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All Journal Seminar Nasional Teknologi Informasi Komunikasi dan Industri
Eka Lona Maulida
Teknik Informatika, Fakultas Sains dan Teknologi, UIN Sultan Syarif Kasim Riau
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

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Perkiraan Waktu Studi Mahasiswa Menggunakan Metode Klasifikasi Dengan Algoritma Naive Bayes Lestari Handayani; Eka Lona Maulida
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2015: SNTIKI 7
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

The problems of time studi are caused by many factors. So it needs to be made graduation prediction system to determine what factors can affect student graduation. The system is designed to prediction of student graduation rate using data mining with Naive Bayes algorithm. The criteria used in predicting graduation rates are GPA, nim, sex, and place of birth, home school, home town school, class, date and year of graduation. This system was designed and built using the PHP programming language and MySQL database. Training data used 150 data. After analysis and testing, the accuracy of system using 25 data testing from data training amounted 88%. The accuracy of system using 25 data testing from out of data training amounted 92%. A result of analysis is students with a GPA above 3 predicted to graduate on time. GPA is very influential on the prediction system so that the accuracy of the training data is smaller than the accuracy of the data outside the training.Key words: data mining, MySql, Naïve Bayes, PHP, students, time study.
Co-Authors Lestari Handayani