Sistem Pakar untuk Mendiagnosis Gangguan Mental pada Anak Menggunakan Metode Forward Chaining dan Certainty Factor

Expert System for Diagnosing Childhood Mental Disorders using Forward Chaining and Certainty Factor Method

Abstract

Mental health problems in children, such as stress, anxiety, or depression are real and these problems are as important as physical health problems, but many children do not get the care they need so an artificial intelligence technology such as an expert system can help diagnose the disorder mentally in children early. This research developed an expert system to diagnose mental disorders in children using the mobile-based Forward Chaining and Certainty Factor method that diagnoses 7 types of mental disorders in children from 46 symptoms obtained based on the knowledge of 3 experts. Based on the results of the black box testing states that the expert system that was built has had compatibility in terms of functionality. The results of the theoretical calculation test states that the calculation system of an expert diagnosis of a child's mental disorder is in accordance with the results of calculations done manually. In testing the accuracy of the system from 30 cases tested on 3 experts, the expert system that was built succeeded in producing system accuracy values ​​based on the final belief value of the three experts, based on the belief values ​​of experts 1, 2, and 3, respectively 91.11%, 96.67%, 96.67% and 80%. Furthermore, the results of MOS testing conducted on 35 respondents produce MOS of 4.12 from a scale of 5 where based on that value the expert system built is categorized into a good system.