PERBANDINGAN ALGORITMA C4.5 DAN NAIVE BAYES UNTUK MEGUKUR MINAT PENJUALAN SEPATU

Abstract

The Second Gangbrand shoe shop is one that sells second-hand shoes or what you could also call quality and original second-hand shoes that have certain brands at affordable prices that are cheaper than the original price. This research aims to measure the level of customer interest by comparing the C4.5 algorithm method and the Naive Bayes algorithm. The data source was obtained from second gangbrand stores which were taken based on customer interest. So it is necessary to carry out data analysis to classify customer interest data using the C4.5 and Naive Bayes algorithms to compare accuracy and precision which are the benchmarks in this research. Calculations in this research were carried out manually using Microsoft Excel according to the C4.5 and Naive Bayes algorithm calculation models and then evaluated using the Rapidminer 10.3 tool which was used to help determine accurate values. After conducting research testing, the C4.5 algorithm received an accuracy value of 60.00% and a precision of 50.00%, while the Naive Bayes algorithm received an accuracy value of 60% and a precision of 33.33%. So it can be concluded that the two algorithms have the same accurate accuracy value, but in terms of precision value the C4.5 algorithm is superior in determining customer interest recommendations. It is hoped that the results of this research can provide input and information for future researchers.