<![CDATA[Earthquakes are among the most frequent and damaging natural disasters in Indonesia, particularly in West Java Province, where their unpredictable occurrence often causes casualties and severe infrastructure damage. This study aims to identify spatial and temporal patterns of earthquakes to support disaster risk mitigation efforts. A quantitative exploratory approach was applied using the Spatio-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN) method, which groups earthquake events based on their proximity in space and time while distinguishing random noise. The analysis utilized secondary earthquake data from the Meteorology, Climatology, and Geophysics Agency (BMKG) covering the period January 2022 to December 2023. The results revealed eight distinct clusters and several high-risk zones with strong internal similarity (silhouette coefficient = 0.721), indicating stable and stationary patterns over the observed period. These findings demonstrate that ST-DBSCAN is effective in detecting consistent earthquake-prone areas. More importantly, the study provides practical implications for disaster mitigation, including the development of targeted early warning systems, prioritization of high-risk areas such as Cianjur Regency, and more efficient allocation of resources to strengthen preparedness and community safety.]]>
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