SISTEM PAKAR DIAGNOSIS KECANDUAN GAME (GAMING ADDICTION) PADA REMAJA MENGGUNAKAN METODE DEMPSTER SHAFER

SYARIFAH, SUCI RIYANI (2019) SISTEM PAKAR DIAGNOSIS KECANDUAN GAME (GAMING ADDICTION) PADA REMAJA MENGGUNAKAN METODE DEMPSTER SHAFER. Undergraduate Thesis thesis, Institut Telkom Purwokerto.

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Abstract

ABSTRACT Gaming addiction is characterized by impaired control (cannot reduce) game play activities, as well as increased priority given to games more than other activities. Currently there have been many cases due to addiction to games such as cases of death, and criminal cases. Data on the number of gamers in Indonesia in 2017 according to marketing research institute from Amsterdam, Newzoo, there are 43.7 million gamers (56% of them are men with an estimated prevalence of 6.1% of game players experiencing addiction, so it can be estimated that there are currently 2 7 million game players might be addicted, and the number of psychologists is not proportional to the number of adolescents diagnosed so there is a need for an expert system that can help an expert diagnose game addiction.This study uses the Dempster Shafer method to determine the level of addiction the game experienced by users is mild, moderate and severe levels along with suggestions for handling (solutions) for each level.The author tests the accuracy of users who have filled symptoms on the IGDS9-SF form with the results on the expert addiction diagnosis system expert website. 50 user data that quite often play games where the accuracy results obtained are seb 90%. This shows that the Dempster Shafer method can be used in expert game addiction diagnosis systems well. Keywords: Dempster Shafer, Expert System, Game, Gaming Addiction, IGDS9-SF

Item Type: Thesis (Undergraduate Thesis)
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Informatics > Informatics Engineering
Depositing User: Users 218 not found.
Date Deposited: 05 Jun 2020 19:11
Last Modified: 06 Nov 2024 03:45
URI: http://repository.ittelkom-pwt.ac.id/id/eprint/5681

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