Identifying of Student Succes Based on Grades of State Madrasah Aliyah Students in Bandung City Using Machine Learning

This research aims to identify the values of madrasa students in Bandung City using machine learning techniques. The application of technology in the education sector, primarily through machine learning, can provide significant benefits in analyzing complex and large amounts of academic data. In this study, several machine learning algorithms are applied to analysis student grade data from various subjects and data that influence student success in getting good grades. The analysis results show that the Naïve Bayes algorithm is the most effective in predicting and classifying based on student grades and other supporting data, with an accuracy of 98.5%. Compared with other algorithms used in this research, the results were Random Forest 98.4%, Decision Tree 95.3% and Logistic Regression 71.9%. These findings indicate that using machine learning in the academic assessment process in madrasas increases efficiency and provides deeper insights for better decision-making in the field of education.