Variabel Non Akademik Untuk Memprediksi Prestasi Siswa Dengan Data Mining Menggunakan Metoda Naïve Bayes - Sinaga, Arnold Ropen (FKOM UNIKU, 2023)
The aim of this research is to measure not only the accuracy rate but also the precision result and the recall of the data mining application to predict Junior High School students’ learning outcomes based on their gender, the origin of the school, parents’ education and occupation. Determination of the students’ learning outcomes are very important in the education world. it becomes important because of the difficulty in determining the factors and variables which can affect the students’ learning outcomes.The accurate process of the data mining can recognize and extract the pattern of knowledge in order to offer solutions to increase the education quality where it can help the students maximize their achievement.There are some classification models in data mining: ID3 algorithm, C4.5 and Naïve Bayes which can be used to predict the students’ achievement, specifically, in Junior High School. This research uses Naïve Bayes classification mode to predict the Saint Mary Junior High School students’ achievement in order to get a better accuracy.