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All Journal KOMPUTIKA - Jurnal Sistem Komputer
Nabila Bianca Putri
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analisis Komparasi Algoritma Klasifikasi Data Mining Dalam Klasifikasi Website Phishing Nabila Bianca Putri; Arie Wahyu Wijayanto
Komputika : Jurnal Sistem Komputer Vol 11 No 1 (2022): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v11i1.4350

Abstract

Phishing is a fraudulent act carried out to try to get important information from users who use the internet by sending fake e-mails to the users. Data mining classification techniques can be used to predict phishing websites. Many data mining classification algorithms can be used, so it is necessary to make comparisons to determine the level of accuracy of each algorithm. The algorithm used is naïve Bayes, random forest, decision tree, and support vector machine. The data used are 1.353 websites data. The results of the classification process are evaluated using cross validation and confusion matrix to find out the most accurate data mining classification algorithms for predicting phishing websites.
Co-Authors Arie Wahyu Wijayanto