Utami, Yohana Tri (2022) Application of Data Mining for Student Department Using Naive Bayes Classifier Algorithm. TECH-E, 5 (2). pp. 125-132. ISSN 2598-7585

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Abstract

SMAN 02 Negeri Agung does not have a system that can assist schools in determining majors. The problem is that SMAN 02 Negeri Agung,when doing majors, it still uses existing data. For example, using a majoring interest questionnaire, there are questions about the interests that students want, and the values of their junior high school report cards, which consist of Indonesian, Mathematics, Science, Social Studies, and English. However, many students still choose majors not based on their interests or historical grades, such as following friends' choices. It can hinder student academic activities in the future, which will affect the value and development of student potential. This effective system hopes to help schools and students minimize errors in determining and choosing a major. Based on the problems described above, the authors want to apply the Naïve Bayes method, which will produce a high level of accuracy in determining new student majors more effectively and efficiently.The accuracy of the naive Bayes classifier can be stated quite well. It can be seen based on accuracy, 63.46%, error rate 0.3653%, false positive rate 0.2424%, sensitivity 0.6035%, specificity 0.7575%, and precision 0.944% Naive Bayes classifier method can It is recommended to predict student majors.

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer
Depositing User:	M.Kom. Yohana Tri Utami
Date Deposited:	02 Aug 2022 09:48
Last Modified:	02 Aug 2022 09:48
URI:	http://repository.lppm.unila.ac.id/id/eprint/43809

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