Penerapan Naive Bayes Untuk Memprediksi Kelulusan Mahasiswa Rekayasa Perangkat Lunak Politeknik Negeri Bengkalis
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Institusion
Politeknik Negeri Bengkalis
Author
Samosir, May Sinta
Subject
458 Teknik Informatika
Datestamp
2024-08-31 15:09:34
Abstract :
This research aims to apply the Naïve Bayes algorithm as a method for predicting the acceptance of Bengkalis State Polytechnic Software Engineering students. Naïve Bayes is used to group student data based on certain attributes to predict the likelihood of admission. The dataset used is software engineering student alumni data including social studies, GPA, credits, organization, programming skills competitions, activity in class and the student's year of graduation. The prediction results from the Naïve Bayes algorithm with an accuracy of 76,47%. are expected to provide information and input for universities in making future policies.
This research aims to apply the Naïve Bayes algorithm as a method for predicting the acceptance of Bengkalis State Polytechnic Software Engineering students. Naïve Bayes is used to group student data based on certain attributes to predict the likelihood of admission. The dataset used is software engineering student alumni data including social studies, GPA, credits, organization, programming skills competitions, activity in class and the student's year of graduation. The prediction results from the Naïve Bayes algorithm with an accuracy of 76,47%. are expected to provide information and input for universities in making future policies.
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