Performance Analysis Of The K-Means Algorithm On Intensity Of Science Laboratory Use And Science Skills - Yati, Nurhayati; Simatupang, Baharis Setia Adisahputra; Arisman (Bahasa Indonesia, 2024)
This research aims to analyze the performance of the K-Means algorithm concerning the intensity of use of the Natural Sciences (IPA) laboratory and its impact on students' science skills. The study utilizes data on the intensity of science laboratory use and the results of science skills tests from a group of students. The analysis leverages the K-Means algorithm's ability to cluster students based on their laboratory use patterns and determine qualifications based on their science skills. The performance metrics employed in this study include evaluating cluster suitability and conducting correlation analysis between science laboratory use patterns and students' science skills. Therefore, the research focuses on demonstrating how the K-Means algorithm can effectively group data on the intensity of science laboratory use and its correlation with students' science skills.