Sistem Pakar Deteksi Dini Tingkat Kecanduan Gadget pada Anak Menggunakan Fuzzy Tsukamoto

Fernando Bayu Andika, A. Purnomo
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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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利用模糊塚本早期检测儿童小工具成瘾程度的专家系统
信息和通信技术不断发展和进步,小工具技术的出现就证明了这一点。小工具是智能电子设备,可以帮助用户轻松完成各种任务。儿童对小工具技术的使用与此密不可分。根据 2020 年 KPAI 的调查,约 71.3% 的学龄儿童拥有并较长时间玩过小工具。因此,希望能及早发现使用小工具成瘾的儿童,以确保使用小工具的儿童的精神和情绪障碍能得到妥善解决。本研究的目的是创建一个专家系统原型,利用模糊塚本法早期检测儿童的小工具成瘾程度。本研究采用了模糊塚本法。本研究包括 74 名 9 至 12 岁的受访者。本研究使用 DAS(儿童数字成瘾量表)作为数据收集方法。通过比较专家计算和模糊塚本法计算的结果,使用 74 名受访者的数据对系统的性能进行评估。模糊塚本推理使用了 64 个规则库来构建该专家系统。根据对 74 名受访者数据的评估,该专家系统的系统成功率为 87.83%,表明该系统运行成功。
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