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All Journal Jurnal Kecerdasan Buatan dan Teknologi Informasi
Rizky Fadillah Putra Pratama
Universitas Bhayangkara Jakarta Raya
Computer Science & IT

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Web-Based Stock Overstock Warning System for Spare Parts Inventory Using Linear Regression Rizky Fadillah Putra Pratama; R Wisnu Prio Pamungkas; Fried Sinlae
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 3 (2026): September 2026 In progress.
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i3.568

Abstract

Inventory management in the automotive spare parts industry faces a criticalchallenge in managing overstock conditions, which lead to increased storagecosts and capital freezing. PT. Dipo Internasional Pahala Otomotif currentlymanages spare parts inventory manually, without any predictive alert systemcapable of detecting potential overstock based on sales data. This study developsa web-based overstock warning system using the Simple Linear Regressionalgorithm implemented in the Laravel framework to predict spare parts stockrequirements and automatically trigger overstock alerts. The system was builtfollowing the Waterfall development methodology through seven sequentialphases: planning, analysis, design, coding, testing, implementation, and maintenance.The linear regression model uses time period as the independentvariable (X) and stock quantity as the dependent variable (Y ), forming theprediction equation Y = a + bX. Based on a simulation with n = 4 periods,the resulting equation Y = 7 + 2.7X predicted a stock of 20.5 units in period5, which exceeded the defined overstock threshold. System evaluation usingBlack Box Testing confirmed that all functional modules operated correctly.The system successfully provides automated overstock detection and real-timealert notifications, enabling more accurate and data-driven inventory decisionsat PT. Dipo Internasional Pahala Otomotif.
Co-Authors Fried Sinlae R Wisnu Prio Pamungkas