Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Prediksi Ketepatan Waktu Studi Mahasiswa

Abstract

Classification is a statistical technique that aims to classify data into classes that already have labels by building a model based on training data. There are many methods that can be used in the classification including Naïve Bayes and C4.5. The C4.5 algorithm is an algorithm used to form a decision tree while Naïve Bayes is a classification based on probability. This study aims to determine the results of the classification of C4.5 and Naïve Bayes and to determine the classification accuracy of the two methods. The variables used in this study were graduation status , entrance , gender , regional origin , GPA , and UKT group . After the analysis, the results showed that the average accuracy level of the C4.5 algorithm was 61.99% and the Naïve Bayes accuracy level was 69.97%. So it can be said that the Naïve Bayes method is a better method in classifying student status compared to the C4.5 . method.