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All Journal Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar
Asrul Ashari Muin
Program Studi Sistem Informasi, Universitas Islam Negeri Alauddin, Makassar
Computer Science & IT

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Metode Naive Bayes Untuk Prediksi Kelulusan (Studi Kasus: Data Mahasiswa Baru Perguruan Tinggi) Syarli; Asrul Ashari Muin
JURNAL ILMU KOMPUTER Vol 2 No 1 (2016): Edisi April
Publisher : LPPM Universitas Al Asyariah Mandar

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Abstract

Timetables system, genetic algorithm, timetable at universityClassifier created from a set of data. Bayesian classifier is a statistical classifier for predicting the probability of a particular class membership. This research will try to perform data classification for prediction of new student graduation, Naive Bayes algorithm method used for naïve Bayes classification performance high enough ability to predict future opportunities based on experience or data in the past. Imlementation WEKA algorithms in applications that will explore the characteristics of the dataset with superficial attributes Pass options. Evaluation results show classified data correctly (correct classified instances) in accordance with the grouping of choice graduated first choice, second choice and do not pass by the algorithm as much as 93.6288% or as much as 338 data and classified data, but does not match the class predicted (incorrect classified instances ) which should be a group of two or Pass options but are included in the group First choice as many as 6.3712% or as much as 23 data. Value Percentage accuracy demonstrated the effectiveness dataset Admissions applied to the methods Naïve Bayes Classification, which reached 94%
Co-Authors Syarli