<![CDATA[The savings and loan business in this current era is increasingly circulating in society, both online and offline or conventionally. There are also many companies that provide savings and loan services to their consumers or customers or are referred to as debtors who do not consider the ability of their customers to repay their loans. In fact, there are many algorithms that can be used to overcome or predict whether a debtor will be eligible to be given a loan or not. One of them is the k-nn algorithm, where this algorithm will later classify the basic variables of a debtor's assessment. However, the accuracy of the k-nn algorithm results differ in several existing cases. This time, in this study, the k-nn algorithm will find out how much accuracy it has using the k-fold Cross Validation if it is applied to the Debtor data sample at KSP Galih manunggal. The results of the k-fold cross validation will later be able to find out the average success of a system by repeating it by randomizing the input attributes so that the system is tested for several random input attributes.]]>
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