Mitigation Priority Scale with Self-Organising Map in Viewing Flood Prone Area Distribution Pattern Mapping
Keywords:
Analytic Hierarchy Process, Cluster, Flooding, Mitigation, Self-Organizing Map.Abstract
Flooding is a prevalent natural calamity that causes detrimental effects. From 2019 to 2022, nearly all sub-districts spanning an area of 193,200 hectares experienced floods in the North Aceh region. Issues arising from insufficient information, particularly spatial data pertaining to the state of flood-prone areas and the subsequent damages that may be caused, which are crucial for guiding flood prevention measures. This study employed a Analytic Hierarchy Process (AHP) and self-organizing map (SOM) models to categorize areas based on the distribution patterns of flood-prone areas. The main objective was to assess the level of risk associated with flood disasters. The research approach involves collecting data at the office of the Regional Disaster Management Agency (BPBD) in flood-prone areas, followed by establishing the causes of flooding based on criteria such as Soil Structure, Soil Slope, and Land Use. The subsequent phase entails classification utilizing the self-organizing map (SOM) architectural model. District Lhoksukon has the following values: X1 = 1, X2 = 0.005865103, X3 = 0.274919614, X4 = 0.468069147. The value of W1 is 0.468069147. Cluster 1 consists of 21 sub-districts, cluster 2 consists of 3 sub-districts, and cluster 3 consists of 3 sub-districts. Cluster 3 exhibits moderate results and has a low susceptibility to flood distribution. Cluster 2 shows moderate susceptibility to flood distribution, whereas cluster 1 is highly susceptible to flood distribution. Essentially, the determination of mitigation priorities can be made by just examining the cluster pattern generated. Cluster 2 should be given the highest priority, followed by cluster 3, and lastly cluster 3.
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