C45 Algorithm for Motorcycle Sales Prediction On CV Mokas Rawajitu

Abstract

CV Mokas Rawajitu is a company that sells various types of used motorbikes both in cash and on credit. In sales, the problem that occurs is the frequent occurrence of ups and downs in motorcycle sales due to the mismatch of the available motorcycle variants with consumer interests so that motorcycle sales often do not reach the target. The role of data mining is needed to analyze consumer purchasing patterns at CV Mokas Rawajitu which can produce information, namely knowing what types of motorbikes most in-demand by consumers are and which are most in-demand in the market by predicting using the C4.5 algorithm based on the sales transaction data they have. from previous periods. The study used a dataset of motorcycle sales at CV Mokas Rawajitu from 2017-2019 with a total data volume of 1,411 data. The attributes used are the motorbike category, the motorbike brand, the motorbike price, and the year of production. The tools used in this research are Rapid Miner. The results of the application of the C4.5 Algorithm can be used as a prediction of sales at CV Mokas Rawajitu because the results of the accuracy of testing data and models using 9-Fold Cross Validation reach a value of 87.95% where the 9th fold reaches the highest accuracy value with a Sensitivity level of 97, 15%, 69.05% Specificity, 86.57% Precision, 12.05% Error (Error Rate) and 30.95% False Positive Rate.