Paper Contents
Abstract
ABSTRACT:Student graduation is important in the accreditation assessment process. Because student graduation there are standards that must be Achieved by the Study Program items, namely a four-year study period and a 3.0GPA. Therefore we need a prediction that can Anticipate from the beginning of the graduation standard level that has been set. This study aims to predict student graduation using Nave Bayes Classifier with a data mining approach. Nave Bayes provides accurate prediction results with a minimum error rated compared to all other data mining components. With the prediction of the student, graduation can be used as input, especially the Information System Study Program in making policies for improvement in the future. The software used in data processing is WEKA. The test results showed that from the Information Systems Study Program Faculty of Computer Science Faculty of Sriwijaya University in 2015 as many as 141 students as training data and in 2016 as many as 127 students as testing data, the prediction accuracy was 97,6378%.Keywords: predicted, data mining, Nave Bayes classifier
Copyright
Copyright © 2024 Gayathri Sri.R. This is an open access article distributed under the Creative Commons Attribution License.
