Ontology-based Daily Menu Recommendation System for Complementary Food According to Nutritional Needs using Naïve Bayes and TOPSIS

Abstract

Babies begin to be given complementary feeding at the age of 6 to 24 months. Complementary foods given to babies need to meet nutritional needs according to their ages. Since, at these ages, babies are just learning to eat, it is necessary to plan a complementary food menu referring to the nutritional needs and the baby and mother's preferences. It is certainly not an easy thing for a mother. Therefore, a recommendation system is needed to determine the baby's daily menu according to those all. This research proposes a complementary food menu recommendation system that considers the balanced composition of three significant nutrients (carbohydrates, protein, and fat) in the diet. It also takes into account the baby and mother's preferences. The ontology contains Knowledge-based about food and its nutritional content and the nutritional needs of babies according to their ages. Naive Bayes is used to prepare menu options according to user preferences. TOPSIS method is used in this study to provide optimal recommendations regarding nutritional balance and user preferences. Several mothers who have had babies aged 6-24 months and mothers of babies aged 6-24 months were asked to test the recommendation system. The results of the usability testing of the system using SUS showed a good level of user satisfaction.