The government realizes the importance of the problem of poverty by making various efforts, one of which is holding social assistance programs for the poor. One of the government policies is the Family Hope Program (PKH). The situation in the community indicates that those who receive PKH assistance from the government usually use the assistance to meet the health needs of their families, schools and daily needs, which are generally consumptive. The process of processing PKH beneficiary data in the Timbang Deli sub-district is still done manually, therefore this study aims to carry out data processing with the Naïve Bayes classification by creating a system to make it easier for officers in the Timbang Deli sub-district to determine PKH beneficiaries. The method used in this study is the Naive Bayes classification method. The variables used in this study were the head of the family, number of dependents, occupation, income, number of cars, number of motorcycles, status of residence, and condition of the house. The data in this study were 100 data from PKH beneficiaries and non-recipients of Timbang Deli Village, 80 as training data, and 20 as testing data. Based on the results of a study of 20 test data for recipients and non-recipients of PKH assistance in Timbang Deli Village, Medan Amplas District, the accuracy of the truth is 80% where there are 16 data that have values according to the test data, and 4 data that have values that do not match the test data.
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