Prediksi kelulusan mata kuliah menggunakan hybrid fuzzy inference system

Abstract

College is an institution that holds very informative data if it mined properly. Prediction about student’s graduation is a common case that many discussed. Having the predictions of student’s graduation in the middle semester, lecturer will anticipate or give some special attention to students who would be not passed. The method used to prediction is very varied including Fuzzy Inference System (FIS). However, fuzzy rule process is often generated randomly or based on knowledge experts that not represent the data distribution. Therefore, in this study, we used a Decision Tree (DT) technique for generate the rules. So, the research aims to predict courses graduation using hybrid FIS and DT. Dataset used is the posttest score, tasks score, quizzes score, and middle test score from 106 students of the Polytechnic Kediri who took Algorithms and Data Structures. The research started by generating 5 rules by decision tree. The next is implementation of FIS that consist of fuzzification, inference, and defuzzification. The results show that the classifier give a good result in an accuracy, sensitivity, and specificity respectively was 94.33%, 96.55% and 84.21%.