The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus

Research Article

Clustering Model to Measuring Level of Game Addiction

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  • @INPROCEEDINGS{10.4108/eai.24-10-2018.2280618,
        author={Anastasya Latubessy and Ratih Nindyasari and Alif Catur Murti and Aditya Akbar Riadi and Tutik Khotimah},
        title={Clustering Model to Measuring Level of Game Addiction},
        proceedings={The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus},
        publisher={EAI},
        proceedings_a={ICCSET},
        year={2018},
        month={11},
        keywords={addiction clustering game},
        doi={10.4108/eai.24-10-2018.2280618}
    }
    
  • Anastasya Latubessy
    Ratih Nindyasari
    Alif Catur Murti
    Aditya Akbar Riadi
    Tutik Khotimah
    Year: 2018
    Clustering Model to Measuring Level of Game Addiction
    ICCSET
    EAI
    DOI: 10.4108/eai.24-10-2018.2280618
Anastasya Latubessy1,*, Ratih Nindyasari1, Alif Catur Murti1, Aditya Akbar Riadi1, Tutik Khotimah1
  • 1: Universitas Muria Kudus
*Contact email: anastasya.latubessy@umk.ac.id

Abstract

World Health Organization (WHO) has issued a statement that addiction to the game is one of the mental disorders. Playing games favored by various age groups. Adults and children love to play games. Excessive game play patterns can lead to addiction to games. Actually, the rate of addiction to games can be measured. One way of measuring the level of game addiction is to classify the symptoms of this type of game addiction behavior. There are six types of game addiction behavior that have been obtained from previous research. Those symptoms can be grouped using one of the clustering methods. This study uses K-Means Clustering to categorize the rate of game addiction.