<![CDATA[The education sector is one of the fields that gets the most attention from the government, especially when graduating from high school students. It is expected that these graduates will continue to pursue higher education. Various information about majors in universities have been widely available but have not been able to meet the needs of prospective students. There are three main problems experienced by prospective students, namely limited knowledge of the majors to be followed, limited information available, and limited quantitative recommendations that can be used by prospective students.This study tries to overcome these problems by producing predictions of departmental recommendations using the Naive Bayes algorithm and incorporating criteria that influence the selection of majors in the form of abilities, interests, and also preferences for certain fields. An approach to user preferences is used so that the recommendations approach the desired results. This is done by giving the criteria weighting to the user. Keywords: Data Mining, Predictions, Universities, Naive Bayes]]>
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