A Combination of Forward Chaining and Certainty Factor Methods in a Child Mental Health Expert System with Accuracy Comparison Using the Strengths and Difficulties Questionnaire

Thomas Ryantama; Chairani

Authors

Thomas Ryantama Institut Informatika dan Bisnis Darmajaya (IIB Darmajaya), Lampung, Indonesia
Chairani Institut Informatika dan Bisnis Darmajaya (IIB Darmajaya), Lampung, Indonesia

Keywords:

Expert System, Child Mental Health, Strengths and Difficulties Questionnaire (SDQ) , Forward Chaining, Certainty Factor, Classification

Abstract

The increasing complexity of child mental health issues requires accurate detection and intelligent decision-support systems for early identification and intervention. This study analyses emotional and behavioural difficulties among 500 children aged 11–17 years using the Strengths and Difficulties Questionnaire (SDQ) dataset and develops an expert system integrating Forward Chaining and Certainty Factor methods. Results indicate that most respondents had relatively low difficulty levels across SDQ dimensions, although substantial proportions showed high Emotional Symptoms and Conduct Problems scores, suggesting potential psychological concerns. The proposed expert system achieved 90% accuracy, demonstrating good performance in distinguishing Normal and Abnormal categories, although classification of the Borderline category remained challenging. Higher scores in Emotional Symptoms, Conduct Problems, Hyperactivity, and Peer Problems, alongside lower Prosocial Behaviour scores, were associated with greater likelihood of Borderline or Abnormal classification. These findings demonstrate that integrating Forward Chaining and Certainty Factor can effectively support early screening and decision-making in child mental health assessment.

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