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All Journal JRST (Jurnal Riset Sains dan Teknologi)
Janice Thea Sumar
Program Studi Sistem Informasi, Institut Shanti Bhuana, Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering

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Implementation of Smart Detection in Risk Monitoring and Flood Mitigation in Bengkayang Regency Candra Gudiato; Santi Thomas; Rossi Gawida; Janice Thea Sumar
JRST (Jurnal Riset Sains dan Teknologi) Volume 10 No. 2, September 2026 :JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v10i2.29050

Abstract

Bengkayang Regency is one of the areas prone to flooding due to extreme rainfall, poor drainage systems, and low vegetation. This research aims to develop an Internet of Things (IoT)-based Smart Detection system for real-time flood risk monitoring and mitigation. The scientific contribution of this study lies in the integration of three main parameters—water level, rainfall, and Normalized Difference Vegetation Index (NDVI)—which are processed using the Simple Additive Weighting (SAW) method to determine flood vulnerability levels. Test results at four research locations show that Teriak District (Vi = 0.964) and Lumar District (Vi = 0.939) are identified as "safe" areas, while Seluas District (Vi = 0.489) and Ledo District (Vi = 0.640) have "alert" status that requires special attention from the local government. The Smart Detection system is capable of providing early warnings for incoming floods and is expected to contribute to the local government's more holistic mitigation decision-making and enhance community preparedness for potential disasters. ABSTRAK (Bahasa Indonesia) Kabupaten Bengkayang merupakan salah satu wilayah yang rawan banjir, akibat curah hujan ekstrem, buruknya sistem drainase, dan rendahnya vegetasi. Penelitian ini bertujuan untuk mengembangkan sistem Smart Detection berbasis Internet of Things (IoT) untuk pemantauan risiko dan mitigasi banjir secara real-time. Kontribusi ilmiah penelitian ini terletak pada integrasi tiga parameter utama, yaitu ketinggian air, curah hujan, dan tingkat kehijauan lahan (NDVI), yang diolah menggunakan metode Simple Additive Weighting (SAW) untuk menghasilkan keputusan tingkat kerawanan banjir. Hasil pengujian pada empat lokasi penelitian menunjukkan bahwa Kecamatan Teriak (Vi= 0,964) dan Kecamatan Lumar (Vi=0,939) teridentifikasi sebagai wilayah “aman” dari banjir, sedangkan Kecamatan Seluas (Vi= 0,489) dan Kecamatan Ledo (Vi= 0,640) memiliki tingkat kerawanan dengan status “waspada” yang memerlukan perhatian khusus dari pemerintah daerah setempat.  Sistem Smart Detection mampu memberikan peringatan dini akan datangnya banjir dan diharapkan dapat berkontribusi bagi pemerintah daerah setempat dalam pengambilan keputusan mitigasi yang lebih holistik serta meningkatkan kesiapsiagaan masyarakat terhadap potensi bencana banjir.
Co-Authors Gudiato, Candra Rossi Gawida Santi Thomas