Sistem Deteksi Intrusi Cerdas: Studi Perbandingan Algoritma Pembelajaran Mesin Untuk Keamanan Siber

Authors

  • Isma Elan Maulani Universitas Muhammadiyah Cirebon, Indonesia
  • Dwi Rayhan Sunandar Putra Universitas Muhammadiyah Cirebon, Indonesia
  • Komarudin Komarudin Universitas Catur Insan Cendekia, Indonesia

DOI:

https://doi.org/10.59188/jurnalsostech.v3i11.987

Keywords:

Keamanan Siber, Algoritma Pembelajaran Mesin, Perbandingan Kinerja, Akurasi Deteksi Serangan, Tingkat Kebocoran, Respons Sistem

Abstract

Dalam era yang terus berkembang di bidang teknologi informasi, keamanan siber menjadi aspek kritis yang memerlukan perhatian mendalam. Studi ini membahas implementasi Sistem Deteksi Intrusi (IDS) yang cerdas dengan fokus pada perbandingan kinerja berbagai algoritma pembelajaran mesin yang diterapkan dalam lingkungan keamanan siber. Tujuan penelitian adalah untuk mengevaluasi akurasi deteksi serangan, tingkat kebocoran, dan respons sistem pada berbagai algoritma. Metode penelitian kuantitatif digunakan dengan merancang eksperimen pada sejumlah organisasi yang mewakili berbagai sektor industri. Hasil penelitian memberikan wawasan mendalam tentang keefektifan relatif algoritma pembelajaran mesin dalam meningkatkan keamanan siber, membimbing pemilihan dan implementasi IDS yang optimal.

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Published

2023-11-30

How to Cite

Elan Maulani, I., Rayhan Sunandar Putra, D. ., & Komarudin, K. (2023). Sistem Deteksi Intrusi Cerdas: Studi Perbandingan Algoritma Pembelajaran Mesin Untuk Keamanan Siber. Jurnal Sosial Teknologi, 3(11), 918–923. https://doi.org/10.59188/jurnalsostech.v3i11.987

Issue

Vol. 3 No. 11 (2023): Jurnal Sosial dan Teknologi

Section

Articles

License

Copyright (c) 2023 Isma Elan Maulani, Dwi Rayhan Sunandar Putra, Komarudin Komarudin

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