<![CDATA[The low interest of students at the Hidayaturrohman Teluknaga Foundation to continue their education from MTs Hidayaturrohman to Hiro High School makes it necessary to look for the factors causing this lack of interest. This study aims to combine the application of advanced study predictions of students using the naïve Bayes method and the application of ranking with the weighted product method. The data for this research object are graduates of MTs Hidayaturohman in 2022. The research sample is 322 data. The data collection method is in the form of secondary data, namely students graduating from MTs Hidayaturrohman in 2022. The attributes used to assess factors for graduates of MTs Hidayaturrohman to continue their studies at Hiro High School consist of 5 attributes, namely hobbies, modes of transportation, parents' income, distance from home to school and school test scores. In the study, 322 data were divided by 85% (273 data) for training data and 15% (49 data) for testing data. The results showed that the Naïve Bayes method could be applied in predicting the further study of students from MTs Hidayaturrohman to Hiro High School. This is evidenced by the accuracy test using the confusion matrix with an accuracy value of 71%. Where from 49 testing data it is predicted that 34 data with advanced results and 15 data with moving results. Furthermore, data ranking using a weighted product was carried out on 316 data, where 50% of the data (158 data) with the highest vector value v entered advanced ranking and the rest entered moving ranking. The 50% figure is in accordance with the expectations of Hiro High School, namely that as many as 50% of MTs Hidayaturrohman graduates continue on to Hiro High School. Then the highest vector v value is 0.005945284 for parent number 19207207 and the lowest vector v value is 0.001552376 for parent number 19207219.]]>
