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Evaluation of The Implementation of A Regional Emergency Response Information System Based On The Tabalong Siaga Application Using The Human Organization–Technology Fit In Tabalong Regency Doni Irmawan Ismawardi; Hanif Al Fatta
International Journal of Science and Environment (IJSE) Vol. 6 No. 2 (2026): May 2026
Publisher : CV. Inara in Colaboration with www.stie-sampit.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijse.v6i2.683

Abstract

This study aims to evaluate the implementation of the Tabalong Siaga application as a health emergency response information system in Tabalong Regency using the Human-Organization-Technology Fit (HOT-Fit) approach. The main problem is the absence of citizen emergency reports submitted through the application during the September 2025 to February 2026 period, despite the launch of PSC 119 Tabalong Smart on August 30, 2025, 503 application downloads, and 244 reports received through non-application channels. This study applies an explanatory sequential mixed-methods design involving 150 citizen respondents, 60 personnel/operator respondents, and 12 interview informants during March to May 2026. The simulated draft data analysis indicates that 38.7% of citizens had heard of the application, 11.3% had downloaded it, 4.7% had opened it, and 0% had used it to submit an emergency report. WhatsApp preference scored the highest among citizens (mean 4.31), while usage barriers were also high (mean 3.96). Among personnel/operators, system quality was rated relatively adequate (mean 3.44), but system use (mean 2.47) and organizational support (mean 2.64) remained low. Triangulation suggests that non-use is mainly associated with low awareness, strong WhatsApp preference, weak operational SOP enforcement, uneven training, and the absence of mandatory integrated recording. The main recommendations include strengthening SOPs, integrating WhatsApp gateway with the application dashboard, community-based dissemination, recurring training, and monitoring application usage indicators.