A Implementation of an Expert System for Diagnosing Attention Deficit Hyperactivity Disorder (ADHD) in Adults Using the Forward Chaining and Certainty Factor Methods Based on a Web Platform

IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA GANGGUAN ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD) PADA ORANG DEWASA MENGGUNAKAN METODE FORWARD CHAINNING DAN CERTAINTY FACTOR BERBASIS WEB (STUDI KASUS: MAHASISWA UNPAM)

Authors

  • Zidan Absar Abdallah universitas pamulang
  • Jaka Sutresna

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that may persist into adulthood, affecting concentration, impulse control, and daily activities. This research aims to develop a web-based expert system to assist in early screening of ADHD in adults, particularly students at Pamulang University, using the Forward Chaining and Certainty Factor methods. Forward Chaining is applied as an inference mechanism to determine ADHD type based on symptoms, while the Certainty Factor method calculates the confidence level of the diagnosis using expert and user certainty values. The results of Black Box Testing show that all system functions work properly and produce accurate initial diagnostic results. This system is expected to help increase awareness of mental health among students and serve as a digital-based early detection tool for ADHD.

Downloads

Published

2025-12-12

How to Cite

Abdallah, Z. A., & Sutresna, J. (2025). A Implementation of an Expert System for Diagnosing Attention Deficit Hyperactivity Disorder (ADHD) in Adults Using the Forward Chaining and Certainty Factor Methods Based on a Web Platform: IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA GANGGUAN ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD) PADA ORANG DEWASA MENGGUNAKAN METODE FORWARD CHAINNING DAN CERTAINTY FACTOR BERBASIS WEB (STUDI KASUS: MAHASISWA UNPAM). Journal of Artificial Intelligence and Innovative Applications (JOAIIA), 6(4), 82–94. Retrieved from https://openjournal.unpam.ac.id/index.php/JOAIIA/article/view/55147

Issue

Section

Articles