DECISION TREE UNTUK PREDIKSI SISWA TERBAIK BERBASIS WEBSITE PADA MTs DARUL FALAH

Authors

  • Astuti Hadijah Pili Fakultas Teknologi Informasi Universitas Hasyim Asy'ari Tebuireng Jombang
  • Ahmad Heru Mujianto Fakultas Teknologi Informasi Universitas Hasyim Asy'ari Tebuireng Jombang
  • Reza Augusta Jannatul Firdaus Fakultas Teknologi Informasi Universitas Hasyim Asy'ari Tebuireng Jombang
  • Mahrus Ali Fakultas Teknologi Informasi Universitas Hasyim Asy'ari Tebuireng Jombang

DOI:

https://doi.org/10.33752/inovate.v9i2.8870

Abstract

MTs Darul Falah is an agency that predicts the best students manually and still uses Excel, so the system that has been created will make it easier for teachers to predict the best students. In determining/predicting the best students the author uses the Decision Tree method. Decision Tree One of the classification algorithms that is commonly used to obtain non-binary classification results where the results will form the root of a decision tree. Therefore, the importance of the best student prediction system in making a decision. The aim of the research is to make it easier for schools to determine the best students who can be sent to take part in the Olympics. In this research, testing was carried out using Black Boks Testing. The results of this research are in the form of a website-based best student prediction system with data from 25 students who were predicted to be the best students. Overall it can be concluded that in testing the application the best student predictions were received according to what was needed.

Keywords: Predictions, Decision Trees, Thesis Topics

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Published

2025-04-20

How to Cite

Hadijah Pili, A., Heru Mujianto, A., Augusta Jannatul Firdaus , R., & Ali , M. (2025). DECISION TREE UNTUK PREDIKSI SISWA TERBAIK BERBASIS WEBSITE PADA MTs DARUL FALAH . Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi, 9(2), 43–50. https://doi.org/10.33752/inovate.v9i2.8870

Issue

Vol. 9 No. 2 (2025): Inovate: Jurnal Ilmiah Inovasi Teknologi Informasi

Section

Artikel

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