Student Achievement Category with K-Means and K-Nearest Neighbors

Abstract

This study aims to categorize student achievements into high, medium, and low categories. The objective is to provide policyholders with references for decision-making purposes, including finding ways to improve student achievement and the facilities needed by students. The research was conducted on semester 1 students at the Muhammadiyah University of Cirebon in the academic year of 2022/2023. The data was collected by downloading score documents from the campus assessment system, followed by data preprocessing to remove outliers and normalize the data. The data processing was carried out using K-Means and K-NN techniques for better predictions. The AUC value obtained was 1.000, CA value was 0.992, F1 value was 0.992, precision value was 0.992, and recall was 0.962.

Keywords

• student achievement, k-means, knn