Alfansyah, M Dicky (2024) Perbandingan Kinerja Algoritma Klasifikasi dan Implementasi Model Terbaik pada Website Deteksi Link Phishing. Other thesis, Universitas Islam Riau.

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Abstract

The development of information technology has changed the practical way of interacting, communicating and conducting transactions online. However, this also brings security risks, such as the increase in phishing attacks. Indonesia AntiPhishing Data Exchange (IDADX) noted that in the first quarter of 2023 there were 26,675 phishing reports. This research aims to identify phishing links by building a system that applies classification algorithms using a machine learning approach to produce the best model, with GPT (Generative Pre-trained Transformer) as one of the extraction features. Based on the research results, the developed neural network model achieved the highest performance, with accuracy, precision, recall, and f1score reaching 92.11%, showing excellent ability in classifying phishing URLs.

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