Flood Vulnerability Mapping in Cepu Subdistrict Using Mamdani Fuzzy Inference System for Disaster Risk Reduction
DOI:
https://doi.org/10.30812/matrik.v25i1.5390Keywords:
Cepu Subdistrict, Fuzzy Inference System, Flood Vulnerability, MamdaniAbstract
Floods pose a persistent and serious threat to Cepu Subdistrict, frequently causing significant economic loss, resident displacement, and damage to critical infrastructure. In response to this issue, and aligned with the National Disaster Management Agency's (BNPB) efforts to enhance landscape monitoring, a comprehensive analytical study was conducted. The purpose of this research was to assess and map the flood vulnerability levels across 17 villages in Cepu Subdistrict, categorizing them to facilitate more effective disaster response planning and resource allocation. The research method uses the Mamdani Fuzzy Inference System, an advanced computational approach adept at handling the non-linear relationships between environmental variables. This system allowed for a detailed analysis of the complex interactions among key flood-influencing factors, including rainfall intensity, watershed area, elevation, slope, and population density. The results of the quantitative research obtained from 17 villages in the Cepu Subdistrict show that Ngelo Village has the highest score of 65.16, categorized as a "high" risk level. In contrast, most other villages, such as Ngroto, Karangboyo, and Cabean, fell into the "medium" risk category with varying scores between 55.0 and 63.93. The model's accuracy was validated by evaluation metrics, with a Mean Absolute Error (MAE) of 8.67 and a Root Mean Squared Error (RMSE) of 10.29, indicating satisfactory predictive performance. The conclusion of this study emphasizes the urgent need for comprehensive and adaptive mitigation strategies, including early warning systems and community preparedness programs, to protect Cepu Subdistrict from future flood threats.
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