Application of Naïve Bayes Method for Student Performance Classification

Prayoga, Riza Akhsani Setyo
Basatha, Rizky
Akbar, Muhammad Sonhaji
Elfaiz, Ersha Aisyah
Putra, Cendra Devayana

Sistemasi: Jurnal Sistem Informasi
Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi

In every school, students exhibit varying levels of performance, influenced by several factors such as parental support and involvement, participation in extracurricular activities, motivation levels, internet access for learning, teacher quality, peer influence, and learning difficulties. This study aims to classify student performance to identify those who may need additional support for improvement. The classification method employed in this research is the Naïve Bayes algorithm. The results indicate that the trained model successfully classified 25 out of 30 tested data points. The evaluation metrics achieved include a precision of 100%, recall of 80%, specificity of 100%, accuracy of 83%, and an F1-score of 89%.