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All Journal Riwayat: Educational Journal of History and Humanities
Christina Juliane
Program Pasca Sarjana Komputer Management, STMIK LIKMI STMIK Amik Bandung Kota Bandung
Humanities Education Social Sciences

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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
Riwayat: Educational Journal of History and Humanities Vol 6, No 3 (2023): Social, Political, and Economic History
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v6i3.33769

Abstract

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.
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
Riwayat: Educational Journal of History and Humanities Vol 6, No 3 (2023): Social, Political, and Economic History
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v6i3.33769

Abstract

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.
Co-Authors Dewangga Bayu Putra Komharudin Komharudin*