Prediction of Cyber Attack Categories with Random Forest Classification Algorithm Using Rapidminer

##plugins.themes.bootstrap3.article.main##

Saddam Rabbani Diana Diana

Abstract

Cyber attacks are a serious threat to organizations or institutions that use computer networks in their operations, one of which is Communication and Informatics Department of Palembang. Therefore, this study aims to implement the Random Forest classification algorithm on the Rapidminer platform to predict cyber attack categories at the Communication and Informatics Department of Palembang. The data used in this study is cyber attack data from firewall devices for a certain period. The data is processed using Rapidminer with the Random Forest algorithm to predict cyber attack categories. The results of this research provide a high accuracy value, thereby enabling the responsible team to take preventive action or response detrimental cyber to the Communication and Informatics Department of Palembang. After evaluation using the confusion matrix and accuracy score, the results obtained were 99.84% accuracy and out of bag error 0.16.

##plugins.themes.bootstrap3.article.details##

Section
Articles
References
[1] R. Hendra Wicaksana, A. Imam Munandar, P. L. Samputra, J. Salemba, R. No, dan J. Indonesia, “Studi Kebijakan Perlindungan Data Pribadi dengan Narrative Policy Framework: Kasus Serangan Siber Selama Pandemi Covid-19 A Narrative Policy Framework Analysis of Data Privacy Policy: A Case of Cyber Attacks During the Covid-19 Pandemic,” Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi, vol. 22, no. 2, hlm. 143–158, doi: 10.33164/iptekkom.22.2.2020.143-158.
[2] I. G. Secretariat, “Cyber Crime: Covid-19 Impact,” Lyon, France, 2020.
[3] D. A. Sudarmadi dan A. J. S. Runturambi, “Strategi Badan Siber dan Sandi Negara (BSSN) Dalam Menghadapi Ancaman Siber di Indonesia,” Jurnal Kajian Stratejik Ketahanan Nasional, vol. 2, no. 2, hlm. 157–178, 2019.
[4] K. Khariwal, J. Singh, dan A. Arora, “IPDroid: Android malware detection using intents and permissions,” 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), vol. IEEE, hlm. 197–202, 2020.
[5] H. Yang, Y. Zhang, Y. Hu, dan Q. Liu, “Android malware detection method based on permission sequential pattern mining algorithm,” Journal on Communications, vol. 34, no. Z1, hlm. 107–115, 2013.
[6] M. Ignasius, J. Lamabelawa1, dan B. Sukarto2, “Analisis Data Kunjungan Wisatawan Mancanegarake Ntt Dengan Metode Prediksi Time Series.” [Daring]. Tersedia pada: https://ntt.bps.go.id
[7] A. K. Hermawan dan A. Nugroho, “Analisa Data Mining Untuk Prediksi Penyakit Ginjal Kronik Dengan Algoritma Regresi Linier,” Bulletin of Information Technology (BIT), vol. 4, no. 1, hlm. 37–48, 2023, doi: 10.47065/bit.v3i1.
[8] E. P. K. Orpa, E. F. Ripanti, dan T. Tursina, “Model Prediksi Awal Masa Studi Mahasiswa Menggunakan Algoritma Decision Tree C4. 5,” JUSTIN (Jurnal Sistem dan Teknologi Informasi), vol. 7, no. 4, hlm. 272–278, 2019.
[9] D. Luthfah, “Serangan Siber Sebagai Penggunaan Kekuatan Bersenjata dalam Perspektif Hukum Keamanan Nasional Indonesia”.
[10] T. Vimy, S. Wiranto, R. Rudiyanto, P. Widodo, dan P. Suwarno, “Ancaman Serangan Siber Pada Keamanan Nasional Indonesia,” Jurnal Kewarganegaraan, vol. 6, no. 1, hlm. 2319–2327, 2022.
[11] Y. Ilhamdi dan Y. N. Kunang, “Analisis Malware Pada Sistem Operasi Windows Menggunakan Teknik Forensik,” Bina Darma Conference on Computer Science.
[12] J. Pendidikan dan D. Konseling, “Optimasi Metode Naïve Bayes dengan Particle Swarm Optimization untuk Sistem Deteksi Serangan D-Dos Universitas Pahlawan Tuanku Tambusai,” vol. 4, 2022.
[13] N. B. Putri dan A. W. Wijayanto, “Analisis Komparasi Algoritma Klasifikasi Data Mining Dalam Klasifikasi Website Phishing,” Komputika : Jurnal Sistem Komputer, vol. 11, no. 1, hlm. 59–66, Jan 2022, doi: 10.34010/komputika.v11i1.4350.
[14] T. Imam dkk., “JJIIFKOM (Jurnal Ilmiah Informatika & Komputer) STTR Cepu Analisis Serangan dan Keamanan pada SQL Injection: Sebuah Review Sistematik.”
[15] P. R. Silalahi dkk., “Analisis Keamanan Transaksi E-Commerce Dalam Mencegah Penipuan Online,” Jurnal Manajemen, 2022.
[16]F. Rahmat, “Deteksi Malware Ransomware Pada Platform Android Menggunakan Metode Random Forest,” Universitas Sriwijaya, 2021.
[17]Y. I. Kurniawan, “Perbandingan Algoritma Naive Bayes dan C.45 dalam Klasifikasi Data Mining,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 5, no. 4, p. 455, Oct. 2018, doi: 10.25126/jtiik.201854803.