<![CDATA[Along with the rapid development of information technology today, the cost to meet the needs of life increasingly high, this is triggered by the amount of budget issued by the government to solve economic problems in Indonesia, especially in terms of National Welfare Guarantee. Kartu Indonesia Sehat is a card issued by the government and managed by the Badan Penyelenggara Jaminan Sosial (BPJS) to alleviate the poor for health. Existing problems such as in the distribution of the card has not been on target because of the amount of data obtained so highly possible error happens in determining the recipient of Kartu Indonesia Sehat. The concept of data mining is considered to solve the problems faced in determining the recipient community or not the recipient of Kartu Indonesia Sehat. Classification methods are able to find models that distinguish the concepts or data classes, with the spesific goal of determining the class of an unknown object label. Therefore, the Naïve Bayes algorithm could predict future opportunities based on prior experience by considering some variables such as age, last education, occupation, monthly income and dependents of children that will determine the final outcome of a decision. The result of this research is a system that will predict the people who will receive Kartu Indonesia Sehat so that the government will distribute the card accurately to the public and the acquired results from the test obtained an average accuracy rate of 94.78%, 98.86% precision and 90.98% recall.DOI: https://doi.org/10.26905/jtmi.v4i1.1870]]>
