<![CDATA[As it is known that one of the tasks of the Financing field is to analyze customer data in a cooperative to find out which customers have the potential to be able to do credit again. The method that can be used to analyze existing customer data is by classifying all customers who have made or completed their financing installments into subsequent marketing targets. That is why this research was conducted to help resolve the above problems by designing a data mining application that can serve to predict the criteria of loan fund customers who have the potential to borrow funds back to the BMT 071. Financing Section of BMT 071 located in Central Kalimantan, Regency Kotawaringin Timur is a place chosen by researchers as a case study, assuming the BMT 071 Financing Section has experienced problems as explained above. Therefore, the authors use data mining techniques that are applied to the application to be built is the Decision Tree classification technique. As for the algorithm used as a helper algorithm to form a decision tree is the C4.5 Algorithm. For the dataset processed in this study is the installment data for BMT 071 financing customers from August 2018 to March 2020 in Microsoft Excel format. The results of this study are a design application that can facilitate the Financing section of the BMT 071 in obtaining financing targets in the future]]>
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