<![CDATA[Government assets are essential components for supporting operational performance and public services. Over time, some assets depreciate and require removal to avoid unnecessary budget burdens. However, asset disposal processes in government institutions are often still manual and not data-driven, which can lead to inefficiencies. This study aims to apply the Apriori algorithm to discover asset disposal patterns in the Binjai City Government. The data used includes asset attributes such as Regional Government Organizations (OPD), Item Type, Age, Brand/Type, Material, and Acquisition Method. The method employed is data mining with the Apriori algorithm, and the analysis is supported by the RapidMiner tool. The results reveal strong associative patterns among specific asset attributes that tend to be disposed of, such as assets over 10 years old, made of synthetic materials, and acquired through purchase. Identifying these patterns facilitates more efficient, transparent, and objective decision-making in asset disposal. This research contributes to the development of data-driven asset management systems and supports bureaucratic reform in local government institutions. Keywords: Data Mining, Apriori Algorithm, Asset Disposal, Local Government, RapidMiner]]>
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