Web application to measure level of addictive game
Abstract
Game becomes very popular within all ages. The intensity of someone playing games can influence the behavior of that person. World Health Organization (WHO) is classifying gaming disorder as an addictive behavior disorder. According to psychologists, there are six types of game addiction behavior, such as, Salience, Euphoria, Conflict, Tolerance, Withdrawal, and the last is Relapse and Reinstatement. A person is said to be addicted to the game if it meets at least three of the six types of behavior that exist. The six types of game addiction behavior then modeled using backward chaining algorithm. After that, the model was implemented into the system. Thus this research re-sult a web application to identify game addiction. Now we can measure how many people are affected using this web application.
About this article
Keywords
- Web Application
- Game Addiction
- Backward Chaining
- Algorithm.
References
[1] C. Green, and D. Bavelier, The cognitive neuroscience of video game. Digital Media: Transformations in Human Communication. Messaris & Humphreys, Eds, 2004.
[2] A.Latubessy and M.N.Ahsin, “Hubungan Antara Adiksi Game Terhadap Keaktifan Pembelajaran Anak Usia 9-11 Tahun”, Jurnal Simetris, vol.7, no.2, pp.687-692, 2016. https://doi.org/10.24176/simet.v7i2.782.
[3] A.Latubessy and E.Wijayanti, “Model Identifikasi Kecanduan Game Menggunakan Backward Chaining”, Jurnal Simetris, vol.8, no.1, pp. 9-14, 2017. https://doi.org/10.24176/simet.v8i1.807
[4] N. Saquib, etc, “Video game addiction and psychological distress among expatriate adolescents in Saudi Arabia”, Addictive Behaviors Reports, December 2017, Vol.6 pp. 112-117. https://doi.org/10.1016/j.abrep.2017.09.003.
[5] O. Lefebvre, “The governance of Internet and game theory“, International Journal of Engineering & Technology, 2018, 7(2.28), doi 10.14419/ijet.v7i2.28.12906.
[6] R. Maskeliūnas, etc, “IDO:modeling a serious educational game based on hands on approach for training dementia Carers”, International Journal of Engineering & Technology, 2018, 7(2.28), doi : 10.14419/ijet.v7i2.28.12898.
[7] A. Latubessy, and A. Jazuli, "Analisis Model Penelusuran Backward Chaining dalam Mendeteksi Tingkat Kecanduan Game pada Anak", Jurnal Teknologi dan Sistem Komputer, Okt 2017, vol. 5, no. 4, pp. 129-134 doi: 10.14710/jtsiskom.5.4.2017.129-134, [Online]. https://doi.org/10.14710/jtsiskom.5.4.2017.129-134.
[8] R.Fiati and A.Latubessy, 2016. ”Mapping of Flooded Areas in the Kudus District”. Indonesian Journal of Electrical Engineering and Computer Science, 2016, 4(3). doi: http://dx.doi.org/10.11591/ijeecs.v4.i3.pp. 670-677.
[9] B.Yudistira, I.K.G.D. Putra and A.A.K.O. Sudana, “Sketching Expert System for Crime Investigation Purposes”. Indonesian Journal of Electrical Engineering and Computer Science. 2014 12(7): 5655-5660. https://doi.org/10.11591/telkomnika.v12i7.5726.
[10] S.N.Arif, “Implementasi Rule-Based Expert System Dalam Mendeteksi Kerusakan Sistem Jaringan Komputer Dengan Metode Backward Chaining”. Jurnal SAINTIKOM.2011; 10(2): 81-93.
uter Dengan Metode Backward Chaining”. Jurnal SAINTIKOM.2011; 10(2): 81-93.