doi: 10.18178/ijiet.2023.13.9.1945
Diagnosing Learning Disorders in Children: A Comparison of Certainty Factor and Dempster-Shafer Methods
Anthony Anggrawan*
,
Hairani Hairani ,
Christofer Satria ,
Aprillia Dwi Dayani
- Bumigora University, Indonesia
- Manuscript receivedNovember 23, 2022
- revisedFebruary 2, 2023
- acceptedMarch 17, 2023
Abstract
Even though educational technology is very advanced, some children experience learning disorders. Learning disorders in children include Dyslexia, Dysgraphia, Dyscalculia, and Dyspraxia. Ignorance about learning disorders in children will result in the child not getting help to reach his potential and have an impact on problematic behavior and destructive mental disorders in children. That is why it is necessary to make an early diagnosis to determine the presence of learning disorders in children. Therefore, for this reason, this study aims to develop an expert system for the early diagnosis of learning disorders in children using the Certainty Factor and Dempster-Shafer methods. The results show that the Certainty Factor method is more accurate than the Dempster-Shafer method in diagnosing children with disorders. The accuracy of the test results by diagnosing children’s learning disorders using the Certainty Factor method is 90%, and by the Dempster-Shafer method, it is 87%. The novelty of this research is to build a system for diagnosing the types of learning disorders in children using the Certainty Factor and Dempster-Shafer methods which have never been done by previous researchers.
Keywords
- Educational technology
- learning disorder
- children learning
- certainty factor
- dempster-shafer
How to Cite
Anthony Anggrawan, Hairani Hairani, Christofer Satria, and Aprillia Dwi Dayani, "Diagnosing Learning Disorders in Children: A Comparison of Certainty Factor and Dempster-Shafer Methods," International Journal of Information and Education Technology, vol. 13, no. 9, pp. 1422-1429, 2023. https://doi.org/10.18178/ijiet.2023.13.9.1945
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).