Modelling of Flood Hazard Early Warning Group Decision Support System

Arief A. Soebroto; Lily M. Limantara; Ery Suhartanto; Moh. Sholichin

doi:10.28991/CEJ-2024-010-02-018

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Arief A. Soebroto
ariefas@ub.ac.id
1) Doctoral Student in Department of Water Resources Engineering, Faculty of Engineering, University of Brawijaya, Malang, Indonesia. 2) Department of Informatics, Faculty of Computer Science, University of Brawijaya, Malang,, Indonesia http://orcid.org/0000-0001-9917-7663
Lily M. Limantara Department of Water Resources Engineering, Faculty of Engineering, University of Brawijaya, Malang,, Indonesia
Ery Suhartanto Department of Water Resources Engineering, Faculty of Engineering, University of Brawijaya, Malang,, Indonesia
Moh. Sholichin Department of Water Resources Engineering, Faculty of Engineering, University of Brawijaya, Malang,, Indonesia

Vol. 10 No. 2 (2024): February

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Early warning of flood hazards needs to be carried out comprehensively to avoid a higher risk of disaster. Every decision on early warning of a flood hazard is carried out in part by one party, namely the government or water resource managers. This research aims to provide a collaborative decision-making model for early warning of flood hazards through a Group Decision Support System Model (GDSS), especially in Indonesia. The novelty of this research is that the GDSS model involves more than one decision-maker and multi-criteria decision-making for early warning of flood hazards in the downstream Kali Sadar River, Mojokerto Regency, East Java Province, Indonesia. The GDSS model was developed using a hybrid method, namely the Analytical Network Process (ANP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). There was more than one decision result; voting was carried out using the BORDA method to produce the decision. The test results of GDSS were obtained using a Spearman rank correlation coefficient of 0.8425 and matrix confusion, an accuracy value of 86.7%, a precision value of 86.7%, a recall value of 86.7%, and an f-measure of 86.7%. Based on the test results, good results were obtained from the GDSS model.

Doi: 10.28991/CEJ-2024-010-02-018

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Soebroto, A. A., Limantara, L. M., Suhartanto, E., & Sholichin, M. (2024). Modelling of Flood Hazard Early Warning Group Decision Support System. Civil Engineering Journal, 10(2), 614–627. https://doi.org/10.28991/CEJ-2024-010-02-018

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Publication Start Year:	2015
JCR 2024 Impact Factor (IF):	4.9
JIF QUARTILE:	Q1
SJR 2024 Quartile:	Q1
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Modelling of Flood Hazard Early Warning Group Decision Support System

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