Rule-Based Expert System for Meal Recommendation in Malnourished Children

Malnutrition remains a critical public health issue, especially among children in developing countries, due to limited access to nutritional knowledge and appropriate meal planning. A web-based rule-based expert system is proposed in this research to help carers create individualized meal plans for malnourished children. After analyzing input factors including age, gender, height, weight, and dietary preferences using rule-based reasoning, the system suggests meals that are suitable for the child's daily calories and nutritional requirements. The system, which was created using the Waterfall Model, uses evidence-based recipes from Volumes I and II of the Nutritionists' Choice Cookbook and incorporates Flask for backend processing and MySQL for data administration. The output of the system guarantees nutritional accuracy and relevance by conforming to Malaysia's Dietary Guidelines for Children and Adolescents. Its usefulness and efficacy in assisting carers were validated by expert validation and functionality testing. In the future, the system can be improved by incorporating expert feedback to improve the knowledge base, putting strong data protection measures in place based on international standards like the General Data Protection Regulation (GDPR), and adding a progress-tracking component to track children's nutritional development over time.