Addictive Detection of Gadgets Using Artificial Intelligence

The purpose of this study was to discover the addictive influence of gadgets on the emotional and social intelligence of elementary school students. This type of research is a survey, with a quantitative approach to correlational models. The sample of this study was 150 students from 4 elementary schools in Bantul. Data collection techniques through questionnaires using the P-KES-SD application. Data analysis using descriptive statistics and linear regression. The results of the study showed that: (1) The addictive level of student gadgets belongs to a high category on the aspect of having an effect on the physical. (2) The emotional and social intelligence of students is high in the psychomotor aspect, and the lowest in the cognitive aspect, this indicates a lack of understanding of the student's reasons for doing good deeds. (3) There is an addictive influence of gadgets on the emotional and social intelligence of Islamic elementary school students with a coefficient of determination (R Square) of 19.7% and the remaining 80.3% is influenced by other factors. This proves that artificial intelligent is able to detect addictive gadgets of elementary school students.