<![CDATA[Each year the University offers many types of scholarships to its students, not least Amikom University Yogyakarta also offers the kind of underprivileged scholarships (PPA) for students in need. Each year the number of scholarship recipients continues to increase, but the amount received annually remains. Thus, it is necessary to develop a system to perform data mining from the data stack that will be used for certain purposes, one of which is to analyze the eligibility of the scholarship recipients to be on target. The Naive Bayes Classifier is an approach that refers to the Bayes theorem that combines previous knowledge with new knowledge. So it is one of the classification algorithm which is simple but has high accuracy. Therefore, in this study will be proved the ability of Naive Bayes Classifier to classify the data of scholarship applicants who inform the feasibility of awarding PPA scholarship. The scholarship data of the scholarship is done preprocessing, so that the data becomes "clean", so it is feasible to do the next process. Then the preprocessing is classified with the Naive Bayes Classifier, resulting in a classification probability model for the class determination of the next scholarship applicants. From the results of model accuracy testing of the developed system, yielding the smallest accuracy value of 64% on testing with a sample of 100 data and resulted in the highest accuracy of 97.66% in the test with a sample of 386 data]]>
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