<![CDATA[Central Java Province stands as a pivotal agricultural region in Indonesia, characterized by high productivity in paddy and rice cultivation. However, substantial production disparities persist across districts, attributed to varying geographical conditions, agricultural infrastructure, and farmers' cropping patterns. Consequently, the identification of production clusters is imperative for elucidating production patterns and formulating targeted policy interventions. This study aims to classify districts in Central Java based on production metrics using the K-Means Clustering technique implemented in the R statistical environment. Production data across various regions were analyzed to determine optimal clustering patterns. The clustering analysis stratified the study area into four distinct agricultural typologies: optimal performance zones (Cluster 3, n=2), land-based volume producers (Cluster 1, n=7), small-scale efficient producers (Cluster 4, n=15), and priority intervention areas (Cluster 2, n=11). These findings underscore the necessity for differentiated policy strategies addressing the disparities in efficiency and production scales.]]>
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