Implementation of the breadth-first search method on forward-chaining inferences to diagnose autism disorders in children

Authors

  • Dodi Nofri Yoliadi UIN Mahmud Yunus Batusangkar, West Sumatera, Indonesi

DOI:

https://doi.org/10.35335/cit.Vol15.2023.339.pp58-72

Keywords:

Expert system, Autism disorder, Diagnostics, Forward chaining

Abstract

Autism is a type of mental disorder that can affect children as young as three years old, but can affect children from birth. This mental disorder is characterized by social relationships, culture, verbal and non-verbal communication, imagination, and a single attractive object. By using the Autism Disorder Diagnostic Expert System, we hope that most people will be able to attempt an autism diagnosis without an expert. This system works by answering all system questions. The "forward chaining" method is a way of drawing conclusions that starts with facts and tests hypotheses toward conclusions. To test the hypothesis, begin matching facts or statements with IF. The forward chaining method searches for a solution to a problem. The forward chaining inference and breadth first search methods were used to design this system, as well as Microsoft Access for database management systems and Visual Basic Language Programming. The expected outcome is that all users, particularly parents, will be able to easily assess the possibility of their child developing autism symptoms from an early age. The output of the system is whether there is a possibility of autism in a child based on the facts and symptoms given to the system.

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Published

2023-05-31

How to Cite

Yoliadi, D. N. . (2023). Implementation of the breadth-first search method on forward-chaining inferences to diagnose autism disorders in children. Jurnal Teknik Informatika C.I.T Medicom, 15(2), 58–72. https://doi.org/10.35335/cit.Vol15.2023.339.pp58-72