Naïve Bayes Algorithm Analysis For Student Graduation Timeliness Prediction - A. Nurul Anwar; Dani Dani; Ade Napila (Komunitas Dosen Indonesia, 2025)
This study developed a student graduation prediction system using the Naïve Bayes algorithm, using PS1-PS4 scores, PK, and SKS as indicators of academic progress. This model achieved 88.33% accuracy and an ROC value of 0.900, indicating superior predictive ability. These results outperform other common models such as logistic regression and the C4.5 decision tree, which have approximately 85% accuracy in predicting student graduation. These results also outperform previous research in the same field, which had ROC values of approximately 0.85.Graduation predictions were categorized as