UKT (Single Tuition) Classification Prediction uses MKNN (K-Nearest Neighbor Modification) algorithm

Abstract

Islamic University of Sultan Syarif Kasim (UIN SUSKA) Riau Province has used an information system, namely the Sistem Registrasi (SIREG) to facilitate the registration of prospective students and also SIREG also provides a decision on determining the UKT of students who have been declared graduated. But there has never been an evaluation of SIREG's accuracy in determining the UKT. From these problems, a model is needed to be implemented to facilitate SIREG officers in conducting classifications to establish UKT new students. Using the MKNN method and supported by the K-Fold Cross Validation validation method, the classification results get an accuracy value of 71%