EARLY DETECTION OF PROBLEM STUDENTS USING THE RANDOM FOREST METHOD AT SMK MUHAMMDIYAH 3 BANJARMASIN

Authors

  • Frista Rinandi STMIK Likmi Bandung
  • Hery Heryanto Institut Teknologi Harapan Bangsa Bandung
  • Koes Wiyatmoko Politeknik Negeri Banjarmasin

DOI:

https://doi.org/10.31961/positif.v9i1.1820

Keywords:

Data Mining, classification, Random Forest

Abstract

Education is the basic capital for the state in developing productive and quality human resources. To produce a good quality education is also influenced by the behavior of children during the school period. Some of the variables that influence children's behavior include the family, environment, play and economic level. From some of these variables, the Random Forest method can be used to predict the success rate of children by processing data based on predetermined variables. To produce a prediction with a high level of accuracy, a method is also needed, namely the Confusion Matrix, to process variables which are input, an online based application is created using Python whose output immediately produces predictions of " Bermasalah" or "Tidak Bermasalah".

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Published

2023-05-30

How to Cite

Rinandi, F., Heryanto, H., & Wiyatmoko, K. (2023). EARLY DETECTION OF PROBLEM STUDENTS USING THE RANDOM FOREST METHOD AT SMK MUHAMMDIYAH 3 BANJARMASIN. POSITIF : Jurnal Sistem Dan Teknologi Informasi, 9(1), 1–7. https://doi.org/10.31961/positif.v9i1.1820

Issue

Vol. 9 No. 1 (2023): Positif : Jurnal Sistem dan Teknologi Informasi (On Progress)

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Articles

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Copyright (c) 2023 Frista Rinandi, Hery Heryanto, Koes Wiyatmoko

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This work is licensed under a Creative Commons Attribution 4.0 International License.