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Prediction Of Andesit Stone Production using Support Vector Regression Algorithmression

Authors :
Aura Azzahra
M. Afdal
Mustakim Mustakim
Rice Novita
Source :
Sistemasi: Jurnal Sistem Informasi, Vol 13, Iss 5, Pp 1893-1901 (2024)
Publication Year :
2024
Publisher :
Islamic University of Indragiri, 2024.

Abstract

PT. Atika Tunggal Mandiri is a company engaged in andesite stone mining located in the fifty municipalities, West Sumatra. The demand for andesite stones in the company continues to increase, necessitating an increase in production to meet it. Therefore, accurate prediction is needed to assist effective operational planning, enabling the estimation of future andesite stone production to meet market demand. This study aims to predict andesite stone production using the Machine Learning method, specifically the Support Vector Regression algorithm. The research utilizes data from January 2022 to November 2023 with an 80%:20% split for training and testing data. The experimental results using the Linear Kernel yielded an RMSE value of 3444.12 and an MAPE of 9.27%, categorized as "Very Good," followed by the RBF kernel and Polynomial kernel. Based on the obtained error results, the Support Vector Regression algorithm is the best algorithm for predicting andesite stone production.

Details

Language :
Indonesian
ISSN :
23028149 and 25409719
Volume :
13
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Sistemasi: Jurnal Sistem Informasi
Publication Type :
Academic Journal
Accession number :
edsdoj.6fc83e6c61d242b4b6bde45e07a5a65a
Document Type :
article
Full Text :
https://doi.org/10.32520/stmsi.v13i5.4155