Classification of Student Majors with C4.5 and Naive Bayes Algorithms (Case Study: SMAN 2 Bekasi City) - Antonius Yadi Kuntoro; Hermanto Hermanto; Taufik Asra; Ferry Syukmana; Hermanto Wahono (Semesta Teknika, 2020)
School majors conducted in high school are based on interests and these have a goal to provide opportunities for learners to develop the competence of attitudes, skills competence of learners in accordance with interests, talents, and academic ability in a group of scientific subjects.In this research, the researcher uses two algorithm models that is a comparison between the C4.5 algorithm and also the Naive Bayes algorithm. In this study, the data used is the results of school entrance test data and also the data from psychological results for students who have been declared passed the entrance test school SMAN 2 Bekasi City academic year 2018/2019. By comparison of two data mining classification algorithm, can be proved with accuracy result and AUC value from each algorithm that is for Naive Bayes accuracy = 76,43% and AUC value = 0,846, while for algorithm C4.5 accuracy = 70,29% and AUC value = 0.738.