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All Journal Techno.Com: Jurnal Teknologi Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JSI (Jurnal sistem Informasi) Universitas Suryadarma JURNAL KAJIAN TEKNIK MESIN Jurnal Mantik Cyber Security dan Forensik Digital (CSFD) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Jurnal Jaring SainTek Jurnal Pengabdian Masyarakat Indonesia Jurnal Manajemen Informatika Jayakarta Journal of Students‘ Research in Computer Science (JSRCS) J-Intech (Journal of Information and Technology) Jurnal Sistim Informasi dan Teknologi Jurnal Pengabdian Pelitabangsa Jurnal Manajemen Informatika dan Bisnis Digital Indonesian Journal of Education And Computer Science Journal of Computer Science Contributions (Jucosco) Journal of Informatics and Information Security IKRAM: Jurnal Ilmu Komputer Al Muslim
Joniwarta
Program Studi Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
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Journal : Jurnal Manajemen Informatika Jayakarta

 1 
ANALISIS KOMPARATIF ALGORITMA MACHINE LEARNING UNTUK MENDETEKSI MALICIOUS URL BERBASIS FITUR GANDA Alexander, Allan Desi; Warta, Joni; Lubis, Hendarman; Mahbub, Asep Ramdhani; Rasim, Rasim
Jurnal Manajamen Informatika Jayakarta Vol 5 No 3 (2025): Jurnal Manajemen Informatika Jayakarta ( JMI 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i3.2101

Abstract

Malicious URL Detection (MUD) merupakan komponen esensial dalam pertahanan siber, mengingat kerugian finansial global yang disebabkan oleh phishing, penyebaran malware, dan serangan botnet IoT. Pendekatan tradisional seperti blacklisting terbukti tidak efektif melawan URL yang baru dibuat atau polymorphic. Penelitian ini menyajikan analisis komparatif ekstensif dari tiga kelas algoritma utama: Ensemble Learning (Random Forest/RF), Kernel Methods (Support Vector Machine/SVM), dan Deep Learning (DL), dalam mengklasifikasikan URL yang berpotensi berbahaya. Data yang digunakan bersumber dari repositori publik URLhaus, yang sangat fokus pada malware download, khususnya kampanye botnet Mozi dan Mirai. Metodologi studi ini menekankan pada rekayasa fitur multi-modal, yang menggabungkan fitur leksikal, berbasis host/domain, dan fitur berbasis metadata (tag malware). Kinerja model dievaluasi menggunakan metrik yang sensitif terhadap keamanan siber, yaitu Presisi, Recall, dan F1-Score, untuk meminimalisir False Negatives. Hasil analisis memperlihatkan bahwa meskipun model DL mencapai akurasi tertinggi, Random Forest menawarkan keseimbangan optimal antara kinerja deteksi yang kuat dan efisiensi komputasi, menjadikannya ideal untuk implementasi real-time dalam sistem deteksi ancaman. Malicious URL Detection (MUD) is an essential component of cyber defense, given the global financial losses caused by phishing, malware distribution, and IoT botnet attacks. Traditional approaches such as blacklisting have proven ineffective against newly created or polymorphic URLs. This study presents an extensive comparative analysis of three main classes of algorithms: Ensemble Learning (Random Forest/RF), Kernel Methods (Support Vector Machine/SVM), and Deep Learning (DL), in classifying potentially malicious URLs. The data used is sourced from the public repository URLhaus, which focuses heavily on download malware, specifically the Mozi and Mirai botnet campaigns. The study's methodology emphasizes multi-modal feature engineering, combining lexical, host/domain-based, and metadata-based features (malware tags). Model performance is evaluated using cybersecurity-sensitive metrics, namely Precision, Recall, and F1-Score, to minimize False Negatives. The analysis results show that although the DL model achieves the highest accuracy, Random Forest offers an optimal balance between strong detection performance and computational efficiency, making it ideal for real-time implementation in threat detection systems.
Co-Authors -, Rasim ., Rasim Achmad Noe’man Agus Hidayat Alexander, Allan D Alexander, Allan D Alexander, Allan Desi Alif Septiyanto Amaliah Annisa Annisa, Amaliah Ardha Maliki Asep R. Hamdani Asep Ramdhani M Asep Ramdhani Mahbub Cecep Kusmana Dani Yusuf Dimas Abimanyu Prasetyo Dwi Budi Srisulistiowati Hadi Kurniawanto Hantoro, Kusdarnowo Henny Leidiyana Irsya Fadillah Jeremiah Marvin Kapoyos Khaerudin, Muhamad Khoirunnisaa, Nabiilah Kustanto , Prio Lubis, Hendarman Mahbub, Asep Ramdhani Maria Ulfah Mugiarso Mugiarso Muhamad Khaerudin Muhammad Khaerudin Nurfiyah Nurhasan Nugroho Priatna , Wowon RAFIKA SARI Rafika Sari Ramadhan, Idrus Rasim Rasim Rasim, Rasim Ratna Salkiawati Rinaldi Tunnisia Ritzkal, Ritzkal Shifa Anamika Sinaga, Zulkani Sri Rejeki Sulistiyo, Dwi Tyastuti Sri Lestari Widodo, Hernowo