Abstract:
This study aims to predict the academic achievement of FMIPA Riau University students
using the K-Nearest Neighbor algorithm. The results of the predictions are achievement in
terms of the category of cumulative grade point average (IPK) "High" or "Low", this is
because new students cannot know their estimated future achievements, so with this
prediction system new students can see their achievement predictions. in the future (sixth
semester) by looking at the school of origin majors, the average national exam, college
motivation, and work at the beginning of college which can be used as a reference and
motivation for maximum achievement. The system is designed using the PHP programming
language and the database server uses MySQL and the system design uses UML. The
comparison of training data and test data is 70%: 30%. The results obtained from this study
get an average level of accuracy of 80%.
