Implementation of Decision Tree Algorithm for Predicting Prices and Units Sold at XYZ Auction House using Rapidminer Application

Komharudin Komharudin*, Dewangga Bayu Putra, Christina Juliane


Data mining aims to obtain important information that can provide added value from very large data. Classification is a technique in data mining to classify data based on data attachment to sample data. Classification can be used in one of the areas of sale in this case is the auction hall. The purpose of this study was to predict the number of units sold (sold) and unsold (unsold) at company XYZ with a sample of four-wheeled vehicles and criteria, namely brand, year of publication, engine grade, and price. to predict the number of units sold and unsold and can be used for other companies as a consideration. The results of the accuracy of the decision tree classification is 68.71%, with a total data of 4,714 data.


Data Minning, Auction, Decision Tree

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Riwayat: Educational of History and Humanities indexed by


Riwayat: Educational of History and Humanities

E-ISSN 2775-5037
P-ISSN 2614-3917

Published by History Education Department, Faculty of Teacher Training and Education, Universitas Syiah Kuala, Province Aceh. Indonesia
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