Komparasi Machine Learning Memprediksi Phising Dalam Keamanan Website

Aswan Supriyadi Sunge (Universitas Pelita Bangsa)

SAINTEK
Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022

The growth rate of online mobility is fast and increases sharply from desktop to mobile phone. Growth is recognized by users because of the ease of searching for information and dealing mainly in banking matters. Behind them, there is the most important issue of security on the Internet, one of them Phishing which means to resemble official or original websites when false with the intention of obtaining user information. There fore it takes a malicious web-based Phishing alias by using data set, then tested with some Machine Learning algorithms and then to compare the best and highest predictions. Computer simulation results have resulted an accuracy of up to 95.24% for the techniques used and the comparison with other models. Keywords: Predictions, Website, Phishing, Machine Learning