Nia Kumaladewi
Syarif Hidayatullah State Islamic University

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Development of an Expert System for Diagnosing Toddler Nutritional Status Using a Participatory Design Approach Wiwin Susanty; Dika Hastanto; Dian Resha Agustina; Nia Kumaladewi; Taqwan Thamrin; Tia Tanjung; Asep Trisna Setiawan
Applied Information System and Management (AISM) Vol. 9 No. 2 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i2.52355

Abstract

Assessing the nutritional status of a toddler remains an essential challenge for child health, since the process often requires professional expertise and may not always be readily available to the community. This work presents a web-based expert system to assist in assessing toddler nutritional status by combining the Certainty Factor method with the Participatory Design methodology. Nutritionists, Posyandu (Integrated Health Post) cadres, and parents of toddlers were actively involved in the development process, from identifying user requirements to designing the system to evaluating its functionality. The knowledge base consisted of 24 symptoms and six categories of nutritional status, representing expert knowledge, and the Certainty Factor approach was used to address the uncertainty in the diagnostic procedure. The resulting system offers integrated capabilities for Z-Score calculation, symptom-based consultation, nutritional status diagnosis, and follow-up suggestions. The diagnostic validation was performed on 30 selected toddler records and showed promising performance with 88.30% accuracy, 89.98% precision, 88.30% recall, and 87.08% F1-score. Moreover, the usability test conducted with 50 respondents yielded an average System Usability Scale (SUS) score of 79.15, which falls within the Acceptable category, namely Grade B or Good adjective rating. The results of this study show that the proposed system can efficiently enable early diagnosis of children's nutritional status while offering a user-friendly experience and high user approval.