Prediksi Kelulusan Mahasiswa Dengan Metode Naive Bayes dan Artificial Neural Network : Studi Kasus Fakultas Teknik UNIS Tangerang

Abstract

Sheikh -Yusuf Islamic University (UNIS) is one of the leading Islamic Universities in Tangerang City which has a vision of making Islamic Higher Education superior in the field of science and technology in Southeast Asia by 2036. With the vision of the university, the engineering faculty must produce graduates in the engineering field who are superior, strong, and able to compete at national and international levels. The problems faced by the Faculty of Engineering, UNIS Tangerang, are the low percentage of students who graduate on time compared to students who graduate late. This study aims to assist the Faculty of Engineering in predicting student graduation so that it can be anticipated earlier. This study uses the attribute number of credits, IP from semesters 1 to 4. The methods used in this study are Naïve Bayes and Artificial Neural Network. The data used in this study used 330 student records who graduated from 2012 to 2016. Accuracy results obtained after testing with a system using 20% data testing obtained an accuracy of 63.63%, precision 71.05%, recall 67.5%, and AUC 62.6%.