JOMLAI: Journal of Machine Learning and Artificial Intelligence
Vol. 5 No. 2 (2026): Juni 2026

Heavy Equipment Management Information System at PT Gajah Unggul International

Kevin Fernando Cahyadi (Universitas Multi Data Palembang)
Triana Elizabeth (Universitas Muli Data Palembang)



Article Info

Publish Date
15 Jun 2026

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.

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Journal Info

Abbrev

jomlai

Publisher

Subject

Computer Science & IT Engineering

Description

Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well ...