observations and the use of the Design Thinking method which consists of the Empathize, Define, Ideate, Prototype, and Test stages. The results showed that the merchandise successfully attracted the attention of the community, as evidenced by the positive response during the community exhibition at Kebun Winih, Singosari. Visitors were interested in buying merchandise because of its creative design and relevance to the identity of Pelanusa Community. In addition to being a product, this merchandise serves as an effective visual promotional medium, because its use by the community indirectly introduces the community to a wider audience. This research concludes that designing merchandise illustrations can be an effective promotional strategy, while strengthening the image and values of the community.

The Future of Enterprise Systems Integrating Metaverse, Web 3.0, and Extended Reality

2024-12-06T02:01:50+00:00

The convergence of emerging technologies such as the metaverse, Web 3.0, and extended reality (XR) is poised to reshape the landscape of enterprise systems, offering unprecedented opportunities for innovation and user experience. This paper explores the transformative potential of these technologies within the context of enterprise systems, focusing on their implications for user interaction, data management, business processes, and collaboration. We delve into the unique features of each technology and how they can be integrated into existing enterprise systems to enhance user engagement, streamline workflows, and foster new business models. Furthermore, we analyze the challenges and ethical considerations associated with implementing these cutting-edge technologies, highlighting the need for responsible development and ethical guidelines. Ultimately, this paper aims to shed light on the exciting future of enterprise systems as they embrace the transformative power of the metaverse, Web 3.0, and XR, paving the way for a more immersive, interconnected, and innovative business landscape.

Design of Web-Based Administrative Service Information System with Scrum Method

2024-12-06T02:02:08+00:00

In the digital era, information systems have an important role in improving the efficiency of public services, including in administrative services. This research aims to develop a web-based administrative service system as a solution to manual systems that tend to be inefficient. The Scrum method was chosen as the development framework because of its flexibility in adapting to user needs as well as supporting collaboration and continuous improvement. The development stage starts from gathering user needs at the Product Backlog stage, followed by Sprint planning, Sprint implementation, to evaluation of work results through Sprint Review and Sprint Retrospective. The results of the development of this system show that the Scrum approach allows the integration of key features that make it easier to manage data and administrative services. The resulting system has succeeded in improving administrative efficiency and providing better accessibility for users. This research also provides insight into the implementation of the Scrum method in the development of web-based information systems, which can be applied to similar projects to improve the overall quality of public services.

Advancements in Text-to-Image Diffusion Models for Personalized Image Generation: A Review of ID-Preserving Techniques of InstantID

2024-12-06T02:02:34+00:00

The evolution of text-to-image diffusion models, such as GLIDE, DALL-E 2, and Stable Diffusion, has significantly enhanced image generation capabilities. However, achieving image personalization with precise facial detail retention, minimal reference images, and reduced computational costs remains challenging. Traditional methods like DreamBooth and Textual Inversion rely on extensive fine-tuning, while techniques like IP-Adapter, which avoid fine-tuning, often compromise accuracy. Addressing these gaps, InstantID introduces a novel plug-and-play module that uses a single reference image to enable efficient identity preservation with high fidelity and flexibility.

InstantID departs from conventional approaches by employing ID Embedding and an Image Adapter to enhance semantic richness and facial detail fidelity. Unlike models relying on CLIP-based visual prompts, InstantID integrates ID Embedding with ControlNet to refine the cross-attention process. This involves using simplified facial keypoints for conditional input and replacing text prompts with ID Embedding. Trained on a large-scale dataset comprising LAION-Face and additional high-quality annotated images, InstantID demonstrates superior ID retention and facial detail restoration. Notably, its performance improves with multiple reference images but remains highly effective with just one.

The results highlight the effectiveness of InstantID's modular components, such as IdentityNet and the Image Adapter, in ensuring exceptional generation quality and detail retention. Although currently optimized for SDXL checkpoints, InstantID offers a scalable and efficient solution for personalized image generation. By integrating with tools like ComfyUI, it provides a seamless and accessible approach to image personalization with strong ID control and adaptability.

Utilization of YouTube as a Learning Media Algorithms of Programming for Students Informatics Engineering UNIPMA

2024-12-06T02:02:55+00:00

YouTube as an information sharing site is an application that is provided free of charge and is easy to access and use in various activities, on of which is for creating learning media. Learning with YouTube can improve skills and strengthen learning in the form of videos, making it easier to study and develop discussion material for Professional Educators. The purpose of using learning media via YouTube is to help Informatics students understand teaching material more easily and can motivate them to learn. The method in this research uses descriptive qualitative and collects primary and secondary data, namely students who take the 1st semester Algorithms of Programming course, class 1A, 1B, 1C totaling + 50 people and other internet users who watch videos on YouTube and library journals that are relevant to the research topic . The process and steps for making YouTube as a learning media include, 1) Making storyboards for material concepts 2) Making ppt files as discussion material 3) Making learning videos 4) Editing videos 3) Uploading videos to YouTube. The final result was +250 views, comments and likes. Whereas, learning videos can be viewed via the YouTube channel at the link https : // www.youtube.com / watch?v = bRsSFCc8kV0. The conclusion of this research is that using YouTube as a learning media makes learning more interesting, effective and very useful in the learning process and increases student motivation in learning more optimally because it can be played back to understand the material more deeply

Gamifying Human Circulatory System: A Game-Based Learning Application to Enhance Students' Understanding and Retention of Human Body Concepts For Grade 6 Students

2024-12-06T02:03:08+00:00

This thesis developed a gamified mobile learning application designed to enhance Grade 6 students' understanding of circulatory system concepts namedGamifying Human Circulatory System . Acknowledging the rising significance of games in fostering children's engagement in educational pursuits, this research capitalized on the trend by developing a mobile game that not only captures students' interest but also facilitates the comprehension of complex anatomical concepts. Utilizing a pretest-posttest design with paired t-tests for analysis and survey questionnaires based on the ISO 25010 standards , the study reveals a highly significant positive impact on students' knowledge scores. The Gamifying Human Circulatory System application successfully engaged students, transforming the learning of fundamental circulatory system principles into an enjoyable and effective educational experience. These findings underscored the potential of gamified approaches to create an immersive and entertaining educational environment for Grade 6 students. This study provided valuable insights into science education, emphasizing the practical application of gamification to enhance both engagement and comprehension. Focused on the circulatory system, the study supported the idea that gamified learning tools, particularly in the form of mobile games, can positively influence how young learners interact with scientific concepts. The study's outcome demonstrated that incorporating gamified elements into educational tools holds promise in significantly improving students' understanding, making the learning process both informative and enjoyable in the Grade 6 Science curriculum.

Sentilyze: A Bilingual Sentiment Analysis API Using Logistic Regression and Support Vector Machine Algorithms

2024-12-06T02:04:31+00:00

This study introduces a Bilingual Sentiment Analysis API employing Logistic Regression and Support Vector Machine (SVM) algorithms. Using descriptive research methods, the study focuses on the administrative personnel of the External Relations Department (ERD) at Colegio de San Juan de Letran Calamba, with the Director as the primary respondent. Data were collected through interviews and social media content, particularly Facebook posts and comments. The API development followed the Agile Model within the Software Development Life Cycle (SDLC). Results highlight the proposed model’s precision and reliability, with Logistic Regression delivering accuracy and SVM effectively capturing sentiment patterns. Combined, these algorithms achieved a 90.19% accuracy rate across five recorded tests, showcasing the efficiency of automated sentiment analysis in reducing processing time and providing real-time insights. This tool aids the ERD in online reputation management and strategic decision-making by interpreting sentiment data. Furthermore, the research advances natural language processing by addressing sentiment analysis challenges in social media contexts and offering a practical solution for sentiment interpretation. The Bilingual Sentiment Analysis API provides a powerful resource for improving the ERD's capabilities in utilizing sentiment data to enhance communication strategies and operational efficiency.

BioApp: A Mobile Augmented Reality Application to Enhance Junior High School Students’ Academic Performance in the field of Ecological Relationship in Biology.

2024-12-06T02:04:44+00:00

This study investigates student difficulties in understanding biology concepts, particularly during the transition from basic topics like sexuality to complex areas such as genetics. Challenges include reduced engagement and participation, leading to lower performance in assessments. To address these issues, researchers propose "BIOAPP," an Augmented Reality (AR)-based solution designed to enhance learning experiences through interactive and immersive methods. The application prioritizes cost-effective implementation and accessibility, even in low-connectivity areas. The study employs a quantitative research methodology with purposive sampling to assess AR's effectiveness in improving biology education. The resulting mobile game integrates AR to create a dynamic and engaging learning environment, functioning as both an instructional tool and a diagnostic system for tracking student comprehension. This innovative approach aims to renew student interest and participation in biology, offering a transformative and accessible educational solution.

SignTalk: An Assistive Bi-Directional Real-Time Sign Language Mobile Application using MediaPipe, CNN, and GAN

2024-12-06T02:04:57+00:00

In the realm of inclusive education, the hearing-impaired community often faces communication barriers, particularly in educational settings where sign language may not be universally understood. This research study endeavors to address this issue through the development of a bi-directional sign language application tailored to the unique needs of hearing-impaired students, parents, and teachers at Paete Elementary School. Before this research, no dedicated studies or applications have been crafted yet. Employing a quantitative approach via simple random sampling as the instrumentation for the client's population, this study aims to delve into the participants' perspectives. This pioneering initiative provides valuable insights into technology-driven solutions for the communication gap in education for the hearing-impaired. Its findings are poised to significantly contribute to inclusive education and technology-assisted learning, fostering a more accessible educational environment for the hearing-impaired community. The researchers strongly encourage future studies to prioritize technological solutions that cater explicitly to the diverse needs of Special Education (SPED) students or Persons with Disabilities (PWD). Understanding their requirements and challenges is crucial in creating more inclusive and effective applications or tools. Further with research studies understanding their requirements and challenges is important in creating more inclusive and effective applications or tools. Foster interdisciplinary collaborations between technology experts, educators, therapists, and specialists in the field of disability studies. Collaborative efforts can yield comprehensive solutions that integrate technological advancements. KeywordsHearing Impaired Individuals, Sign Language, Sign Talk, Special Education *Correspondence Email:author@email.com

Nutrieye: An Android-Based Food Nutritional Value Recognition App Using Yolov8 Algorithm

2024-12-06T02:05:31+00:00

Good nutrition is essential for a healthy lifestyle, yet many people consume calorie-dense, low-nutrition foods, contributing to malnutrition. While food recognition systems exist, few cater specifically to Filipino dietary needs. This study developed NutriEye, an Android-based app that identifies the nutritional content of common Filipino foods and recommends portion sizes based on user profiles and dietary needs. Using the Food Nutrition and Research Institute's (FNRI) Philippine Food Composition Table and Dietary Reference Intake Chart, the app leverages the YOLOv8 algorithm to analyze food images, estimate nutritional values, and calculate suitable servings. The app's accuracy was tested through evaluation metrics and validated using ISO/IEC 25010 standards for quality, including functionality, efficiency, usability, and security. Feedback from 100 respondents confirmed the app’s effectiveness in promoting better nutrition management tailored for Filipino users.

Enterprise Architecture Planning Information System at Bus Rental Service Company

2024-12-06T02:05:52+00:00

In increasing customer satisfaction, convenience and improving the quality of the company. The company engaged in bus rental services is PT. Transaba wants to have a digital platform and an integrated management system in the Company. One way is to do enterprise architecture planning to find out what systems/applications are urgent to create. The EAP framework provides the direction desired by the Company with its stages, including planning initiation, business modeling, current systems and technologies, data architecture and application architecture, and technology architecture. In this planning, the Company's directions and guidance regarding what must be done first to achieve the objectives, namely Procurement and installation of infrastructure, Customer Management System, Reservation management system, Scheduling and route system and Human Resources Training

Mapping and Prediction Analysis of Rice Fertilizer Use in Paron District, Ngawi Regency using K-Means and Fuzzy Sugeno Methods

2024-12-06T02:06:11+00:00

Clustering and prediction methods are effective tools in overcoming this problem. In this research, the K-Means method was used to map fertilizer needs based on regional characteristics, such as soil type, planting patterns and land productivity levels. This method is able to group regions that have similar characteristics, making it easier to determine optimal fertilizer allocation. Next, the Fuzzy Sugeno method is applied to predict fertilizer needs in the next planting season based on historical data and the results of the grouping that has been carried out. By combining these two methods, it is hoped that the results of this research can provide accurate recommendations for the effective and efficient use of fertilizer. Mapping and predictive analysis on the use of rice fertilizers in Paron District, Ngawi Regency in 12 villages were carried out by referring to the K-Means and Fuzzy Sugeno methods. Mapping with the K-Means Method is done by determining the centroid and clustering, while the prediction mapping using the Fuzzy Sugeno Method is done by determining the variables and fuzzy sets as well as the condition calculation rules. The results obtained are that 2 villages are in the category of low fertilizer use, 3 villages are in the category of medium fertilizer use and 7 villages are in the category of high fertilizer use. Based on the prediction calculation using the Fuzzy Sugeno Method, it was found that the level of error in the comparison of data was 5.36%, meaning that from 100% of the error rate difference, the truth value in calculating the prediction of the use of urea fertilizer using the fuzzy Sugeno method was 94.64%.

The Effectiveness of Watching Movies Using English Subtitles in Teaching Vocabulary

2024-12-06T02:09:08+00:00

This study assesses the effectiveness of using movies with English subtitles for teaching vocabulary. Experimental research refers to a method in which one explores variables for their causing effect through manipulation and observes the impact on another variable. The present study was conducted experimentally with SMPN 1 Peukan Bada grade VIII students. The study's sample consists of 57 students divided into two classes: one, VIII 5, as an experimental class in which the movies were shown with subtitles in English, and the other, VIII 7, as a control class where the movie was presented without subtitles. Data has been collected in the form of pre-and post-tests to measure the improvement in vocabulary acquisition by students. The average of pre-tests was 58 for the experimental and 56 for the control classes. It was observed that the experimental class had a steep increase in their vocabulary score as compared to the control class. The mean post-test score of the experimental class was 90 while the average of the control class climbed up to 76. Data were analyzed using both independent t-tests and paired t-tests to determine the significance of differences between the two groups by SPSS. The results of the statistical analysis indicated that there was indeed a significant difference between the two classes, with the p-value less than <0.001. Therefore, it would be proper to conclude that the use of English subtitles while watching movies effectively enhances vocabulary acquisition for students.

Sustainable Business Model: MSME System Digitalization and Its Impact on Profitability

2024-12-06T02:09:23+00:00

Micro, Small, and Medium Enterprises (MSMEs) are the backbone of the economy in many countries, including Indonesia. MSMEs make significant contributions to job creation, local economies, and social stability. However, many MSMEs face significant challenges in managing supply chains, product distribution, and marketing, which often hinder their growth potential. The digitalization of MSME systems emerges as a solution to address these issues, as technology enables automation, operational efficiency, and expanded market access. This article explores the concept of a sustainable business model that integrates digitalization into MSME operational systems and its impact on profitability. The main focus of this study is on how digital technology can improve efficiency, open new markets, and drive long-term sustainability. By including case analyses, data, and relevant illustrations, this article aims to provide practical insights for MSMEs to optimize their digitalization efforts for higher profitability.

Challenges in Supply Chain Management for MSMEs in Maintaining Financial Stability in the Digital Era

2024-12-06T02:09:40+00:00

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role as a cornerstone of the economy in various countries, including Indonesia. However, the era of globalization and digitalization presents complex challenges in supply chain management that threaten the financial stability of MSMEs. Some of the key issues faced include dependency on single suppliers, limited access to digital technology, minimal transparency within the supply chain, and rapidly changing global market dynamics. These obstacles often lead to uncertainty in inventory management, increased operational costs, and reduced production efficiency. This article not only identifies these challenges but also provides an in-depth analysis of their impact on the sustainability of MSMEs. Using a solution-based approach, the article offers practical strategies such as supplier diversification to mitigate dependency risks, digital technology integration to enhance supply chain efficiency, and collaboration within supply chain ecosystems to create stronger synergies. Furthermore, the article discusses the role of governments and business communities in supporting digital infrastructure development and providing training for MSMEs to adapt to technological changes.To illustrate the implementation of these strategies, the article includes flowcharts, graphs, and real-world case analyses as practical guides for MSMEs. With this approach, MSMEs are expected to maintain financial stability, improve competitiveness, and achieve sustainable growth amidst the challenges of globalization and digital transformation.

Digital Financial Strategies in Managing SMEs to Maximize Profitability

2024-12-06T02:09:55+00:00

Micro, Small, and Medium Enterprises (MSMEs) are the backbone of the Indonesian economy. However, they continue to face significant challenges in financial management. Key issues include a lack of financial literacy, manual record-keeping prone to errors, limited access to formal financial services, and minimal adoption of digital technology. These obstacles often lead to operational inefficiencies, data-less decision-making, and low market competitiveness. Digital financial solutions emerge as innovative tools to address these challenges. By leveraging digital technology, MSMEs can enhance operational efficiency, accelerate transactions, support strategic decision-making, and improve access to formal financial services. This article explores various benefits of digital financial solutions, ranging from financial transparency and cost savings to the potential for significantly increasing profitability. Additionally, the article presents practical and relevant digitalization strategies for MSMEs, including step-by-step adoption approaches and case studies of successful MSMEs that have embraced technology. Through the use of illustrations such as graphics, flowcharts, and real-world examples, this article aims to provide actionable and inspiring insights for MSME players in optimizing digital finance. By doing so, MSMEs can achieve sustainable business practices and improve competitiveness in the digital economy era.

Assessment of Cultural Sensitivity in the ChatGPT’s Translation of the Acehnese Chronicle ‘Ali Peureudan’

2024-12-06T02:10:08+00:00

Cultural sensitivity is an integral aspect in translation to ensure the preservation of context and meanings, allowing the readers to grasp the intended meanings; however, this aspect was often omitted and still highly under-researched. The research aimed to examine cultural sensitivity in the ChatGPT’s English translation of the Acehnese Chronicle of Ali Peureudan originated from Aceh Province, Indonesia. The story contains culturally-specific phrases in Acehnese and Arabic languages. The research was a Comparative Literary Analysis which is descriptive qualitative in nature. The source text (ST) and Target Text (TT) generated by ChatGPT were compared and analyzed carefully using the Translation Quality Assessment developed by Juliane House (2015). There were 26 cultural phrases in total under analysis. The results revealed that 85% of ChatGPT’s renditions of culturally-bound terms were covert, which means that the phrases were adapted to the target language norms (English), such as Allah as ‘God’, Insya Allah as ‘God willing’, and ‘Surat’ as ‘Wish’, causing a loss of cultural nuance, generalization, semantic narrowing, and meaning distortions. Only 15% of the analyzed phrases were translated overly by maintaining their original versions, avoiding diminution of cultural meanings. Of the 15%, only a single word was found to be kept intact in its original version yet accompanied by a meaning description, namely the word Alhamdulillah (Praise be to God). Such strategy protects its originality, avoids erasure of cultural details, as well as provides understanding to the target readers of its intended meaning. This research concludes that ChatGPT still lacks cultural sensitivity in rendering a literary work. This research is expected to be a foundation for those using ChatGPT as a translation tool for such culturally sensitive texts, and provide an input to ChatGPT developers to improve its system for more accurate rendition.

Effectiveness of ChatGPT vs. Perplexity AI in English Language Learning at the University of Serambi Mekkah

2024-12-06T02:10:24+00:00

This study aims to compare the effectiveness of ChatGPT and Perplexity AI in the English Language Learning. It employs a mixed-method approach to determine the effectiveness of the two AI tools, ChatGPT and Perplexity AI, in improving English language learning at the University of Serambi Mekkah. Questionnaires and interviews were used to collect data. The results showed that 73.3% of participants favored the use of ChatGPT because of its interactive features and easy navigation. Sixty percent believed that ChatGPT provides more accurate information as opposed to Perplexity AI. This helps to motivate the learners and boost their confidence in using the language. Their counterpart, Perplexity AI, was preferred by a minority of respondents (13.3%) for its speed and accuracy. In this respect, ChatGPT was rated by participants as “highly effective” in improving their English skills, and 40% were “highly satisfied”. In contrast, only 26.7% considered Perplexity AI more effective and satisfying. Though ChatGPT is undeniably favored, the study acknowledges how Perplexity AI may serve as customized support, in satisfying specific needs regarding language learning. Both are very helpful for English language acquisition, though ChatGPT is favored because it is more appealing. These findings would be useful to educators in incorporating appropriate AI technologies into language curricula to meet various learners' needs and improve learning outcomes. This research has emphasized how AI tools support the more conventional ways of teaching a language and gives useful insight that is relevant to further education.

New Energy Vehicle Brand Sales Trend Forecast and User Evaluation Research

2024-12-06T02:10:37+00:00

In the context of green economic development, new energy vehicles, as one of the representatives of innovation-driven development and environmental protection and energy conservation, are currently in a leading position in the market. This paper selects eight representative well-known brands, namely BYD, Li Auto, Xiaopeng, Geely, NIO, Changan Automobile, SAIC-GM and ORA, for quantitative analysis, with the aim of identifying future sales trends and conducting a precise business evaluation of new energy vehicles, as well as exploring the key factors affecting sales. The study was empirically tested using ARIMA time series forecasting, principal component analysis, linear regression analysis and neural network models. The results showed that brand identification behavior and personalized products have the most significant positive impact on sales. Therefore, this study believes that car brand collection, forwarding, personalized production and quality control are the key factors and improvement priorities that will affect future sales.

The Innovative Path of AI Technology Empowering Marketing Strategy in Unmanned Supermarkets

2024-12-06T02:10:50+00:00

This research , whose research objects are users’ experiences, is a quantitative research t through methods such as literature method, questionnaire survey, and data analysis. The results show that the impact of unmanned supermarket technology on shopping experience, the evaluation of unmanned supermarket service and safety, and the correlation between technical difficulties and shopping frequency are the most important factors affecting user experience. Among them, the diversity of checkout technology and service response speed contribute the most. These analysis results provide important theoretical support and reference for unmanned supermarkets to optimize user experience in the future. At the same time, they are of great significance for optimizing the operation mode of new retail and meeting users' diverse consumption needs. Furthermore, they offer practical insights for enhancing the integration of AI technology to improve service efficiency, operational processes, and customer satisfaction, further supporting the sustainable growth and competitiveness of unmanned supermarkets in the evolving retail landscape.

Depth Study of User Purchase Influencing Factors in Platform E-commerce under the Background of Big Data and AI

2024-12-06T02:11:01+00:00

Taking Taobao as a typical platform e-commerce, this study is devoted to exploring how big data and artificial intelligence technology can empower platform e-commerce and affect users' purchase intention. This paper adopts the empirical research method, collects data through online questionnaire, uses spss26 for regression analysis, and adopts the gradient lifting algorithm of machine learning model for data verification. The research results show that marketing activities such as "precise placement", "personal privacy", "product details" and "product ranking", which rely on big data and artificial intelligence technology, are the key factors affecting Taobao users' purchase intention, and their impact coefficients are 0.57, 0.135 and 0.288 respectively. Inventory management, profile building and personalized recommendations are also important factors. This paper takes the Consumer Behavior Analysis Model (AISAS) as the theoretical basis, and puts forward corresponding suggestions for Taobao platform e-commerce to enhance user attention, interest, search, purchase and sharing under the background of big data and artificial intelligence technology application.

Progress in the Application of Artificial Intelligence in Mental Health Education for College Students in Universities

2024-12-06T02:11:14+00:00

The purpose of this paper is to explore how artificial intelligence technology can help mental health education in colleges and universities, analyse the progress of its application in personalised education, mental health monitoring and evaluation, ecological transient intervention, etc., and analyse its current situation, strengths, challenges, and future development direction.

Research on the Development of Intelligent Financial Education in the Era of Artificial Intelligence

2024-12-06T02:11:27+00:00

With the continuous progress of the digital era, artificial intelligence is increasingly interwoven with various fields. This paper focuses on the current status of financial management courses, applies the SWOT analysis method to analyze the current situation of the development of financial education, proposes the problems existing in current courses, discusses the limitations of traditional teaching, explores the application of AI technology in financial management education, improves and refines course design, breaks the limitations of traditional teaching methods, emphasizes the integration of theory and practice, enhances students' professional competence, cultivates financial management thinking, and builds an intelligent teaching platform. On this basis, it discusses the specific applications of AI in three parts: designing basic courses, cultivating professional competence and thinking, and building a teaching platform. The aim is to innovate financial management education, promote its sustainable and innovative development, and cultivate high-quality talents who can meet the needs of the future financial industry.

Review and Prospect of Research on the Application of VR Technology in Education and Teaching Analysis based on citespace knowledge graphs

2024-12-06T02:11:44+00:00

This paper analyzes 863 China Knowledge Network (CNN) source documents using CiteSpaceV6.3.R1 software, and sorts out the current research status and development trend of VR technology in education and teaching by mapping the relevant knowledge map of keywords, issuing authors, and issuing institutions. It is found that the research on VR technology in education and teaching has experienced a slow growth from its start in 1996 to 2015, and then a significant growth after 2017 with interdisciplinary characteristics. In terms of authors and institutions, as the cooperation on this related topic is still small and very scattered, but there are some research teams cooperating with each other, and the research hotspots cover virtual reality, information technology, vr technology, education and teaching, and teaching tools. In the future, research in this field should show the following trends: deepen interdisciplinary integration and expand VR education applications; strengthen empirical research and verify the effectiveness of the technology; pay attention to ethical privacy and build a responsible education ecology.

Application Practice and Innovative Exploration of AIED Technology in the Education of Rural Left-behind Children

2024-12-06T02:11:58+00:00

This study focuses on the application practice and innovative exploration of Artificial Intelligence in Education (AIED) in promoting the education of rural left-behind children. By comprehensively utilizing methods such as literature review and field case analysis, and through in-depth mining and visual presentation of core literature in the field of AIED over the past five years, the study aims to reveal its positive roles in balanced allocation of educational resources, improvement of teaching quality, and innovation of learning modes. The research findings indicate that AIED technology effectively alleviates the shortage of educational resources faced by rural left-behind children, and significantly narrows the urban-rural education gap, by integrating high-quality educational resources from across the country and even globally, building personalized learning platforms, and implementing a dual-teacher teaching mode of "online master teacher + offline tutoring". In terms of enhancing learning outcomes, AIED technology not only improves students' academic performance but also strengthens the mental health of left-behind children through intelligent mental health monitoring and intervention.

AI Empowers Graphic Design Education: Innovation and Breakthrough

2024-12-06T02:12:10+00:00

In the 1950s, the scientific community first proposed the term "Artificial Intelligence" (AI). Against the backdrop of rapid technological development in the 21st century, the application fields of AI technology are becoming increasingly widespread, penetrating every corner of our work and life. From the perspective of AI's impact on graphic design education, it can provide designers with more inspiration, express more accurately what designers want to convey, and also promote the updating of graphic design course content, thereby continuously cultivating students' comprehensive abilities. AI's integration into graphic design education has led to the development of intelligent design tools that can automatically generate design drafts based on given parameters, thus significantly reducing the time required for the initial design phase. Moreover, AI can analyze trends and user preferences, offering designers insights that can guide their creative process. As a result, the educational curriculum must evolve to include the study of AI algorithms and their applications in design, ensuring that future designers are well-equipped to leverage these powerful tools. This shift not only enhances the efficiency and innovation in the design field but also prepares students for the demands of a future job market that will increasingly rely on AI-assisted design solutions.

Research on the Asset Liability Management Mechanism of Commercial Banks Taking Silicon Valley Bank as an Example

2024-12-06T02:12:19+00:00

Since 2023, the bank bankruptcy incidents in the United States, represented by Silicon Valley Bank, have continued to ferment, causing bank runs and capital market turmoil, and spreading panic in the financial market. This article takes Silicon Valley Bank as an example to review the beginning and end of the bankruptcy event caused by the liquidity crisis, and analyzes the reasons for its bankruptcy from internal factors such as bank asset liability maturity mismatch, weakened capital adequacy ratio, and lack of risk management measures, as well as external environmental factors such as the Federal Reserve's aggressive interest rate hike and the cold winter of Silicon Valley technology industry, On this basis, suggestions are proposed for optimizing asset liability structure management and strengthening risk warning and regulatory mechanisms in China's banking industry risk management. Based on the strategic orientation of promoting high-quality development of the financial industry in China, this article provides industry insights from the analysis of the bankruptcy events of Silicon Valley banks, which has certain practical value for strengthening risk management and supervision of banking institutions in China.

Research on Financial Risk Assessment and Control based on New energy vehicle manufacturing industry

2024-12-06T02:12:35+00:00

This paper analyzes the differentiated growth path and business strategy effect of new energy car manufacturing companies NIO, Xiaopeng and Lixiang. Starting with financial performance analysis, Z-Score model is used to analyze the yearly changes of X variable and Z value of the three companies based on their financial data from 2019-2023, and carry out financial capability analysis and financial risk assessment. In the market environment of intensified competition, this paper explores the common problems of new energy car making new power companies, improves the system of measures in order to help enterprises reduce financial risks, maintain stable operations, and provide a reference for many new energy automobile manufacturing companies.

An Exploration of AI-Assisted Tools in the Education of Children with Autism from the Perspective of Inclusive Education

2024-12-06T02:12:50+00:00

With the rapid development of Artificial Intelligence (AI) technology and its widespread use in education, it is becoming increasingly feasible to build more personalized and supportive learning environments for children with autism. The aim of this paper is to explore how AI-assisted tools can promote inclusive education, with a particular focus on the specific group of children with autism. Through keyword searches of relevant papers in mainstream conferences and journals, as well as a comprehensive analysis of existing literature and case studies, we have conducted a systematic review of AI as an aid to promote inclusive education, aiming to provide valuable references for subsequent research. Studies have shown that when AI technology is appropriately applied, it can significantly enhance the social interaction skills, emotional regulation, and academic performance of children with autism. However, it is important to note that most of the current research findings focus on work published within the last few years, and thus may not fully cover relevant contributions from earlier periods. In summary, by examining the current situation of AI applied to the education of children with autism in China, we can see that AI as an assistive tool shows great potential for development and plays a crucial role in realizing inclusive education in the true sense of the word. This not only promotes educational equity, but also provides more opportunities for each child to grow.

Computer Hardware Resources E-commerce Platform Based on Intelligent Recommendation and High Concurrency Processing - "Beiji Technology"

2024-12-06T02:13:07+00:00

With the rapid development of e-commerce and the diversification of the computer hardware market, consumers are facing more and more difficulties in choosing computer accessories, and traditional e-commerce platforms are difficult to meet the user's demand for accurate shopping and efficient recommendation. The purpose of this paper is to build an intelligent computer accessories shopping platform (Beiji Technology), through intelligent recommendation algorithms, to improve the user shopping experience. The platform adopts mainstream front-end technology, efficient and stable back-end architecture, supports high concurrency data processing, and at the same time realizes dynamic interaction, which enhances the responsiveness and smoothness of the user interface. Its intelligent recommendation system generates personalized accessory recommendations based on the user's historical behavior, helping users find the products they need faster. The realization of this platform not only solves the pain points of traditional e-commerce platforms in the purchase of computer accessories, but also promotes the development of the e-commerce industry in the direction of intelligence and precision, and provides valuable references for the future research and practice of intelligent e-commerce.

From Waste to Worth: Unlocking the Potential of Liquid Biomethane for a Decarbonized Energy Future

2024-12-06T02:13:46+00:00

Liquid biomethane (LBM), derived from purified biogas, is a low-carbon, renewable energy source that can contribute to energy security and climate change mitigation. LBM produces a transportable, high-density fuel that can replace fossil fuels in a range of industries by turning organic waste into a liquid energy source. This study looks at the properties of liquid biomethane, the processes required to produce and liquefy it, and its use in transportation, industry, and power generation. The report highlights the ways in which LBM advances worldwide decarbonization efforts, reduces greenhouse gas emissions, and aids in waste management. Technical challenges and emerging opportunities are also discussed to chart the path for LBM's adoption in a sustainable energy future.

E Evaluation of Bandwidth and Latency of Wireless Sensor Networks Using JPERF Simulation

2024-12-06T02:14:42+00:00

WSN is a sensor network that uses wireless communication to connect sensor nodes This research discusses the evaluation of wireless sensor networks (WSN) which was a case study carried out at the Banda Aceh Mayor's Office, with a focus on measuring bandwidth and latency using the JPerf application. Testing is carried out through star topology simulation, where the server and client are connected to each other via an access point. The TCP protocol is used for bandwidth measurements, while the UDP protocol is used for latency measurements. Test results show the average bandwidth ranges from 7,518-8,029 Kbits/s with significant fluctuations due to network interference. Network latency was recorded as stable at 996 Kbits/s with low jitter. This evaluation provides recommendations for improving network performance through optimizing QoS management and strategic device placement. With this implementation, network reliability can be increased to support operational activities efficiently.

SOA-Based IT Infrastructure Planning Strategy to Optimize Network Management in Companies

2024-12-06T02:15:52+00:00

This research aims to develop a Service Oriented Architecture (SOA)-based information technology (IT) infrastructure planning strategy to optimize network management in the company. In the increasingly complex digital context, companies require flexible and integrated IT infrastructure to enhance operational efficiency. The methodology used includes stakeholder needs analysis and mapping of network management functions based on the FCAPS reference. (Fault, Configuration, Accounting, Performance, Security). Through interviews and observations of the current infrastructure conditions, this research found that the implementation of SOA can enhance interoperability between applications and simplify the management of IT resources. The resulting design includes logical and physical topologies aimed at improving the reliability and security of the network management system. It is expected that the implementation of this strategy will enhance service performance and provide added value to the company in facing dynamic business challenges.

Advamcement of Technology and ITS Impact on Modern Society

2024-12-06T02:16:06+00:00

This study explores the rapid advancements in technology and their impact on modern society, focusing on sectors such as communication, healthcare, education, transportation, and entertainment. It examines the positive contributions of technological innovations while addressing challenges like cybersecurity threats, privacy concerns, and automation. The research employs qualitative analysis, integrating data from various academic sources. The findings reveal that technological advancements significantly improve efficiency and accessibility, but ethical considerations are crucial for sustainable progress.

Hospital Management Information System in Increasing Efficiency

2024-12-06T02:16:36+00:00

Healthcare services are the main topic because of the high complexity challenges in the health sector. The purpose of this study is to determine the implementation of Hospital Information System (HIS) in increasing the efficency of healthcare services. The research design used in this article is a literature review method related to Hospital Information Systems in supporting the efficiency of hospital services using databases. In this study, the researcher collected literature review data with a thematic structure based on the concept of thinking using the keywords "hospital information system", "information system efficiency", and "healthcare efficiency" which were compiled to answer scientific questions by grouping and discussing literature sources accordingly to the theme or topic. The results showed that Hospital Information System can minimize the complexity of healthcare services by increasing organizational efficiency through innovation in developing information system based on business process management, service automation, reducing costs, improving hospital performance, which aims to develop human resources, organizational development, and technological quality improvement to achieve efficency in healthcare services.

Improving Network Security: Protection Strategies in the Digital Age

2024-12-06T02:16:48+00:00

Network security is an important factor in protecting data in the digital era. Threats such as DDoS attacks and malware can damage information systems. This article discusses network protection strategies, including the use of firewalls, encryption, VPNs, and Zero Trust Security. In addition, the implementation of multi-factor authentication and user awareness are also identified as crucial mitigation measures. By utilizing technologies such as artificial intelligence, threat detection can be done more efficiently. This research aims to provide practical solutions to improve network security and reduce the risk of cyber attacks.

The Role of Software Engineering in Digital Transformation of Industry 4.0

2024-12-06T02:17:10+00:00

Industry 4.0 is characterized by the adoption of advanced technologies that are changing the way companies operate, interact with customers, and produce products. One of the key factors in the success of digital transformation in this era is software engineering. Innovative and flexible software is the foundation for the implementation of technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data, and automation that support modern industrial operations. This article discusses the critical role of software engineering in accelerating the adoption of Industry 4.0, with a focus on developing software that supports interoperability, scalability, and security in an ever-evolving digital ecosystem. It also discusses the challenges faced by software developers, including the need for new skills, integration of legacy systems, and management of big data generated by devices and sensors. With the right software engineering approach, companies can harness the full potential of Industry 4.0 technologies to improve operational efficiency, productivity, and innovation.(Furstenau et al., 2020)

Mengoptimalkan Bisnis dengan IoT: Solusi Cerdas untuk Masa Depan

2024-12-06T02:18:17+00:00

internet of Things (IoT) telah menjadi teknologi yang sangat relevan dalam mengoptimalkan bisnis di berbagai sektor. Penelitian ini bertujuan untuk mengeksplorasi bagaimana IoT dapat meningkatkan efisiensi operasional, mengurangi biaya, serta memberikan wawasan lebih dalam untuk pengambilan keputusan berbasis data dalam bisnis. Melalui survei dan wawancara dengan para profesional di industri yang telah mengadopsi IoT, penelitian ini menemukan bahwa penggunaan IoT di berbagai bidang seperti manufaktur, logistik, dan ritel memberikan manfaat yang signifikan dalam meningkatkan produktivitas, pengelolaan sumber daya, dan pengalaman pelanggan. Namun, tantangan utama yang dihadapi adalah masalah keamanan data dan integrasi dengan sistem yang ada. Penelitian ini menyimpulkan bahwa meskipun tantangan tersebut ada, potensi besar IoT dalam mengoptimalkan bisnis memberikan keunggulan kompetitif yang signifikan bagi perusahaan yang dapat mengelolanya dengan baik.

ERP Effectiveness in Improving Production Efficiency

2024-12-06T02:19:13+00:00

This research specifically investigates how the implementation of ERP systems impacts the operational performance of manufacturing companies. By analyzing the literature and conducting case studies, this research uncovers potential efficiency improvements in various aspects, including reduced production time, optimized use of resources, and improved data quality. The results of this study are expected to provide valuable recommendations for manufacturing companies in implementing ERP effectively and achieving competitive advantage.

IT Infrastructure Security Optimization Strategies for Today's Organizations

2024-12-06T02:19:26+00:00

Information technology (IT) infrastructure security is one of the top priorities for organizations in the digital age. The rapid adoption of technologies such as cloud computing, the Internet of Things (IoT), and artificial intelligence has presented great opportunities for innovation, but also increased the risk of cyberattacks, data theft, and system vulnerabilities. This research aims to identify and develop IT infrastructure security optimization strategies that can enhance the protection of an organization's digital assets. The approach used includes risk analysis, implementation of a comprehensive security framework, and adoption of advanced defense technologies such as encryption, next-generation firewalls, and artificial intelligence-based threat detection systems. The results show that an integrated, adaptive strategy supported by solid policies can improve system resilience while supporting operational flexibility. Thus, this research provides practical recommendations for organizations to build an IT infrastructure that is secure, resilient, and ready to face future challenges.

Image Classification of Organic and Inorganic Waste Using Convolutional Neural Networks

2024-12-06T02:19:43+00:00

Indonesia will become the third largest contributor of plastic waste in the world in 2024. This is due to the suboptimal management and recycling of waste. One way to reduce the accumulation of waste in the environment is through waste separation as the first step in recycling. In the field of informatics engineering, this process can be implemented using Convolutional Neural Network (CNN), a deep learning method designed to recognize and classify objects in digital images. This study aims to develop a high-accuracy CNN model for waste type classification using the TensorFlow framework. The analysis was carried out to determine the most appropriate CNN architecture in separating waste optimally. By implementing this algorithm, an automatic waste separation system can be built to support the efficiency of the recycling process. This research is expected to accelerate and simplify the waste separation process, while encouraging more effective waste management.

Leveraging AI and Data Science to Increase Student Engagement through Interactive Learning

2024-12-06T02:22:04+00:00

Student engagement in the learning process is often a challenge, especially in modern educational environments that require adaptation to interactive technology. This research aims to explore the application of artificial intelligence (AI) and data science in increasing student engagement through interactive learning. This research uses quantitative methods with a descriptive approach, analyzing participation data, system interactions, motivation, age and education level from 50 students at the upper secondary level. The results showed that the average frequency of student participation reached 12.86 times per week with a standard deviation of 4.19,indicating that although the involvement of most students was quite high, there was still significant variation. Learning system interactions had an average of 27.8 times, indicating that
students actively utilized available technology, with a minimum of 10 times and a maximum of 49 times during the observation period. In terms of student motivation, the average Likert score is 4.02 on a scale of 1–5, indicating a high level of motivation, with a maximum score of 4.94. The average age of students is 15.38 years, with the majority being in grade 12, according to the mode in the education level variable. Further analysis shows that these variables have a positive correlation in supporting student engagement. This shows that the use of AI-based technology can encourage students to be more actively involved in learning, while maintaining their high levels of motivation. This research concludes that the application of AI and data science can be an effective solution to increase student engagement, especially if the system is designed personally and adaptively according to individual characteristics.

Telegram FAQ Chatbot Design for Budi Mulia Lawang Junior High School

2024-12-06T02:20:34+00:00

This study effectively created and assessed an academic services chatbot that employs Natural Language Processing (NLP) and Artificial Neural Networks (ANN). It demonstrates a thorough methodology that includes data collection, preprocessing, model training, and performance evaluation. The dataset was meticulously derived from frequently asked questions at the Institute of Business and Technology Asia Malang, ensuring its relevance and applicability to the target audience. Thorough preprocessing methods, such as tokenization, stemming, and the removal of stop words, were utilized to elevate the quality of the input data for the ANN model, leading to a notable enhancement in its performance. The training outcomes demonstrated a significant relationship between the number of training epochs and the accuracy of the chatbot's responses, suggesting that more extensive training resulted in improved performance. Additionally, the measurement tool employed for user feedback demonstrated confirmed validity and reliability, evidenced by a Cronbach's Alpha coefficient of 0.965, highlighting the strength of the data gathered. A study conducted with 37 students revealed a significant level of satisfaction regarding the chatbot's performance, which attained an impeccable accuracy score of 100%. The results underscore the promise of chatbots powered by natural language processing to improve academic information services, efficiently responding to student questions and markedly alleviating the burden on academic personnel. This study provides a significant framework for educational institutions looking to adopt AI-driven solutions to enhance their academic support services and enrich the student experience.

Design of an Academic Services Chatbot at Asia Institute Malang

2024-12-06T02:22:34+00:00

This study successfully developed and evaluated an academic services chatbot utilizing Natural Language Processing (NLP) and Artificial Neural Networks (ANN), showcasing a comprehensive methodology that encompassed data collection, preprocessing, model training, and performance evaluation. We meticulously derived the dataset from frequently asked questions at the Asia Institute of Technology and Business Malang, ensuring its relevance and applicability to the target audience. Rigorous preprocessing techniques, including tokenization, stemming, and stop words removal, were employed to enhance the quality of the input data for the ANN model, which significantly improved its performance. The training results revealed a strong correlation between the number of training epochs and the accuracy of the chatbot's responses, indicating that increased training led to enhanced performance. Furthermore, a Cronbach's Alpha coefficient of 0.965 confirmed the validity and reliability of the measurement tool for user feedback, highlighting the robustness of the collected data. User testing involving 37 students indicated a high level of satisfaction with the chatbot's performance, as it achieved a perfect accuracy score of 100%. These findings highlight the potential of NLP-based chatbots to enhance academic information services, effectively addressing student inquiries while significantly reducing the workload on academic staff. This study serves as a valuable model for other educational institutions aiming to implement AI-powered solutions to improve their academic support services and overall student experience.

Development of an Interest- and Skill-Based Expert System for Student Career Decisions

2024-12-06T02:23:30+00:00

This study examines an expert system for assessing student career paths based on interests and competencies. This approach is intended to assist Informatics Engineering students in identifying a career trajectory that aligns with their profile. This system is anticipated to be an effective solution, given the growing demand for students to receive pertinent career guidance, as numerous students encounter difficulty in selecting a career path that aligns with their competencies. This expert system is developed by aggregating data concerning students' interests and skills, thereafter processed through the forward chaining approach to align facts and rules inside the knowledge base. Furthermore, the certainty factor approach is employed to assess the degree of certainty for each career recommendation provided. The algorithm can generate pertinent career recommendations depending on the student profile and the degree of certainty of the results. The system is evaluated against expert suggestions to verify the accuracy and relevance of the outcomes. The testing of several datasets indicates that the algorithm can deliver career suggestions aligned with expert outcomes. The findings indicate that 100% of the test outcomes align with the validation results provided by experts. So, this system can be a useful tool that helps students choose a job path and can also help with career counseling at schools.

Transforming Real Estate Marketing with Augmented Reality Technology

2024-12-06T02:23:41+00:00

As the world moves toward a more digitally-first environment, the real estate industry is evolving to meet the expectations of today's buyers. People are looking for technologically innovative and entertaining methods to explore properties without leaving the house. This study proposes a cutting-edge virtual tour application based on Augmented Reality (AR) that can transform the tiresome and demanding procedure of seeing properties. Customers may use their smart devices to virtually walk around residences, interact with aspects such as doors and lights, and obtain a 360-degree view of the entire property. The main objective of this research is to demonstrate how AR can reform the real estate industry by replacing expensive static show units with a dynamic, eco-friendly, and globally accessible solution. The app is developed using tools such as Unity 3D, Vuforia SDK, and SketchUp. The research highlights the potential of the app to create a more sustainable marketing approach. It also helps meet the growing demands for a more personalized experience for tech-savvy buyers. Results from the initial testing have shown increased customer engagement and satisfaction levels. The study concludes that integrating AR with property sales can be a very cost-effective, accessible, and scalable alternative with future potential for more enhanced, cross-platform usage, and international reach.

Web-Based Village Population Data Management System

2024-12-06T02:24:17+00:00

Village Government is one of the governments in charge of organizing and managing resources in government at the Village level and has the obligation to administer population data. Currently, the Coal Village office is still handling the population data administration process manually. The system is still manual and uses Microsoft Word and Microsoft Excel, of course there are still many errors or shortcomings in the data processing process, which can slow down the process of adding data, searching for data and storing data. Apart from that, archiving files is less organized so it will make it difficult to find data. In an effort to overcome the problems above, a new website-based system is needed that will help management speed up and accurate population data. This computerized system will eliminate file accumulation. To achieve the objectives outlined above, this was done by conducting observations through interviews with the Village government to obtain needs for problems that often occur when managing population data. What is then carried out is system analysis, identifying user needs, process mapping, identifying frequently occurring problems, mapping system requirements so that it is hoped that the implementation of the right solution can be realized according to user needs. In an effort to overcome the problems above, a new website-based system is needed which will assist Village management in speed and accuracy of population data. With this population data processing information system, satisfaction in the service process can not only be felt by the community who act as customers, but can also be felt by all staff at the Coal Village Office because the recording and storage process becomes easier to manage.

Infographic Posters at Sumber Gentong Natural Tourism as an Information Medium

2024-12-06T02:25:37+00:00

Infographic posters have significant potential to enhance visitor understanding of the Sumber Gentong tourist destination. This study aims to analyze how infographics can be utilized as an effective visual communication tool to convey information about facilities, regulations, and conservation values at Sumber Gentong. Through engaging and informative visualizations, it is anticipated that infographics can increase Sumber Gentong's brand awareness, attract more visitors, and encourage active participation in environmental conservation.

Application of The Naïve Bayes Algorithm for Hate Speech Detection

2024-12-06T02:26:45+00:00

The spread of hate speech on social media using Indonesian continues to increase. Hate speech has become a problem that is detrimental to human life in society. In this research, the Naive Bayes algorithm is implemented to detect hate speech in social media comments. The dataset used in this research consists of 10,000 Indonesian language social media comments labeled as “Hate Speech” and “Non-Hate Speech”. Accuracy for data processed using TF-IDF is 85% for Indonesian language data. Based on the results, Naive Bayes is a simple but effective analytical approach in detecting hate speech.

Innovative Laser Alarm System for Enhanced Home Security and Burglary Prevention

2024-12-06T02:28:11+00:00

The purpose of this research is to design and develop a laser-based alarm system that produces sound when the laser beam is interrupted, aiming to prevent theft. The research methods include literature study, design, and device development. The results show that this laser-based security system can detect shadow movement using a light sensor and a microcontroller. Therefore, the laser alarm system can be effectively used to detect suspicious movements and provide alerts when the laser beam is disrupted. Further development of this system can be carried out to enhance its reliability and application in various security fields.

Blockchain-Based Barangay Document Management System with OCR Data Extraction

2024-12-06T02:28:28+00:00

This study introduces a Blockchain-Based Barangay Document Management System enhanced with Optical Character Recognition (OCR) to address the challenges of manual document handling in Philippine barangays. The system utilizes Blockchain to create an encrypted, tamper-proof ledger, ensuring data integrity and transparency by decentralizing document storage and preventing unauthorized alterations. AES-256 encryption and hashing algorithms protect transactions, while OCR technology digitizes physical records with 96% accuracy, reducing processing times by 50% and minimizing manual errors. The integration of Merkle Tree ensures each document’s uniqueness, and the system was evaluated against ISO 25010 standards, achieving high functionality, performance, and user satisfaction. This solution improves document security, reduces administrative workloads, and enhances service efficiency, fostering transparency and trust in local governance.

Iot-Based Iot-Based Smart Controller (Sponcer) To Optimize Freshwater Fish Production In Pagelaran, Pringsewu, Lampung

2024-12-06T02:28:46+00:00

An Internet of Things (IoT) based control system for optimal fish production in Pagelaran, Pringsewu, Lampung is a modern fish farming solution that uses IoT technology to automatically monitor and assess various fish environmental parameters. The system is equipped with various sensors that can measure critical parameters such as water level, pH, turbidity, and water temperature. This data is sent in real-time to a web-based application, allowing users to continuously monitor conditions remotely through devices connected to the internet. This helps maintain ideal fish environmental conditions for growth, reduces the risk of disease, and increases productivity. One of the striking features of this system is its automatic feed regulation capacity. With this system, feed is provided timely and accurately according to the needs of the fish, which is very important to ensure optimal growth. The purpose of developing an IoT-based system in Pagelaran, Pringsewu, Lampung is to increase productivity and fish production in the area. It is expected that with more careful monitoring and wiser feed handling, fish production can be increased in terms of both quantity and quality. In short, IoT-based system controllers not only improve operational efficiency but also reduce environmental damage. Farmers can reduce excessive resource use and lower operational costs by minimizing manual intervention and using technology for smarter pond management. It is expected that this system will become a model for more modern, efficient, and environmentally friendly fish farming practices, not only in Pagelaran, Pringsewu, Lampung but also in other areas.

Intelligent Waste Segregation System Using Convolutional Neural Networks for Deep Learning Applications

2024-12-06T02:28:59+00:00

Efficient waste management is essential for environmental sustainability and reducing landfill burdens. This study proposes an Intelligent Waste Segregation System leveraging Convolutional Neural Networks (CNNs), specifically the VGG-16 model, to automate the classification of waste into recyclable and non-recyclable categories. The purpose of this research is to enhance waste sorting accuracy and efficiency using advanced deep learning techniques. The system employs VGG-16, pre-trained on a large dataset, and fine-tuned with a waste image dataset, enabling high precision in recognizing waste types. The methodology includes dataset preprocessing, model training, and performance evaluation using metrics such as accuracy, precision, and recall. Experimental results demonstrate that the proposed system achieves a classification accuracy of 96%, surpassing existing traditional methods. The implications of this research include improving recycling processes and reducing environmental pollution through accurate waste segregation. This system has practical applications in urban waste management and recycling facilities, providing a scalable solution to global waste challenges. The findings highlight the potential of CNN-based models, particularly VGG-16, in addressing critical environmental issues. In conclusion, the proposed system offers an effective approach to automated waste segregation, paving the way for sustainable waste management practices through deep learning applications.

Visual Identity of Tlogo Land Tourism to Enhance Brand Awareness

2024-12-06T02:29:34+00:00

Tlogo Land is a tourist destination in Malang Regency that faces issues with visual identity inconsistency, including the use of different logos across various social media platforms. This study aims to design a consistent and integrated visual identity to enhance brand awareness and attract tourists. The research employs a non-participatory approach, with data collected through direct observation of Tlogo Land and interviews with the management. The process of designing the visual identity follows the Design Thinking method, consisting of five stages: Empathize, Define, Ideate, Prototype, and Test. The results show that the designed visual identity, including the logo, colors, and other graphic elements, effectively reflects the character and values of Tlogo Land as a nature-based tourist destination. The implementation of the visual identity on media such as business cards, staff uniforms, and stamps proves to be effective in increasing recognition and creating a positive image of Tlogo Land among visitors. This study concludes that developing a consistent visual identity can be an effective strategy for brand awareness of tourist destinations, while also strengthening Tlogo Land's image as a professional and attractive tourist destination

Analysis of the Level of Satisfaction of E-Learning Users at PGRI Madiun University Using the Pieces Method.

2024-12-06T02:29:46+00:00

The development of technology is a way to quickly disseminate information to users and can help solve problems faced by an institution. The level of user satisfaction with the Universitas PGRI Madiun e-learning system uses the PIECES method (Performance, Information, Economy, Control, Efficiency, and Service). This method was chosen because it is able to identify various aspects of system performance that affect user experience. This study was conducted by collecting data through questionnaires distributed to system users, namely students and lecturers using the Googleform platform. The results of the analysis showed that the Performance and Service aspects obtained the highest satisfaction scores, which indicated that the system was running stably and providing good service to users. However, the Control and Efficiency aspects require improvement, especially regarding ease of access and management of security features. These findings are expected to be input for e-learning system managers to improve the quality of service and overall user experienceThe development of technology is a way to quickly disseminate information to users and can help solve problems faced by an institution. The level of user satisfaction with the Universitas PGRI Madiun e-learning system uses the PIECES method (Performance, Information, Economy, Control, Efficiency, and Service). This method was chosen because it is able to identify various aspects of system performance that affect user experience. This study was conducted by collecting data through questionnaires distributed to system users, namely students and lecturers using the Googleform platform. The results of the analysis showed that the Performance and Service aspects obtained the highest satisfaction scores, which indicated that the system was running stably and providing good service to users. However, the Control and Efficiency aspects require improvement, especially regarding ease of access and management of security features. These findings are expected to be input for e-learning system managers to improve the quality of service and overall user experience.

Keywords

E-Learning, User Satisfaction, PGRI Madiun University, Pieces Method.

Implementation Of The Iot Device For Sit-Up Counting Based On ESP 8266

2024-12-06T02:30:00+00:00

Sit ups are a type of strength exercise that functions to strengthen muscles. Sit up movements are usually calculated manually, but as technology develops, it is necessary to innovate to build a digital technology-based sit up movement counting tool. The goal is to provide a sit up instrument that is able to accurately calculate the number of sit ups that have been done. The tool is made based on digital technology using the internet of things (IoT). In making this tool, the author uses 2 LDR sensor modules and 2 KY008 laser sensors installed to detect the shoulder. If one of the light sensors in the form of an LDR module is not disconnected from the light displayed by the laser sensor, then the series of sit up counting tools with this application will not calculate the sit up acquisition. The sit up counter tool will calculate if the sit up position is perfect and cut off the laser light, it will send the results of the sit up to the MySQL database which will later be displayed in the web server. This tool is easy to use and portable or easy to move. The way this tool works is quite easy, the user only needs to choose the type of exercise needed, then the tool will calculate the movements done and the user just needs to lie on the side of the tool and prepare to do the display according to the activity to be done. Then the tool will calculate automatically and will enter the website data.

Drip Irrigation Technology for Watermelon Crops with IoT-Based Solar Panels for Efficient Use of Energy Resources

2024-12-06T02:30:59+00:00

Water scarcity and energy inefficiency are major challenges in modern agriculture, particularly for water-intensive crops like watermelon. This study aims to develop a sustainable solution by integrating drip irrigation technology with IoT-based solar panels to optimize water and energy use. The purpose of this research is to design and test a system that uses renewable solar energy and IoT sensors to monitor soil moisture and control irrigation automatically, providing an efficient and environmentally friendly solution for watermelon farming. The methodology involves the development of a prototype system powered by solar panels and equipped with IoT sensors for real-time data collection and system management. The findings demonstrate that the solar-powered IoT drip irrigation system significantly reduces water consumption and energy costs compared to conventional irrigation methods, ensuring efficient water use while operating off-grid. The practical implications of this study suggest that this integrated system can be scaled for large-scale farming operations, improving crop yields and contributing to sustainable agricultural practices. The results highlight the potential of combining renewable energy, IoT, and modern irrigation techniques as a viable solution to address global challenges of water conservation, energy efficiency, and sustainable farming.

Jelajah Sultra: Inovation Of UI/UX Design for Smart Tourism App with AI-Based Travel Assistant to Support SDG 8

2024-12-06T02:31:13+00:00

The Jelajah Sultra application is a conceptual digital innovation designed to promote sustainable tourism in Southeast Sulawesi by incorporating an AI-powered smart travel assistant and optimal UI/UX design principles. This initiative addresses the growing demand for user-friendly and efficient digital platforms in the tourism sector, particularly in response to increasing tourist numbers in Indonesia. The primary aim of this study is to develop a UI/UX design concept for a tourism application that supports sustainable tourism practices, enhances local economic growth, and empowers communities by improving market accessibility. Utilizing the Design Thinking method, this research involves the stages of empathizing, defining user needs, ideating, prototyping, and testing to create a user-centric design for Jelajah Sultra. The design incorporates features such as AI-powered chatbot assistance, interactive maps, and streamlined navigation to ensure a superior user experience. The usability testing resulted in a high usability score of 94.0, indicating the potential of Jelajah Sultra to facilitate seamless information delivery and effective interaction for users. This research contributes to SDG 8 by fostering local economic growth and supporting responsible tourism practices.

AI-Based Phishing Attack Detection And Prevention Using Natural Language Processing (NLP)

2024-12-06T02:31:32+00:00

Phishing attacks remain one of the most prevalent and damaging cybersecurity threats, targeting users across various communication channels such as email, social media, and SMS. Traditional phishing detection systems are often limited to email and rely on static rule-based filtering or keyword matching, making them ineffective against evolving phishing tactics. This project proposes an innovative solution that utilizes Artificial Intelligence (AI) and Natural Language Processing (NLP) to create a real-time phishing attack detection and prevention system. By analyzing the contextual language of messages across multiple platforms, the system can detect and block phishing attempts with high accuracy. The system extracts important linguistic features such as urgency, emotional tone, and anomalous patterns within text, and applies machine learning algorithms—such as Random Forest, Support Vector Machines (SVM), and deep learning models like Long Short-Term Memory Networks (LSTM)—for classification. Additionally, a feedback loop is integrated to allow the system to adapt and improve over time through active learning, ensuring the detection system evolves alongside emerging phishing techniques. This AI-based solution extends beyond traditional email phishing detection by incorporating multiple channels, including SMS and social media platforms, making it a versatile tool for individuals and businesses. The system offers automated prevention actions, such as flagging suspicious messages and alerting users, thus providing a robust defense against phishing attacks in real-time. The project's implementation aims to fill the market gap in comprehensive, multi-channel phishing detection and contribute to the growing demand for intelligent and adaptive cybersecurity solutions.

The Effectiveness of Snort in DDoS Attack Scenarios

2024-12-06T02:32:09+00:00

Secure communication in the digital era has become important, while on the other side, the attackers are consistently moving into more sophisticated ways to acquisition their target. DDoS was one of the common techniques used with the aim to overwhelm and make their target fail to function. To detect and limit this threat, many organizations have begun to employ various solutions. However, it was discovered that several solutions are ineffective while others require high cost for the implementation, and this has become a challenge for medium to low-sized organizations to meet their business strategy. For that, in this study we aim to introduce Snort as an open-source solution for the network detection and prevention system to determine how it undertakes and performs analysis especially in terms of accuracy and speed in relation to DDoS attacks. This study will involve a few steps: first, to establish the simulation environment; secondly, to perform the simulation with a DDoS attack to allow Snort to capture the traffic and respond according to the pre-established rules; and finally, to measure and evaluate the result. Snort as an open-source product, in nature allows the public to contribute, and that becomes the advantage compared with other commercial products especially in detecting anomalies. This will help the administrators to react more quickly by having an accurate information with an earlier warning system. Additionally, Snort is affordable, making it good choice for the organization.

The Quantum-Assisted Fingerprint Biometrics: a Novel Approach To Fast And Accurate Feature Extraction And Synthetic Generation

2024-12-06T02:32:20+00:00

This research explores the integration of artificial intelligence (AI) and quantum computing to enhance fingerprint biometrics through improved feature extraction and synthetic fingerprint generation. Traditional fingerprint biometrics face challenges related to processing speed and scalability, particularly when managing large datasets or creating synthetic fingerprints for testing and training purposes. We propose a dual approach: using convolutional neural networks (CNNs) to extract distinctive fingerprint features—such as loops, whorls, and minutiae points—and employing generative adversarial networks (GANs) for the synthesis of high-quality fingerprint images that preserve realistic patterns and variations. To address computational limitations in processing these data-intensive tasks, we explore the use of quantum computing algorithms. Specifically, we implement a hybrid quantum-classical model, using quantum support vector machines (QSVM) for feature classification and quantum-enhanced GANs (QGAN) to speed up synthetic fingerprint generation. Preliminary results indicate that quantum-assisted models demonstrate promising efficiency gains in both feature extraction and image synthesis, potentially enabling faster processing and improved scalability compared to classical models alone.This study contributes to biometric security by providing a framework for faster, more accurate fingerprint biometrics using cutting-edge AI and quantum methodologies. The findings hold potential applications in security systems, law enforcement, and digital identity management, where real-time analysis and synthetic data generation can strengthen verification and identification processes. Future work includes optimizing quantum components for larger datasets and further refining AI models to improve the realism of generated fingerprint images.

Duck Egg Hatching Incubator Technology Based On Internet of Things

2024-12-06T03:16:03+00:00

The egg incubator was originally a simple tool using a lamp to produce heat without other supporting tools, So the incubation process has a big influence on traditional egg hatching through the mother duck incubating the eggs. However, temperature control at the time Incubation of eggs by the parent certainly has certain limitations due to the parent which is difficult to control in order to incubate it which ultimately causes the egg to suffer hatch failure. In the process of hatching duck eggs, you must pay attention to temperature and humidity and egg rotation which must be maintained regularly, is necessary continuous supervision and monitoring so that the eggs can hatch well. By utilizing applicable Internet of Things technology in the field of animal husbandry, it is a solution to monitor the condition of hatching duck eggs automatic and real-time, so it can help farmers in monitoring conditions such as temperature and humidity as well as the condition of the eggs in the hatching room. So A research was conducted entitled "Duck Egg Hatching Incubator Technology Internet of Things” was carried out with the aim of making things easier for breeders monitor temperature and humidity and monitor conditions inside real time drip space.

Implementation of IoT Technology for Optimization Shrimp Feeding in SMKN2 Kalianda Shrimp Ponds

2024-12-06T03:17:02+00:00

Shrimp farming in Indonesia, particularly at SMKN 2 Kalianda, faces inefficiencies in manual feeding methods, leading to wasted feed and suboptimal shrimp growth. This research proposes an IoT-based automatic shrimp feeding system designed to address these issues by automating the feeding process and integrating real-time water temperature monitoring. The system utilizes the NodeMCU ESP8266 microcontroller, servo motors for feed distribution, and a DS18B20 sensor for monitoring water temperature. Data is communicated via HTTP to a web application, providing real-time monitoring capabilities. The system was successfully tested at SMKN 2 Kalianda's shrimp pond, demonstrating efficient feed distribution, with distances of up to 1.5 meters. It also ensured timely and accurate feeding, reduced labor costs, and minimized feed wastage. Additionally, the system can be further enhanced by integrating data analytics and machine learning to optimize feeding schedules and water quality management. These advancements promise to improve shrimp farming efficiency, reduce human error, and contribute to sustainable aquaculture practices.

Application of FFT and KNN Methods for the Process of Identifying Sound Signals

2024-12-06T03:19:45+00:00

Everyone has a different kind of voice. Sound is a unique thing and has a certain range of frequencies and intensity of sound that can and cannot be heard by humans. we can detect important characteristics of the sound. The Fast Fourier Transform (FFT) algorithm is an algorithm for calculating Discrete Fourier Transform (DFT). Process of Identifying Sound Signals beginning with the sound data was preprocessed, feature extraction using FFT, classification using KNN and finding the nearest distance using the Euclidean distance method, an accuracy result of 79% of the tested data was obtained.

Empowering Sustainable Startups in Kenya Through Blockchain Technology

2024-12-06T03:20:00+00:00

This study investigates the potential applications of blockchain technology to offer a solid basis for supporting long-term, sustainable Kenyan entrepreneurs. The study investigates how blockchain technology's decentralized, transparent, and secure features might increase investor confidence, increase stakeholder engagement, and speed up funding processes for sustainable projects. The key findings indicate that blockchain can significantly improve transparency, reduce inefficiencies in the fundraising process, and attract a diverse range of investors to support companies. However, barriers including ambiguous laws, complex technology, and poor awareness make widespread adoption challenging. To solve problems, the paper emphasizes the need for an all-encompassing framework that includes capacity building, policy alignment, and clever public-private partnerships. By prioritizing these initiatives, stakeholders may unlock blockchain's transformative potential to assist Kenya's green development goals, foster innovation, and accelerate sustainable startup growth.

Risk Analysis of Computer Network Security Focusing on Phishing Attacks in Fintech Platform

2024-12-06T03:20:17+00:00

The advancement of Science and Technology, particularly in Information Technology such as the internet, has significantly facilitated individuals in achieving their life goals quickly, either through legal or illegal means. One prominent threat is phishing, which employs social engineering techniques to deceive users by impersonating authoritative entities. Phishing targets various industries, with the fintech platform sector being one of the primary targets. The main factors contributing to phishing in fintech platform services include users' lack of knowledge, psychological factors, and insufficient privacy protection on social networks. Therefore, computer network security is a critical measure to prevent phishing attacks on fintech platform services. This research employs a qualitative method with a descriptive approach.

An Analysis of Family Structures and Daily Life Among the Sea Tribe in Riau: A Cultural Perspective

2024-12-06T03:20:28+00:00

This study explores the family structures and daily life of the Sea Tribe in Riau, focusing on their unique cultural practices, social dynamics, and adaptation to their maritime environment. The research employs a qualitative approach, utilizing ethnographic methods such as in-depth interviews, participant observation, and document analysis. The findings reveal that the Sea Tribe’s family structures are shaped by their communal living patterns, with strong kinship ties playing a central role in social organization and decision-making. Daily life revolves around traditional maritime activities, including fishing, boat building, and trading, which are integral to their economic and cultural identity. Furthermore, the study highlights the intergenerational transmission of knowledge and the role of rituals in strengthening familial and community bonds. Challenges such as modernization, environmental changes, and shifting socio-political landscapes are also examined, shedding light on how these factors impact their way of life. This research contributes to the understanding of indigenous maritime communities and emphasizes the importance of preserving the cultural heritage of the Sea Tribe in Riau amidst rapid global change

Information Systems Audit Using the 2019 COBIT Framework with Domain DSS01 and BAI04 on the Grand Landak Hotel Reservation System

2024-12-06T03:20:45+00:00

Grand Landak Hotel is one of the hotels that has implemented information systems in their operations, one of which is the room booking or reservation section. At this time the reservation system is used by the front office of the hotel by the receptionist, which is part of the hotel's front office. Therefore the system must be able to manage, store and maintain data security and the system can operate when there is an increase in reservations. So this research aims to evaluate the operational efficiency and availability of the reservation system in the Front Office Department of the Grand Landak Hotel using the COBIT 2019 framework. This research focuses on two main domains, namely DSS01 (Managed Operations) and BAI04 (Managed Availability and Capacity). While the data was obtained through interviews with the general manager and front office staff of the hotel. The results showed that the service process has been running well with a result of 49.4 percent and for capacity of 54.8 percent but technological innovation requires more attention, especially in actively involving employees in the process of implementing new systems.

Exploration of Singosari Museum

2024-12-06T03:20:54+00:00

This study, conducted by the Makar Team, students of Visual Communication Design (DKV) at STIKI Malang, aimed to develop an Augmented Reality (AR) application to assist visitors in exploring the historical context of the Singosari Museum in Malang. Utilizing the design thinking methodology, the research comprised five stages: empathize, define, ideate, prototype, and test. Direct observation was conducted during the empathize stage to understand visitor needs. Problems were formulated in the define stage, followed by ideation (ideate) and prototype development (prototype). The prototype was tested (test) to gather feedback. The results showed that the AR application significantly enhanced historical understanding and provided innovative interaction with historical information.

Development of Cloud Messaging-Based Mobile Learning Application to Improve Interaction in the Learning Process at STIKI (ebelajar case study)

2024-12-06T03:23:15+00:00

In the digital era, the use of technology in the learning process is crucial to improve the effectiveness and efficiency of education. This study aims to develop a cloud messaging-based mobile learning application to improve interaction between students and lecturers at STIKI. This application is developed using the Dart programming language with the Flutter framework and utilizes cloud messaging technology to enable fast and effective communication in the form of announcements, discussions, and task notifications.

The research method used is the research and development (R&D) method with the Agile software development model. The development stages include needs analysis, design, implementation, and application testing and evaluation. The results of the study show that this mobile learning application can increase the frequency and quality of interaction in the learning process. This increase is measured through user satisfaction surveys and analysis of application usage data.

With this application, it is expected to provide a positive contribution in increasing student involvement in the teaching and learning process, as well as making it easier for lecturers to deliver materials and information related to lectures. This study also presents recommendations for further development so that the application can continue to be adjusted to user needs and technological developments.

The Heartcare: Predictive Analytics for Early Detection and Prevention

2024-12-06T03:23:35+00:00

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, often due to late detection and prevention. Heartcare aims to leverage predictive analytics to facilitate early detection and prevention of heart diseases. By integrating machine learning algorithms such as Decision Trees, Random Forests, and Logistic Regression, Heartcare provides healthcare professionals with a powerful tool for patient health monitoring. This study focuses on developing a predictive model to assess heart disease risk using patient-specific data, such as age, sex, BMI, and lifestyle factors. The outcomes will enable healthcare professionals to make informed decisions, potentially saving lives and reducing healthcare costs.

Data Protection Strategy in Management Information Systems: Risk Analysis and Implementation

2024-12-05T03:35:11+00:00

Management information system (MIS) data protection is critical and cannot be ignored, especially considering the increasing number of cyber threats and data leaks that can harm organizations. This journal discusses various data protection methods that can be used in MIS, with special emphasis on risk analysis and good implementation. In this research, we conducted a comprehensive analysis of the various threats faced by management information systems, including threats from cyberattacks, human error, and technological vulnerabilities. We also identify the components that contribute to those risks and how they impact data integrity and confidentiality. We do this using a case study approach and qualitative data collection. Additionally, the journal offers various solutions for mitigation, such as implementing strict access controls, data encryption, and security training for users. We also emphasize how important it is to have a clear information security policy and disaster recovery procedures to ensure continued operations. This research aims to assist organizations in strengthening their management information systems by providing practical, evidence-based recommendations for implementing data protection strategies. It is hoped that the results will serve as a guide for stakeholders in designing and implementing effective data protection strategies, which will increase trust and security in data management in the digital era.

Design and Development Website English Learning for Elementary School to Increase Engagement

2024-12-05T03:35:11+00:00

The development of technology has a great influence on the development of Learning media is one of the factors that plays an important role during the learning process especially for elementary school. Elementary school currently use gadget media as a daily guide but are not used as a medium for learning English. This causes a decrease in value and a lack of interest in learning English through book media due to the lack of enjoyable interaction. The purpose of this study is to find out how to design and build English learning media and increase engagement for elementary school in grade 4 based on a website that can increase interest in learning and help the teaching and learning process to be more efficient. This learning media is designed with several features such as materials, sample questions, learning videos, and practice questions which are expected to motivate students to continue to understand the learning materials obtained. The steps used in building this website are through planning needs then system design then system development and the last is implementation. This study uses Cognitive Engagement type engagement which means involvement in cognitive. With the system on the website, it is expected to help 4th grade elementary school students in English learning activities.

Design and Construction of a Website-Based Garment Production Information System

2024-12-05T03:35:11+00:00

Garment is a specialist production in producing various types of clothing such as ready-to-wear clothing, sportswear, clothing accessories, etc. by utilizing information technology. As time goes by, there are now more and more companies operating in the garment sector and as technology advances, garment companies are now starting to intensively use a system in their production flow. The Garment Industry is a company that operates in the garment manufacturing sector. However, in its operation there are still many problems such as slow operation, less effective data management, manual reporting, missing range data and many more. Administrative activities in garments such as processing order data, order allocation and preparing reports still do not meet operational achievements. Because of this, an information system is needed which is expected to help garment companies solve the problems they face. The role of this information system is the right solution to deal with the problems faced by the company so that everything runs effectively and efficiently. The method that the author used in writing this final assignment was by observing the company premises, conducting interviews with people related to the company, and studying literature from several journals and guidelines for writing this final assignment. Thus, this system is expected to increase the productivity and service quality of garment companies, as well as make a positive contribution to their business growth. The system proposed by the author is web-based, built with a sequence of steps, namely problem identification, needs analysis, coding, design and testing.

Artificial Intelligence Capability in Education to Enhance Human Resources Quality from Economic Perspective

2024-12-05T03:35:11+00:00

Application of artificial intelligence (AI) in education contributes significantly to improving the quality of human resources (HR). This study aims to analyze the relationship between AI technology and HR quality from an economic perspective. Using a qualitative approach based on literature studies, this study explores the contribution of AI in supporting interactive learning, operational efficiency, and improving critical skills. The results show that AI accelerates the learning process, personalizes learning experiences, and prepares students to face the challenges of the digital job market. At the company level, AI implementation improves productivity, efficiency, and data-driven decision-making. This study recommends the development of a curriculum that supports technological literacy and collaboration between educational institutions, the government, and the private sector to ensure HR readiness to face the demands of the digital era. Practical implications include sustainable training strategies and AI integration to support adaptive digital transformation. This study emphasizes the importance of investing in education and training to optimize technological potential, improve business performance, and support sustainable economic growth

Web-Based Student Internship Monitoring Information System (Case Study: SMK Ma'arif NU 2 Boyolali)

2024-12-05T03:35:11+00:00

Internships are an essential component of vocational school programs, including at SMK Ma'arif NU 2 Boyolali, where students engage in six-month fieldwork during the 12th grade. The current monitoring process relies on WhatsApp and manual documentation, including paper-based journals for attendance, daily activity logs, and final report submissions. This manual approach is inefficient and complicates data management for supervisors. This research aims to develop a web-based information system to streamline the monitoring and management of student internships. The study employs observation, interviews, and literature review for data collection, alongside the SDLC method for system development through planning, analysis, design, implementation, and maintenance.

The system provides three user roles: admins manage data and reports; students log attendance, activities, and submit reports; and supervisors verify submissions. Black box testing confirmed functional success, while user testing yielded an average satisfaction score of 87.53%, demonstrating the system's effectiveness and usability.

AUTOMATIC MOBILE OIL DISPENSING WITH MONITORING FOR TRAIN COMPRESSOR

2024-12-05T03:35:12+00:00

Train compressors require the appropriate oil level to function effectively. Kettles and pitchers are useless, inexact, and dangerous for hand oil replenishment. To solve these problems, this project developed an automated mobile oil delivery system that monitored the oil. The technology avoids spills, dispenses oil accurately, and monitors oil levels and battery efficiency in real-time. All of the above requires a very thoughtful design and development of a self-priming pump, ultrasonic sensors, an electronic battery sensor, an ultrasonic flow meter, and an Arduino Giga display. It was developed and tested locally. The system accurately administered oil and monitored oil levels and the condition of the battery; excellent comments were received from the maintenance experts. This implies that automated oil refilling for railway depots' train compressor oil may enhance efficiency and safety. The potential to work with various train compressors, as well as economic and environmental advantages, deserve further research.

Implementation of COBIT 2019 with Domain DSS01, DSS03, and MEA01 for Audit of Customer Water Usage Recording Information System at HIPPAM Mandiri Arjowinangun

2024-12-05T03:35:12+00:00

Currently, HMA faces challenges in optimizing the recording system, because the meter recording process is still done manually. This manual process hampers operational efficiency and data accuracy which impacts the quality of service to customers. Therefore, it is necessary to evaluate the existing information system to measure whether the application of information technology is in accordance with the goals and expectations of the organization. This study aims to analyze the application of information technology in HMA using the COBIT 2019 framework, specifically in the domains DSS01 (Manage Operations), DSS03 (Manage Problems), and MEA01 (Monitor, Evaluate, and Assess Performance). Through capability analysis in these three domains, this study identifies gaps in the existing system and provides recommendations for improvements to improve the efficiency and accuracy of the customer water usage recording system. The results of the study indicate that HMA's capability level is still below the desired target, so it is important to make improvements by implementing more integrated digital solutions and improving continuous monitoring and evaluation of system performance.

Heritage in Augmented Reality

2024-12-17T06:21:06+00:00

This research explores the application of augmented reality (AR) technology to promote the historical heritage of colonial architecture in East Java, with a focus on Malang. By creating immersive 3D visualizations of iconic buildings, the project aims to document and preserve cultural heritage, raise public awareness, and support sustainable urban planning. The project aligns with Sustainable Development Goals (SDGs) 4 and 11, fostering quality education and sustainable cities.