Disasters pose significant challenges for communities worldwide, including Indonesia, which is vulnerable to both natural and human-made disasters. This study analyzes the clustering of disaster points in Indonesia for the year 2023 using the Agglomerative Hierarchical Clustering (AHC) method with data from the National Disaster Management Agency (BNPB). The data encompasses various types of disasters, such as earthquakes, hydrometeorological events, and volcanic eruptions, as well as variables related to casualties and infrastructure damage. The AHC method involves data preprocessing, calculating distances using Euclidean distance, and applying average linkage within AHC. The results identify four clusters: C1 (2497 members), C2 (1 members), C3 (1 member), and C4 (1 member), with a Silhouette Coefficient value of 0.983. This research is expected to provide valuable information for designing more efficient disaster management strategies.
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