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All Journal Al'Adzkiya International of Computer Science and Information Technology Journal
Evansyah, Muhammad
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Computer Science & IT

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Expert System for Diagnosing Autism Spectrum Disorder (ASD) in Children Using the Forward Chaining Method (Case Study of the Bina Ananda Mandiri Foundation) Evansyah, Muhammad
Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 1 (2025)
Publisher : Al'Adzkiya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55311/aiocsit.v6i1.338

Abstract

Autism Spectrum Disorder (ASD), more commonly known as autism, is a neurological disorder that can affect a child's development. ASD is one of five types of disorders, including: Autistic Disorder (AD), Asperger Syndrome (AS), Childhood Disintegrative Disorder (CDD), Pervasive Developmental Disorder, and Rett Syndrome. At the Bina Ananda Mandiri Foundation, psychologists only visit once a year to diagnose ASD symptoms. With advancements in technology and various new innovations, the limitations of expert personnel and their knowledge can be addressed through technological progress. One step to address the shortage of experts is through the development of an expert system. The purpose of creating this expert system is to diagnose ASD and provide information and solutions to parents who have children with autism. The process in this expert system begins with data collection using the forward chaining method. The data is then processed according to established rules to generate conclusions as solutions to the problem. Developed using the PHP programming language, the ASD diagnosis expert system has been tested for accuracy using real-world case data with a value of 80%. The system effectively detects early signs of autism and presents the likelihood that a child may have autism.
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