Analisis Ancaman Serangan Siber pada Sistem Jaringan Menggunakan Naive Bayes Classifier Berbasis Machine Learning

Arya Admaja

Journal Of Informatics And Busisnes
Vol. 3 No. 3 (2025): Oktober - Desember

The research examines cyber attack threats on network systems using a machine learning approach based on the Naive Bayes Classifier to detect such threats. The NSL-KDD dataset was used as the data source, with preprocessing and model training conducted in the Google Colab environment using the Python programming language. The model testing results indicate that this approach is effective in classifying network data into normal and attack categories with a high level of accuracy. This study contributes to enhancing network system security through faster and more accurate threat detection.