COMPARISON OF DATA MINING CLASSIFICATION ALGORITHM FOR PREDICTING THE PERFORMANCE OF HIGH SCHOOL STUDENTS

Tiska Pattiasina (Pascasarjana STMIK Nusa Mandiri)
Didi Rosiyadi (Ilmu Komputer STMIK Nusa Mandiri)

Techno Nusa Mandiri : Journal of Computing and Information Technology
Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of

Data Mining is a series of processes to explore added value in the form of unknown information manually from the database. In the world of data mining education can be used to obtain information about student performance. In this study the researchers took research samples from class XI (eleven) students at SMAN 3 Ambon by classifying student performance based on thirteen attributes, namely: age, sex, school organization, extracurricular activities, pocket money, duration of study at home, duration of social media, online game duration, attendance, illness, permits, semester 1 and semester 2 grades. Using the KDD (Knowledge Discovery Database) method and classification algorithm that will be used, namely, decision tree, Naïve Bayes and K-Nearest Neighbor. And then do the test using k-fold cross validation.