<![CDATA[ABSTRACT This study aims to analyze the allocation of Village Funds in Bandung Regency in 2025 by integrating descriptive and predictive approaches through the roles of Data Analyst and Data Scientist. Official data from the Ministry of Finance (2025), covering all villages in Bandung Regency, served as the primary dataset. The descriptive approach focused on identifying distribution patterns, inter-village disparities, and differences in performance-based allocations. Meanwhile, the predictive approach employed clustering techniques to uncover hidden structures within the allocation patterns. The findings reveal that a portion of villages received performance-based allocations with a fixed value of IDR 396.180.329.000, which increased their total allocation by approximately 25% compared to villages without such allocations. Cluster analysis identified three main distribution patterns, reflecting variations in fiscal characteristics and village capacities. Geographic visualization further highlighted disparities across sub-districts, with certain areas receiving relatively higher allocations than others. These results underscore the importance of integrating descriptive and predictive analytics in public policy studies, particularly in the management of Village Funds. Practically, the study provides empirical evidence to support local governments in formulating allocation policies that are more transparent, equitable, and data-driven. Furthermore, the findings demonstrate the potential of data analytics to enhance fiscal governance at the village level, contributing to more effective and accountable resource distribution. Keywords: Village Funds, Performance Allocation, Descriptive Analysis, Clustering, West Java]]>
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