Jurnal Kecerdasan Buatan dan Teknologi Informasi
Vol. 5 No. 3 (2026): September 2026 In progress.

Optimization of Spare Parts Stock Control Using Safety Stock and Reorder Point Approach with Laravel

Dimas Sanjaya (Universitas Bhayangkara Jakarta Raya)
R Wisnu Prio Pamungkas Pamungkas (Unknown)
Fried Sinlae (Unknown)



Article Info

Publish Date
01 Sep 2026

Abstract

Inventory management is a critical aspect of ensuring business operational continuity, particularly in maintaining spare parts availability for automotive workshops. Bengkel Mo Gerzz, a Vespa Matic specialist workshop, handles 1 to 10 vehicles daily with over 100 types of spare parts managed manually through simple records and verbal communication, leading to real-time stock monitoring limitations and reorder inaccuracies. This study develops a web-based inventory management system built with the Laravel framework, integrating the Safety Stock (SS) and Reorder Point (ROP) methods based on lead time to optimize spare parts stock control. The system was developed using the Waterfall methodology through seven sequential phases: planning, analysis, design, development, testing, implementation, and maintenance. The proposed SS formula calculates buffer stock as SS = (Dmax × Lmax) − (Davg × Lavg), while ROP is determined by ROP = (Davg × L) + SS. The system was evaluated using Black Box Testing across six modules, achieving a 100% pass rate across 24 test scenarios. Calculation results for 21 spare part types showed that Oli Mesin Ipone Scooter 10W-40 Premium recorded the highest SS value of 14.97 and ROP of 18, indicating the greatest demand variability. The system provides automated restock notifications when stock reaches the ROP threshold, enabling more structured and data-driven procurement decisions at Bengkel Mo Gerzz.

Copyrights © 2026






Journal Info

Abbrev

JKBTI

Publisher

Subject

Computer Science & IT

Description

Jurnal Kecerdasan Buatan dan Teknologi Informasi or abbreviated JKBTI is a national journal published by the Ninety Media Publisher since 2022 with E-ISSN : 2964-2922 and P-ISSN : 2963-6191. JKBTI publishes articles on research results in the field of Artificial Intelligence and Information ...