Indonesia
DOI:
https://doi.org/10.33379/gtech.v8i2.4240Keywords:
IndonesiaAbstract
This study aims to apply the K-Nearest Neighbors (KNN) method in determining the category of recipients of direct cash assistance in Ketowan village, Arjasa district, Situbondo regency. From the data set consisting of 50 entries, 34 entries were deemed eligible for assistance, while 16 other entries were deemed unfit. Researchers used six criteria to assess eligibility for receiving assistance, including housing conditions, income, employment, number of dependents, recent education, and status. The process of implementing the KNN method resulted in the parameter value K=5, with 38 data considered feasible and 12 data considered ineligible. This method is expected to help decision making in the allocation of village funds to minimize data errors and improve the effectiveness of social assistance programs at the village level.
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