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Komparasi Kinerja CPU dan Memori dalam Proses Klasifikasi Malware Menggunakan Algoritma Random Forest pada Sistem Operasi Kali Linux 64-bit dan Ubuntu 64-bit
Abstract
Machine learning telah menjadi aspek krusial dalam keamanan siber, khususnya dalam deteksi intrusi dan klasifikasi malware. Namun, penerapan teknik ini memerlukan alokasi sumber daya komputasi yang signifikan. Dalam konteks ini, sistem operasi memiliki peran krusial berkaitan dengan kemampuannya dalam mengelola sumber daya komputasi. Penelitian ini bertujuan untuk mengevaluasi dan membandingkan performa CPU dan memori dari dua sistem operasi populer, yaitu Kali Linux dan Ubuntu, dalam konteks komputasi klasifikasi malware menggunakan teknik dan algoritma machine learning untuk mengetahui sistem operasi dengan performa yang lebih baik. Keduanya diuji menggunakan model machine learning dan variasi dataset yang sama untuk klasifikasi malware menggunakan algoritma Random Forest. Analisis dilakukan dengan membandingkan persentase konsumsi CPU dan memori antar kedua sistem operasi. Berdasarkan hasil pengujian, ditemukan bahwa sistem operasi Kali Linux memiliki rata-rata penggunaan CPU yang lebih rendah sekitar 19,64%, dan penggunaan memori yang lebih rendah sekitar 0,06% dibandingkan dengan sistem operasi Ubuntu. Dengan demikian, dapat disimpulkan bahwa sistem operasi Kali Linux memiliki performa yang lebih baik daripada sistem operasi Ubuntu dalam hal konsumsi CPU dan memori dalam komputasi klasifikasi malware menggunakan teknik dan algoritma machine learning.
Keywords
kali linux; machine learning; malware; random forest; sistem operasi; ubuntu
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DOI: https://doi.org/10.24114/cess.v9i1.53994
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CESS (Journal of Computer Engineering, System and Science)
CESS (Journal of Computer Engineering, System and Science) is licensed under a Creative Commons Attribution 4.0 International License