<![CDATA[This study aims to identify the distribution patterns of Micro, Small, and Medium Enterprises (MSMEs) in Depok City using a spatial data-based clustering approach. The research problem is motivated by the uneven distribution of MSMEs across regions, which may affect the effectiveness of development and support program planning. This study employed a quantitative approach using data mining techniques through the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. The dataset consisted of secondary data from 50 MSMEs distributed across 11 districts in Depok City, with geographic coordinates (latitude and longitude) used as the primary variables. The clustering process was conducted using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm with the best parameters of ε = 0.60 and min_samples = 4. The results showed that the DBSCAN algorithm successfully generated four clusters and identified four data points as noise. Evaluation results using the Silhouette Score and Davies-Bouldin Index yielded values of 0.3171 and 0.6766, respectively, indicating a reasonably good clustering structure with relatively clear separation among clusters. Visualization through scatter plots and interactive maps revealed concentrations of MSME distribution in several areas of Depok City. The findings can be utilized as supporting information for decision-making and regional-based MSME development planning.]]>
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