Sistem Inferensi Fuzzy untuk Memprediksi Prestasi Belajar Mahasiswa Berdasarkan Nilai Ujian Nasional, Tes Potensi Akademik, dan Motivasi Belajar

Abstract

Predictions based on student learning achievement motivation levels, interests, and student discipline in following lectures using fuzzy logic applications have been made. This study is a follow-up of research prediction student learning achievement based on the value of the test of academic potential, NEM, and motivational learning using fuzzy inference system Mamdani method. This research is a study of the development of computer software with data inputs in the form of value of the test of academic potential, national exam score, and levels of learning motivation, and generate output in the form of student achievement results prediction (GPA). The programming language used is MATLAB version 7.0. The Data is taken from the sample as many as 216 students i.e. students of Informatic Engineering of Engineering Faculty. Data retrieval method used is the question form and documentation. Question form method used to obtain data on students' learning motivation levels, while the method of documentation used to obtain the data value of the test of academic potential score, national exam score, and GPA up to semester gasal 2011/2012. Steps of system development through stages of fuzzyfication, inference, and the determination of output. The results of this study showed that the use of applications of fuzzy logic with Mamdani fuzzy inference method can be predicted students learning achievement based on the value of test of academic potential score, national exam score, and motivation levels. This system is engineered visually, so users can use it just by doing a drag on its visual images. Based on a regression analysis that was done, the three input variables have an influence on the learning achievements of students, so that the student is expected to increase the motivation of their learning to achieve learning achievements (GPA)