Abstract
Information and communication technology continues to develop and progress which demonstrated by the presence of gadget technology. Gadgets are smart electronic devices that assist in making it simple for users to accomplish various task. The use of gadget technology in children are unable to be separated. According to the 2020 KPAI survey, approximately 71,3% of school-age children own and have played with gadgets for a longer time. As a result, it is expected that early detection of gadget addiction can be carried out to ensure that mental and emotional disorders in children who use gadgets can be properly addressed. The aim of this research is to create a prototype expert system for early detection of gadget addiction levels in children using the fuzzy tsukamoto. The fuzzy tsukamoto method was used in this study. This study included 74 respondents aged 9 to 12 years old. The DAS (Digital Addiction Scale : For Children) was used as the data collection method in this study. The system’s as performance will be evaluated using 74 respondents data by comparing the result of expert calculations and fuzzy tsukamoto method calculations. Fuzzy Tsukamoto reasoning with 64 rule bases in used to build this expert system. According to evaluation with 74 respondent data, this expert system has a system acurracy rate of 87,83%, which indicates that it proceeds succesfully.
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