<![CDATA[The Indonesian Smart College Card Scholarship or KIP-K is one of the many scholarships provided by the government to continue their education to a higher level for students who excel but are constrained by costs. One of the universities in Garut that provides new student admissions through this scholarship route is the Garut Institute of Technology. Every year, the Garut Institute of Technology always experiences an increase in the number of KIP-K scholarship applicants, however this is not commensurate with the number of quotas obtained so a selection process must be carried out so that the scholarship can be right on target. The selection process itself is carried out manually without the help of a special system that can help select more precisely and efficiently. The aim of this research is to build a web-based prediction system application by applying the K-Nearest Neighbors classification model to help select prospective KIP-K scholarship recipients at the Garut Institute of Technology based on test scores, economic conditions, academic and non-academic achievements of each participant. The classification model is applied in the system as a process of classifying the eligibility of prospective recipients so that the selection process is more focused on participants who are categorized as eligible. The system was built using the waterfall approach method so that system development is more structured. This research produces an application in the form of a web-based prediction system that can help classify eligibility and select prospective KIP-K scholarship recipients at the Garut Institute of Technology with a system accuracy level in predicting participant eligibility of 91.86%.]]>
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