<![CDATA[The Blood Donation Unit (UDD) of PMI Kota Jambi plays an important role in maintaining the availability of safe and eligible blood supplies. One of the challenges faced is that the determination of donor eligibility is still carried out manually and relies heavily on medical staff examinations, which may lead to inefficiency and delays in service. Therefore, a predictive model is needed to assist in determining donor eligibility more quickly and objectively.This study aims to apply data mining techniques using the Naïve Bayes algorithm to predict the eligibility of blood donors at UDD PMI Kota Jambi. The data used consist of historical donor records, including attributes such as age, gender, body weight, blood pressure, hemoglobin level, and donor history.]]>
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