Analisis Perbandingan Kinerja Algoritma Naïve Bayes, Decision Tree-J48 dan Lazy-IBK

Authors

  • Indra Rukmana ARS University, Bandung
  • Arvin Rasheda ARS University, Bandung
  • Faiz Fathulhuda ARS University, Bandung
  • Muh Rizky Cahyadi ARS University, Bandung
  • Fitriyani Fitriyani ARS University, Bandung

DOI:

https://doi.org/10.30865/mib.v5i3.3055

Keywords:

Naïve Bayes, Decision Tree-J48, Lazy-IBK, UCI Machine Learning

Abstract

This research is focused on knowing the performance of the classification algorithms, namely Naïve Bayes, Decision Tree-J48 and K-Nearest Neighbor. The speed and the percentage of accuracy in this study are the benchmarks for the performance of the algorithm. This study uses the Breast Cancer and Thoracic Surgery dataset, which is downloaded on the UCI Machine Learning Repository website. Using the help of Weka software Version 3.8.5 to find out the classification algorithm testing. The results show that the J-48 Decision Tree algorithm has the best accuracy, namely 75.6% in the cross-validation test mode for the Breast Cancer dataset and 84.5% for the Thoracic Surgery dataset.

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Published

2021-07-31

Issue

Vol. 5 No. 3 (2021): Juli 2021

Section

Articles

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