Classification of Graduation Students of the Faculty of Computers and Multimedia, Universitas Islam Kebangsaan Indonesia Using the Naïve Bayes Classifier Algorithm

Abstract

The purpose of this study to discuss classification of graduation Students of the Faculty of Computers and Multimedia, Universitas Islam Kebangsaan Indonesia using the naïve bayes classifier algorithm. The methodology used in this study uses a unified modeling language. The results show that the data mining system for classifying graduation Students of the Faculty of Computers and Multimedia, Universitas Islam Kebangsaan Indonesia succeeded in processing datasets, namely training data and sample data to form classes in the classification graduation Students of "Graduated on Time" or "Graduated Late". Processing data mining with the naïve bayes classifier algorithm is able to describe and draw conclusions on large amounts of datasets even though the data is complicated to understand. Research with this web-based system is easy for academics or faculties to use and data processing can be done quickly. Keywords: Classification, Naïve Bayes Classifier, Algorithm