Analisis Perbandingan Algoritma Naïve Bayes, KNN dan Decision Tree untuk Hasil Prediksi Kelulusan Cpns Auditor Ahli Pertama

Authors

  • Indah Dwijayanthi Nirmala Universitas Budi Luhur
  • Dwi Budi Srisulistiowati Universitas Bhayangkara Jakarta Raya

DOI:

https://doi.org/10.31599/a5afw728

Keywords:

Decision Tree, KNN, Naive Bayes, Rapid Minner

Abstract

It cannot be denied that every time there is a CPNS acceptance, many are ready to compete to be able to graduate as a civil servant. To become a civil servant, one of the challenges that must be faced is taking the CAT SKD, SKB test by meeting the CAT threshold scores determined by BKN. Where the final graduation rate for CPNS participants is by getting the highest score from the specified number of formations.

Therefore, the evaluation carried out by researchers in carrying out a comparative analysis of the Decision Tree, KNN, and Naïve Bayes algorithms for the predicted results of the 2021 Ministry of Religion First Expert Auditor CPNS graduation using Rapid Minner Tools. The results of this research will help in providing more effective and efficient solutions in assessing the qualifications of CPNS candidates, as well as minimizing subjective biases that may arise in the manual selection process.

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Published

2025-08-31

Issue

Vol. 6 No. 1 (2025): Juni 2025

Section

Artikel

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How to Cite

Analisis Perbandingan Algoritma Naïve Bayes, KNN dan Decision Tree untuk Hasil Prediksi Kelulusan Cpns Auditor Ahli Pertama. (2025). Journal of Informatic and Information Security, 6(1), 57-68. https://doi.org/10.31599/a5afw728