Design and Development of a Water Quality Recommendation System Prototype for Nila Aquaculture
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Abstract
In fish farming, specific processes are required for fish intended for food or ornamental purposes. In addition to food and weather, water quality must also be considered. Water quality parameters include ammonia content, water temperature, pH, turbidity, and Total Dissolved Solids (TDS). Poor water quality can result in the presence of toxic compounds, leftover feed, organic materials, and substances that cause diseases in fish. Conversely, good water quality can reduce water turbidity, allowing sufficient sunlight penetration and potentially increasing fish productivity. This study discusses a water quality detection device using five sensors: a temperature sensor, pH sensor, ammonia sensor, TDS sensor, and turbidity sensor, all connected to an Arduino Nano ATmega-328 to read the sensor data. Testing was conducted under five different water conditions: tilapia pond water, clean water, tilapia pond water mixed with clean water, catfish pond water, and tilapia pond water mixed with catfish pond water. The standard deviation for temperature, pH, and ammonia for all water conditions was less than 0.1. The standard deviation for TDS in catfish pond water and tilapia pond water mixed with catfish pond water was less than 1.0, and the turbidity values were below 7.
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[2] F. D. Wulansari and Ardiansyah, “Pengaruh Detergen Terhadap Mortalitas Benih Ikan Patin Sebagai Bahan Pembelajaran Kimia Lingkungan,” Edu Sains: Jurnal Pendidikan Sains dan Matematika, vol. 1, no. 2, 1013.
[3] B. Bahrin, “Sistem Pakar Deteksi Kualitas Air Dengan Metode Forward Chaining Pada Laboratorium ‘Aquaryan’ Marisa,” Simtek : jurnal sistem informasi dan teknik komputer, vol. 5, no. 1, pp. 12–20, Apr. 2020, doi: 10.51876/simtek.v5i1.66.
[4] E. D. Agustiningsih, “Perancangan Perangkat Monitoring Kualitas Air Pada Kolam Budidaya Berbasis Web Localhost,” Jurnal UMRAH, 2016.
[5] E. al. Dhinakaran, “IoT-Based Environmental Control System for Fish Farms with Sensor Integration and Machine Learning Decision Support,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 11, no. 10, pp. 203–217, 2023, doi: 10.17762/ijritcc.v11i10.8482.
[6] M. M. Rashid, A. A. Nayan, M. O. Rahman, S. A. Simi, J. Saha, and M. G. Kibria, “IoT based Smart Water Quality Prediction for Biofloc Aquaculture,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, pp. 56–62, 2021, doi: 10.14569/IJACSA.2021.0120608.
[7] Maiyulis, M. Syahrizal, and P. G. Muthe, ““Sistem Pakar Mendiagnosa Penyakit Ginjal Menggunakan Metode Rule Based Reasoning,” Information System Development, 2018.
[8] F. H. Khasan, D. Syauqy, and R. Primananda, “Sistem Rekomendasi dan Pemantauan Kualitas Air Kolam Bibit Budidaya Ikan Nila menggunakan Metode Support Vector Machine (SVM),” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 8, no. 2 SE-, Feb. 2024, [Online]. Available: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/13352
[9] H. Abduh, “Diagnosa Penyakit Pada Ikan Air Tawar Dengan Metode Rule-Based Dan Case Based Reasoning,” PENA TEKNIK: Jurnal Ilmiah Ilmu-Ilmu Teknik, vol. 4, no. 1, p. 67, Aug. 2019, doi: 10.51557/pt_jiit.v4i1.216.
[10] S. Pemantauan, K. A. Berbasis, M. Octaviani, and N. Paramytha, “IoT-Based Water Quality Monitoring System for Catfish Ponds at Agrowisata Tekno 44,” vol. 9, no. 1, pp. 10–17, 2024.
[11] A. Bhawiyuga and W. Yahya, “Sistem Monitoring Kualitas Air Kolam Budidaya Menggunakan Aquaculture Water Monitoring System Using Wireless Sensor,” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 6, no. 1, pp. 99–106, 2019, doi: 10.25126/jtiik.201961292.