Journal of Computer Science and Informatics Engineering
Vol 5 No 2 (2026): April

Quality Evaluation of the IZAT Application Based on ISO 25010 an PLTU Tembilahan

A. Rukib (Universitas Islam Indragiri)
Fitri Yunita (Universitas Islam Indragiri)
Bayu Rianto (Universitas Islam Indragiri)



Article Info

Publish Date
30 Apr 2026

Abstract

The Zero Accident Assistant (IZAT) application is a mobile-based system developed to support occupational safety management at PLTU Tembilahan, Indragiri Hilir Regency. The research gap identified in this study stems from the absence of systematic and standardized software quality evaluation for occupational safety applications in the power generation sector, particularly using the ISO 25010 standard. Although this application has been operationally deployed, no standardized quality testing has been conducted, making it difficult to systematically identify potential weaknesses. The novelty of this study lies in the comprehensive application of ISO 25010 combined with technical testing tools (OWASP ZAP and GTmetrix) in the industrial occupational safety domain — a methodological combination not previously found in the literature. This study aims to evaluate the quality of the IZAT Application using the ISO 25010 standard, covering eight quality characteristics: functional suitability, performance efficiency, usability, reliability, security, maintainability, portability, and compatibility. The method used is structured questionnaire-based testing and technical testing using automated tools. Respondents consisted of 35 active users selected through purposive sampling and 5 application developers. The results showed that the IZAT application achieved an overall average quality score of 84.76%, classified as "Good". The functional suitability characteristic obtained the highest score of 88.5%, while maintainability obtained the lowest score of 80.5%. The contributions of this study include: (1) an integrated ISO 25010 evaluation model for occupational safety applications in the energy industry; (2) a quality profile of the IZAT application as a baseline for future development; and (3) evidence-based improvement recommendations. This research provides quality improvement recommendations that can serve as a reference for developers for the next iteration.

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Journal Info

Abbrev

cosie

Publisher

Subject

Computer Science & IT

Description

Artificial Intelligence Machine Learning Natural Language Processing Computer Vision Text Speech Text Mining Data mining Cryptography Data visualization Expert System Deep Learning Fuzzy Logic IoT and smart environments Neural Networks Pattern Recognition Image Processing Optimization Digital Signal ...