Classification of Student Majors with C4.5 and Naive Bayes Algorithms (Case Study: SMAN 2 Bekasi City)

Authors

  • Antonius Yadi Kuntoro STMIK Nusa Mandiri
  • Hermanto Hermanto STMIK Nusa Mandiri
  • Taufik Asra Universitas Bina Sarana Informatika
  • Ferry Syukmana Universitas Bina Sarana Informatika
  • Hermanto Wahono STMIK Nusa Mandiri

DOI:

https://doi.org/10.18196/st.v23i1.7381

Keywords:

Algorithm C4.5, Naïve Bayes, Student majors

Abstract

School majors conducted in high school are based on interests and these have a goal to provide opportunities for learners to develop the competence of attitudes, skills competence of learners in accordance with interests, talents, and academic ability in a group of scientific subjects.In this research, the researcher uses two algorithm models that is a comparison between the C4.5 algorithm and also the Naive Bayes algorithm. In this study, the data used is the results of school entrance test data and also the data from psychological results for students who have been declared passed the entrance test school SMAN 2 Bekasi City academic year 2018/2019. By comparison of two data mining classification algorithm, can be proved with accuracy result and AUC value from each algorithm that is for Naive Bayes accuracy = 76,43% and AUC value = 0,846, while for algorithm C4.5 accuracy = 70,29% and AUC value = 0.738.

Author Biography

Antonius Yadi Kuntoro, STMIK Nusa Mandiri

 

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Published

2020-05-12

How to Cite

Kuntoro, A. Y., Hermanto, H., Asra, T., Syukmana, F., & Wahono, H. (2020). Classification of Student Majors with C4.5 and Naive Bayes Algorithms (Case Study: SMAN 2 Bekasi City). Semesta Teknika, 23(1), 1–13. https://doi.org/10.18196/st.v23i1.7381

Issue

Vol. 23 No. 1 (2020): MEI 2020

Section

Articles

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