KNN Algorithm Prediction of the Influence of Learning Interest on Free Fire Game Addiction in Elementary School Students 020259

Ginda Salam; Hotler Manurung; Hermansyah Sembiring

doi:10.55927/marcopolo.v3i2.7

Authors

Ginda Salam STMIK Kaputama Binjai, Teknik Informatika
Hotler Manurung STMIK Kaputama Binjai, Teknik Informatika
Hermansyah Sembiring STMIK Kaputama Binjai, Teknik Informatika

DOI:

https://doi.org/10.55927/marcopolo.v3i2.7

Keywords:

Game Addiction, Interest in Learning, K-Nearest Neighbor, Free Fire

Abstract

Online games are increasingly popular with various groups, including elementary school children. One of the popular games is Free Fire. However, addiction to playing games can have an impact on students' interest in learning. This study aims to group students based on the level of addiction to playing the Free Fire game and its impact on interest in learning using the K-Nearest Neighbor (KNN) method. The data used are data from students of Elementary School 020259. The KNN method is used to perform classification by calculating the Euclidean distance between training data and testing data. The results of the study show that the KNN method is able to classify students with fairly high accuracy, so it can be used as a tool in identifying students who experience a decrease in interest in learning due to game addiction.

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