<![CDATA[Auction data is very important data for companies that are particularly engaged in credit distribution services. In this company, there is also an auction activity in which goods that have been pawned but have expired credit payments, the goods will be auctioned in general by the company. A large amount of existing customer auction data causes employees to experience several problems in managing large amounts of data and it is difficult to obtain accurate information in grouping auction data according to the amount of money borrowed. This application can help employees to obtain information in the method of grouping auction data by applying K-Means Clustering and can be better selected based on predetermined criteria. Testing the application for grouping the K-Means Clustering method using RapidMiner gave results based on 17 customer data types of Small loans, 5 Medium loan types, and 2 customer data on Large loan types.]]>
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