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All Journal Jurnal ICT : Information and Communication Technologies
Sembiring, Methewkasly Pratama
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mechanical Engineering

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Data Mining Using Multiple Linear Regression Method for Stock Prediction Sembiring, Methewkasly Pratama; Verina, Wiwi
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i2.288

Abstract

This study aims to apply data mining techniques using multiple linear regression to predict inventory at PT. Sumber Jaya Motor's website. In today's digital era, companies face challenges in managing inventory, which can impact operational efficiency and customer satisfaction. Therefore, accurate inventory prediction is essential to improve inventory management efficiency. The multiple linear regression method was chosen because of its ability to link multiple independent variables with the dependent variable, thus providing more accurate predictions regarding required inventory. The data used in this study includes information related to sales, suppliers, and demand obtained from PT. Sumber Jaya Motor. The results of the multiple linear regression application indicate that the developed model can provide inventory predictions with a high degree of accuracy. This system is implemented on a website to facilitate real-time data-driven monitoring and decision-making. With the implementation of this method, it is hoped that PT. Sumber Jaya Motor can manage inventory more efficiently, reduce inventory costs, and improve customer service.
Co-Authors Wiwi Verina, Wiwi