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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Abddullah, Mohd Asrul Affendi
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Computer Science & IT Engineering

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Flood Risk Mapping in Batu Pahat Using GIS and Analytic Hierarchy Process Zainudin, Muhammad Ammar Asry; Abddullah, Mohd Asrul Affendi; Abdullah, Nazirah Mohamad; Che Him, Norziha; Sufahani, Suliadi Firdaus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.6644

Abstract

Flooding represents an ongoing natural disaster which creates major hazards that endanger human life and destroy buildings and vital systems. This research project develops a flood risk map for Batu Pahat Malaysia by combining Geographic Information Systems (GIS) with Python-based Analytic Hierarchy Process (AHP) technology. The flood-prone area identification process needs to evaluate high-risk zones and study spatial analysis methods which predict flood risks. Researchers studied three key elements which included land cover and slope and Digital Elevation Model (DEM) based elevation data to determine their impact on flood vulnerability. The AHP process became more efficient and reproducible through Python automation which executed the AHP process for the analysis. The AHP results showed that elevation contributes 63% to flood risk assessment while slope and land cover account for 26% and 11% respectively. The flood risk map divided the area into three danger levels which included low danger areas and medium danger areas plus high danger areas that mostly existed in low-lying urban areas with gentle slopes. The predictions proved accurate because researchers validated them by comparing against actual flood data from previous events. The research demonstrates how AHP combined with GIS and Python creates an efficient flood risk assessment tool which helps with disaster planning and resource management. Future research could enhance the model by incorporating additional factors such as rainfall patterns, drainage infrastructure, and soil characteristics, further improving the accuracy of flood risk predictions.
Co-Authors Abdullah, Nazirah Mohamad Che Him, Norziha Sufahani, Suliadi Firdaus Zainudin, Muhammad Ammar Asry