<![CDATA[With the enactment of the Law of the Republic of Indonesia Number 13 of 2011 concerning the Poor, there are ministries/institutions that carry out poverty reduction programs such as the Ministry of Social Affairs. The Ministry of Social Affairs is required to play a role so that efforts to reduce poverty in Indonesia can improve comprehensive social protection, namely regarding the fulfillment of the basic rights of all people as an opportunity for the poor to be able to invest in increasing family capacity in economic growth. Poverty can become a serious threat in the future if it is not thought about. Of the 100 datasets processed, 75 data received assistance consisting of monthly income of 1,000,000 – 3,000,000 and < 3,000,000 and there were 5 wealthy citizens who registered social assistance and monthly income > 3,000,000 with a total of 25 residents who did not receive help. One way to assist the application of determining the eligibility of social assistance for the poor and the needy is to use the Naïve Bayes algorithm method. In this study, the classification of Naïve Bayes and Microsoft Excel will be used. This research method uses business understanding, data understanding, data preparation, modeling stage, evaluation and deployment. After testing the naïve Bayes classification model, the Accuracy value in this model is 100%, Sensitivity value is 100%, Specificity value is 80%, PPV value is 100%, NPV value is 100%.]]>
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