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All Journal JOMLAI: Journal of Machine Learning and Artificial Intelligence
Triana Elizabeth
Universitas Muli Data Palembang
Computer Science & IT Engineering

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Heavy Equipment Management Information System at PT Gajah Unggul International Kevin Fernando Cahyadi; Triana Elizabeth
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 5 No. 2 (2026): Juni 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v5i2.9071

Abstract

PT Gajah Unggul Internasional is a company engaged in loading-unloading services and heavy equipment rental that still manages operational data using Microsoft Excel and WhatsApp communication, resulting in several problems such as inaccurate equipment status, delays in maintenance based on Hour Meter (HM), difficulties in contract monitoring, and unstructured recording of heavy equipment expenses and revenues. This study aims to design and develop a web-based Heavy Equipment Operational Management and Monitoring Information System to support more effective and integrated operational data management. The system development method used is Unified Process (UP) with the stages of inception, elaboration, construction, and transition. The system was developed using the Laravel framework and MySQL database with features including heavy equipment management, contract management, mobilization and demobilization, service monitoring, HM recording, expense and revenue management, equipment scheduling, and heavy equipment performance analysis. The results of this study indicate that the system is able to assist the company in monitoring heavy equipment operations more effectively, accelerate data management processes, and support decision making based on available operational information.
Co-Authors Kevin Fernando Cahyadi