Implementation of the C4.5 Algorithm in the Website-Based Classification System for Students of Al-Ishlah Islamic Middle School - Awaliyah, Ulfa Rifky; Lilis Nur Hayati; Amaliah Faradibah (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2026)
Violations of school regulations constitute an issue that requires systematic management to support students’ character development; however, recording violations manually using books often creates difficulties in monitoring violation histories and determining appropriate sanctions. Therefore, this study aims to design and develop a web-based student violation classification system using the C4.5 algorithm. The classification process is carried out by constructing a decision tree based on entropy and information gain calculations to determine the best attribute. System performance evaluation is conducted using a confusion matrix along with accuracy, precision, recall, and F1-score metrics, with a focus on the test data. The results, based on 500 datasets with a 90:10 data split, indicate that the system is able to classify student violation levels very effectively, achieving an accuracy of 98.86% on training data and 97.96% on test data, with a precision of 0.91, recall of 1.00, and an F1-score of 0.95. With this strong performance, the system can serve as a supporting tool for recording violations and assisting decision-making in managing student violations more effectively and accurately.