Adult Attention Deficit Hyperactivity Disorder Risk Detection Using Forward Chaining Method - Ahsani, Ghania Sabrina; Esi Putri Silmina (International Journal of Informatics and Computation, 2025)
Adult Attention Deficit Hyperactivity Disorder (ADHD) remains underrecognized due to subtle symptoms, persistent misconceptions, and limited access to self-screening tools. This study developed a robust expert system to support the early detection of ADHD risk using the Forward Chaining method. Knowledge acquisition was conducted through literature review and consultation with a psychologist specializing in ADHD to construct a rule-based knowledge base of symptoms and risk classifications. The system provided three possible outcomes: high, moderate, or no risk. Evaluation was carried out through black-box testing with ten respondents and accuracy testing against expert diagnoses. The results showed that the system achieved 100% functionality and 100% accuracy in identifying ADHD risk levels. This research contributes to addressing the gap in digital screening platforms for adult ADHD in Indonesia by providing an accessible and user-friendly tool for self-assessment. The system can be a substitute for an early detection aid to consultation and reduce delays in intervention.