Brilliance: Research of Artificial Intelligence
Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025

Usability-Driven Development of an IoT-Based Salted Fish Quality Detection Application Using the QUIM Model

Muhammad Ikhwani (Information System, Universitas Malikussaleh, Indonesia)
Lidya Rosnita (Universitas Malikussaleh, Indonesia)
Nanda Sitti Nurfebruary (Universitas Malikussaleh, Indonesia)
Asih Makarti Muktitama (Universitas Malikussaleh, Indonesia)
Fidyatunnisa Fidyatunnisa (Universitas Malikussaleh, Indonesia)
Muhammad Zuhdi (Universitas Malikussaleh, Indonesia)



Article Info

Publish Date
29 Dec 2025

Abstract

Salted fish is a vital component of Indonesia’s coastal economy, supporting numerous fishing households and local micro, small, and medium enterprises (MSMEs). However, maintaining product quality during household freezer storage remains a significant challenge. Temperature and humidity fluctuations in shared freezers often lead to quality degradation, discoloration, and the risk of microbial contamination by pathogens such as Salmonella and Staphylococcus aureus. To address these issues, this study developed an Internet of Things (IoT)–based monitoring system that integrates temperature and humidity sensors with an Android application to provide real-time data visualization and automated risk notifications. Recognizing that usability is critical for technology adoption among food-related MSMEs, the Quality in Use Integrated Measurement (QUIM) framework was applied to evaluate system performance across ten dimensions: effectiveness, productivity, satisfaction, efficiency, learnability, flexibility, error tolerance, safety, accessibility, and sustainability. The system was designed using human-centered principles and implemented with an ESP32 microcontroller and DHT22 sensors. A 14-day pilot trial demonstrated that the application could reliably detect environmental fluctuations, with usability scores reflecting high effectiveness (4.1/5) and user satisfaction (4.3/5). Although minor issues with internet connectivity and error message clarity were noted, iterative improvements were successfully incorporated. These findings demonstrate the feasibility of combining IoT technology with QUIM-based evaluation to enhance food storage practices and support quality management in salted fish processing among MSMEs.

Copyrights © 2025






Journal Info

Abbrev

brilliance

Publisher

Subject

Decision Sciences, Operations Research & Management Mathematics Other

Description

Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest ...