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Situmorang, Zakaria
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes Azhari, Mulkan; Situmorang, Zakaria; Rosnelly, Rika
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2937

Abstract

In this study aims to compare the performance of several classification algorithms namely C4.5, Random Forest, SVM, and naive bayes. Research data in the form of JISC participant data amounting to 200 data. Training data amounted to 140 (70%) and testing data amounted to 60 (30%). Classification simulation using data mining tools in the form of rapidminer. The results showed that . In the C4.5 algorithm obtained accuracy of 86.67%. Random Forest algorithm obtained accuracy of 83.33%. In SVM algorithm obtained accuracy of 95%. Naive Bayes' algorithm obtained an accuracy of 86.67%. The highest algorithm accuracy is in SVM algorithm and the smallest is in random forest algorithm
Co-Authors Mulkan Azhari Rika Rosnelly, Rika