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

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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Publication Details

Journal
Indonesian Journal of Interdisciplinary Research in Science and Technology
Published
2025-02-28
DOI
https://doi.org/10.55927/marcopolo.v3i2.7
Primary Topic
Sports and Physical Education Research
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Gavin P. Salam, Hermansyah Sembiring, Hotler Manurung
Indonesian Journal of Interdisciplinary Research in Science and Technology
Sports and Physical Education Research
article

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

Gavin P. Salam, Hermansyah Sembiring, Hotler Manurung
article en

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.

Indonesian Journal of Interdisciplinary Research in Science and TechnologyVol. 3(2)
Kootenay Association for Science & Technology (CA)
Openalex Percentile: Top 94%
Sports and Physical Education Research
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KNN Algorithm Prediction of the Influence of Learning Interest on Free Fire Game Addiction in Elementary School Students 020259 — Gavin P. Salam, Hermansyah Sembiring, et al. · Indonesian Journal of Interdisciplinary Research in Science and Technology (2025) | TGRS Research Map | TGRS