The Classification of “Program Sembako” recipients in Payobasung West Sumatra based on the K-nearest neighbors classifier

Abstract

The "Sembako Program" is a program carried out by the Indonesian government to improve the welfare of low-income communities. The purposes of this study are: (a) to determine the classification of households that deserve to receive basic-food assistance in Koto Panjang Payobasung, West Sumatra, using the KNN classifier and (b) to determine the optimal number of nearest neighbors used in the classification process. The measure of proximity between objects used is the Gower dissimilarity coefficient. This research used primary data consisting of 175 households collected purposively in a survey conducted on all households in Payobasung.  The optimal K value is determined by implementing a 5-fold cross-validation procedure. The result showed that the best classification process is when K = 3 nearest neighbors are used since it produces the highest accuracy coefficient and Mattews correlation coefficient (MCC). Therefore, for further work, in deciding the eligibility of a household to receive the Sembako Program in Payobasung, KNN can be used by considering its 3 nearest neighbors