<![CDATA[The scholarship acceptance process at one of the universities in Jakarta is based on several criteria, including the distance from the residence to the campus, active organizations, participating in UKM, GPA, having parents or guardians, parents' or guardians' jobs, income level, number of family dependents, ownership of a residence. In 2020, there were 1000 students who registered with various majors, so the scholarship selection team had difficulty in determining the scholarship acceptance selection quickly and accurately. In addition, subjective selection determinations were still found so that they were not on target and caused errors in determining policies to increase. Recording and determining scholarship acceptance were still done manually, namely via Excel. By entering detailed data on scholarship applicants and then calculating the value of each criterion met by scholarship applicants, this process is very complicated in processing scholarship determination. With this problem, research was carried out with data mining, using a PSO-based decision tree algorithm model with a PSO-based naïve bayes algorithm. By comparing the accuracy results of the two models, the highest accuracy was obtained with the PSO-based decision tree algorithm model. Furthermore, designing a web-based Decision support system for scholarship selection.]]>
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