Open AccessAnalisis Perbandingan Kinerja Algoritma Naïve Bayes, Decision Tree-J48 dan Lazy-IBK
Author(s) -
Indra Rukmana,
Arvin Rasheda,
Faiz Fathulhuda,
Muh Rizky Cahyadi,
Fitriyani Fitriyani
Publication year - 2021
Publication title -
jurnal media informatika budidarma/jurnal media informatika budidarma
Language(s) - English
Resource type - Journals
eISSN - 2614-5278
pISSN - 2548-8368
DOI - 10.30865/mib.v5i3.3055
Subject(s) - c4.5 algorithm , decision tree , naive bayes classifier , computer science , tree (set theory) , decision tree learning , data mining , machine learning , artificial intelligence , support vector machine , mathematics , mathematical analysis
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.