<![CDATA[Village-Owned Enterprises (BUMDes) play a strategic role in promoting rural economic growth through the management ofbusiness units based on local potential. However, in practice, strategic decision-making in BUMDes management is oftenconducted conventionally and has not fully utilized available data. This study aims to examine the use of data mining as adecision support tool for strategic decision-making in BUMDes management. The research adopts a quantitative approach usingthe clustering method applied to BUMDes operational data, including revenue, number of transactions, and business operationalperiods. The research stages follow the Knowledge Discovery in Databases (KDD) process, consisting of data selection, datacleaning, data transformation, data mining implementation, and result evaluation. The findings indicate that the application of theclustering method successfully classifies BUMDes business units into several performance categories, providing objective andrelevant information to support managerial decision-making. Therefore, data mining can be effectively utilized as a strategicdecision support system in data-driven BUMDes management.]]>
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