Optimization Of Naïve Bayes Algorithm Parameters For Student Graduation Prediction At Universitas Dirgantara Marsekal Suryadarma

Muryan Awaludin, Muryan (2022) Optimization Of Naïve Bayes Algorithm Parameters For Student Graduation Prediction At Universitas Dirgantara Marsekal Suryadarma. Journal of Information System, informatic and Computing, 6 (1). pp. 91-106. ISSN 2597-3673

Text jsc9_JISICOM- Optimization of Naïve Bayes Algorithm Parameters for Student Graduation Prediction at The Aerospace Air Marshal Suryadarma University (Unsurya)-edited.pdf Download (660kB)

Abstract

The Information Systems Study Program at Unsurya is a new department and only a few graduate students. Based on data obtained from graduates of the 2018/2019 academic year, 41 students graduated, including 26 students who experienced delays in taking their studies. A system that can predict student graduation is needed so that the Information Systems department can produce more student graduations than before. By optimizing the parameters of the Naïve Bayes algorithm, it can be applied in predicting graduation by utilizing previous student graduation data, the attributes used are gender, age, sks, gpa, and student status. The results of research testing using Rapid Miner 9.8 with 41 training data and 25 testing data, yielding 96% accuracy, 90.91% recall, and 100% precision.

Item Type:	Article
Subjects:	A General Works > AI Indexes (General)
Depositing User:	Muryan Awaludin
Date Deposited:	05 Aug 2022 07:29
Last Modified:	05 Aug 2022 07:29
URI:	http://eprints.universitassuryadarma.ac.id/id/eprint/1288

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