Implementasi Machine Learning Pada Sistem Pendeteksi URL Bermuatan Konten Negatif Menggunakan Metode Algoritma Naive Bayes Dan Support Vector Machine

Rada Rasi Saputri (Universitas Pamulang)
Agus Heri Yunial (Universitas Pamulang)

OKTAL : Jurnal Ilmu Komputer dan Sains
Vol 2 No 11 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains

Systems for filtering sites that contain negative content have been carried out by many previous researchers. However, these systems focus more on only 1 type of negative content and are mostly built for sites that are in English. The system that can filter URLs using Indonesian only focuses on negative content. This study aims to create a URL detection system that contains negative content using a Machine Learning model. The system in this study filters content on URLs that use Indonesian. This study uses 2 main models, namely Naïve Bayes, Support Vector Machine. Of all the models used, the SVM model produces the highest accuracy of 96.161%.