<![CDATA[The application of Nave Bayes in Classifying Candidates for Non-Cash Food Assistance (BPNT) in Nanjung Mekar Village was made to solve problems in the process of distributing non-cash food assistance programs that have not run optimally and have not been targeted. The purpose of this research is to find out how to apply the Naïve Bayes Algorithm in Classifying Non-Cash Food Aid Recipients in Nanjung Mekar Village so as to obtain optimal results.The method used in this study is the nave Bayes classification method. The Naïve Bayes algorithm is proven to have good performance in a prediction, and produces high accuasy and AUC values. The stages of data analysis were carried out based on the CRISP-DM method while the algorithm testing was carried out on the RapidMiner 9.10.001 software as a comparison between manual calculations and software calculations. The results of these tests obtained an accuracy value of 80%, and an AUC value of 0.938 which was obtained from 250 data with the use of 240 training data and 10 testing data.]]>
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