<![CDATA[The method of selecting candidates for basic foodstuff recipients who still uses conventional methods is that in terms of data storage it is still in paper form, this will certainly have an impact on processing, storing, and searching for stored data if it is matched with newly obtained information or guidelines. This study conducted data processing using data mining to classify the eligibility of recipients and non-recipients of basic food assistance with the classification method using the Naïve Bayes Algorithm. It is hoped that the data generated from the data mining process can be used as evaluation material for the government. In addition, to prevent beneficiaries who often do not refer to the criteria of poor families and cheating by certain parties, a system is needed that can predict the appropriateness of food receipts that can provide alternative decisions and reduce the level of cheating in the selection of basic food recipients.]]>
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