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Rachmat Kasim
Universitas Ichsan Gorontalo Utara
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Library & Information Science

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An Iot-Based Flood Early Warning System Integrated with the Sesaga Approach Rachmat Kasim; Eric Alfonsius
Jurnal Teknoinfo Vol. 20 No. 2 (2026): Period July 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/teknoinfo.v20i2.1570

Abstract

Floods are among the natural disasters that significantly impact human safety, infrastructure, and the economy, particularly in flood-prone areas. Therefore, an early detection system capable of providing fast, accurate, and adaptive information is required to support risk mitigation efforts. This study develops a Flood Early Detection System based on the SESaGa approach (Systematic, Exploratory, SWOT, and GIS Analysis), which integrates Systematic Literature Review (SLR), Exploratory Data Analysis (EDA), SWOT, and GIS. Research data were obtained from a flood monitoring prototype installed at several flood-prone points in Gorontalo. The implementation results show that the SESaGa approach enhances early detection accuracy and provides valuable spatial information for mitigation planning. In addition, the integration of SWOT analysis generates strategic recommendations for strengthening the system and disaster management policies. The developed system was also tested using the blackbox testing method to ensure that the software functionalities meet user requirements. The test results demonstrate that all key features, including sensor data monitoring, warning notifications, and GIS-based visualization, functioned properly without critical errors. Thus, this system has the potential to serve as an essential instrument in supporting community resilience against flood threats and improving the effectiveness of mitigation measures in vulnerable regions.
Co-Authors Alfonsius, Eric