Klasifikasi Mahasiswa Berprestasi Menggunakan Fuzzy C-Means Dan Naive Bayes

Abstract

Success in the world of education is often associated with successful academic achievements. Therefore, processing information is very important to determine the selection of students who excel. However, study programs and student services often face difficulties in recognizing students who have achievements. In this research, outstanding students from the Faculty of Engineering, Makassar State University were determined using the Naive Bayes classification method combined with the Fuzzy C-Means (FCM) method to identify data patterns before classification. The criteria measured are GPA, achievements achieved, organizations attended, and the number of Semester Credit Units (SKS) that have been programmed. By using the Confusion Matrix, the evaluation results show an accuracy level of 98%, recall of 97%, precision of 100%, and F1-Score of 99%.