JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 5, No 2 (2021): April 2021

Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes

Azhari, Mulkan (Unknown)
Situmorang, Zakaria (Unknown)
Rosnelly, Rika (Unknown)

Article Info

Publish Date
25 Apr 2021

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

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Journal Info
JURNAL MEDIA INFORMATIKA BUDIDARMA
Website

Abbrev

mib

Publisher

Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...