Application of Data Mining for Student Department Using Naive Bayes Classifier Algorithm

Authors

  • Yohana Tri Utami Universitas Lampung
  • Debby Alita Universitas Teknokrat Indonesia
  • Ade Dwi Putra Universitas Teknokrat Indonesia

DOI:

https://doi.org/10.31253/te.v5i1.1012

Keywords:

Data Mining, Algorithm, Naive Bayes Classifier, Student

Abstract

SMAN 02 Negeri Agung does not have a system that can assist schools in determining majors. The problem that occurs is that SMAN 02 Negeri Agung, when doing majors, 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, there are still many students who choose majors not based on their interests or historical grades, such as following friends' choices. This can hinder student academic activities in the future, which will affect the value and development of student potential. With this major system, it is hoped that it can 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.

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Published

2022-03-25

Issue

Section

Articles