Deteksi Website Phishing Menggunakan Teknik Machine Learning
DOI:
https://doi.org/10.24002/jiaj.v6i1.11538Keywords:
Machine Learning, Supervised Learning, PhishingAbstract
Phishing merupakan teknik penipuan yang memanfaatkan penyamaran sebagai entitas tepercaya untuk mencuri data sensitif. Metode deteksi berbasis machine learning, seperti XGBoost, Random Forest, dan Decision Tree, efektif dalam mengenali pola website phishing. Hasil penelitian menunjukkan bahwa XGBoost dengan hyperparameter tuning memberikan akurasi tertinggi, yaitu 96%. Model ini kemudian diimplementasikan dalam web service menggunakan Flask atau FastAPI, sehingga pengguna dapat memeriksa URL secara real-time. Sistem juga dilengkapi mekanisme ekstraksi fitur, termasuk analisis URL, domain age, dan konten halaman, serta pelabelan otomatis untuk memudahkan pelatihan ulang model. Selain itu, integrasi dengan bot Telegram memperluas aksesibilitas, karena pengguna dapat melakukan deteksi phishing kapan saja melalui pesan instan tanpa batasan lokasi atau perangkat.
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