Data Mining di Bidang Pendidikan untuk Analisa Prediksi Kinerja Mahasiswa dengan Komparasi 2 Model Klasifikasi pada STMIK Jabar - Galih, Galih (Jurnal Teknologi Sistem Informasi dan Aplikasi, 2019)
Until now many universities that helped the government in accelerating improving the quality of education so the creation of a competitive environment.. The abundance of data contained in the College can be put to good use in accordance with the needs and processed into useful information so as to find out the relationship between the attributes of the data in it can be on the analysis and expected output in the form of student performance has related to the period of study i.e. can be categorized into appropriate or too late in the anticipated period of study. Data mining can be used for educational institutions or institutions and often called as Educational Data Mining (EDM). In the study carried out using two models of Naive Bayes Classifier i.e. algorithms and C 4.5. as for the value of the best accuracy in the Naive Bayes Classifier algorithm model (NBC) was 86.83% with ratio 80% training data, whereas in model algorithm C 4.5 was 88.10% with 90% training data ratio. Application of EDM and expected to be maximized and developed so that it can contribute to and progress in the world of education especially in data mining.