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
DOI:
https://doi.org/10.51601/ijse.v6i2.683Abstract
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.
Downloads
References
[1] Yusof, M.M., Kuljis, J., Papazafeiropoulou, A., & Stergioulas, L.K. (2008). An evaluation framework forHealth Information Systems: Human, Organization and Technology-Fit factors (HOT-Fit). International Journal of Medical Informatics, 77(6), 386-398.
[2] World Health Organization.(2021). Global strategy on digital health 2020-2025. Geneva: World Health Organization.
[3] Zakerabasali, S., Ayyoubzadeh, S.M., Baniasadi, T., Yazdani, A., & Abhari, S. (2021). Mobile health technology and healthcare providers: Systemic barriers to adoption. Healthcare Informatics Research, 27(4), 267-278.
[4] Aljedaani, B., Ahmad, A., Zahedi, M., & Babar, M.A. (2021). End-users knowledge and perception about security of mobile health apps: A case study with two Saudi Arabian mHealth providers.arXiv preprint arXiv:2101.10412.
[5] Aljarboa, SSM, & Miah, SJ (2022). Discovering adoption barriers of clinical decision support systems in primary health care sector. arXiv preprint arXiv:2207.11713.
[6] Borges do Nascimento, IJ, Abdulazeem, H., Vasanthan, LT, et al. (2023). Barriers and facilitators to using digital health technologies by healthcare professionals. npj Digital Medicine, 6, 161.
[7] Fan, S., Jain, R.C., & Kankanhalli, M.S. (2023). A comprehensive picture of factors influencing user willingness to use mobile health applications. arXiv preprint arXiv:2305.05962.
[8] Stoumpos, A.I., Kitsios, F., & Talias, M.A. (2023). Digital transformation in healthcare: Technology acceptance and its applications. International Journal of Environmental Research and Public Health, 20(4), 3407.
[9] Rodrigues, D.A., et al. (2024). Barriers and facilitators of health professionals in adopting digital health-related tools for medication appropriateness: A systematic review. Digital Health, 10.
[10] Meng, D., Li, Y., et al. (2024). Influence of doctor-patient trust on the adoption of mobile medical apps. Frontiers in Public Health, 12.
[11] Oudbier, S.J., et al. (2024). Implementation barriers and facilitators of remote monitoring, remote consultation and digital care platforms. BMJ Open, 14(6), e075833.
[12] Aydin, G., & Silahtaroglu, G. (2024). Insights into mobile health application market via a content analysis of marketplace data with machine learning. arXiv preprint arXiv:2402.10789.
[13] Alzghaibi, H. (2025). Healthcare practitioners' perceptions of mHealth application adoption barriers. Healthcare, 13(6), 665.
[14] Watson, S.L., et al. (2025). Adherence to usability and accessibility principles in digital health apps: A systematic review. Journal of Medical Internet Research, 27, e71567.
[15] Yew, SQ, et al. (2025). Facilitators and barriers to the implementation of digital health technologies. Journal of Medical Internet Research, 27, e63482.
[16] Okeke, E.B., et al. (2025). Barriers and facilitators to digital health adoption: A thematic analysis of healthcare professionals' perspectives in rural Oyo State, Nigeria. BMC Digital Health, 3, 85.
[17] Wittich, L., et al. (2026). Implementation of digital health technologies: A scoping review of barriers and facilitators. Implementation Science Communications.
[18] Tabalong Regency Central Statistics Agency. (2026). Tabalong Regency in Figures 2026. Tanjung: Tabalong Regency BPS.
[19] Tabalong Regency Government. (2025). Demographics of Tabalong Regency. Official Portal of Tabalong Regency.
[20] Ministry of Health of the Republic of Indonesia. (2016). Regulation of the Minister of Health Number 19 of 2016 concerning the Integrated Emergency Management System. Jakarta: Ministry of Health of the Republic of Indonesia.
[24] JF Hair Jr., GTM Hult, CM Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA: Sage, 2022.
[25] Tabalong Regency Central Statistics Agency, Tabalong Regency in Figures 2026. Tabalong: BPS Tabalong Regency, 2026.
[26] Tabalong Regency Government, “Demography of Tabalong Regency,” Official Portal of Tabalong Regency, 2025.
[27] Ministry of Health of the Republic of Indonesia, Regulation of the Minister of Health Number 19 of 2016 concerning the Integrated Emergency Management System, 2016.
[28] Tabalong District Health Office/PSC 119 Tabalong Smart, Recapitulation of PSC 119 Tabalong Smart Report Channels for the Period September 2025-February 2026, 2026.
[29] Fan, S., Jain, R.C., & Kankanhalli, M.S. (2023). A comprehensive picture of factors influencing user willingness to use mobile health applications. International Journal of Medical Informatics.
[30] Munjirin, M., Intisari, AD, & Aji, B. (2024). Evaluation of the implementation of the hospital management information system (SIMRS) using the HOT-FIT method: Systematic review. Science Midwifery, 12(3), 1100-1108.
[31] Ilmada, H. (2023). Evaluation of hospital management information systems using the HOT-Fit method: A literature review. World Journal of Advanced Research and Reviews, 19(3), 685-693.
[32] Saputra, MHA (2026). Evaluating Medxa SIMRS implementation success using the HOT-Fit framework. Information Systems International Journal.
[33] Ekananda, F.P. (2025). Evaluation of healthcare service digitalization using the HOT-Fit framework. Journal La Sociale.
[34] Pamungkas, RA (2025). Hospital Information System (SIRS) using Human Organization Technology-Fit in pharmaceutical installation. International Journal of Nursing and Health Services.
[35] Rahman, B. (2025). HOT-FIT-BR: A context-aware evaluation framework for digital health systems in resource-limited settings. arXiv preprint.
[36] Ministry of Health of the Republic of Indonesia. (2022). 2024 Health Digital Transformation Strategy Blueprint. Jakarta: Ministry of Health of the Republic of Indonesia.
[37] Ministry of Administrative and Bureaucratic Reform. (2021). Guidelines for Evaluating Electronic-Based Government Systems. Jakarta: KemenPAN-RB.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Doni Irmawan Ismawardi, Hanif Al Fatta
This work is licensed under a Creative Commons Attribution 4.0 International License.
