Recommendation System for Complementary Breastfeeding using Ontology Modelling and Naïve Bayes

Abstract Complementary breastfeeding is an additional food given to the baby started from six to 24 months. The giving of complementary foods is given gradually according to the age of the children and adapted to the condition of the children, such as allergies suffered or malnutrition suffered. This research aims to develop an ontology based decision support system that will help mothers in giving breastfeeding to their babies with keep regarding to their food preferences. This research successfully develops a content-based recommendation system by performing the Naïve Bayes Method and modified the existing ontology modelling and also develop a mobile application with the Android platform so that it can be more accessible to many people. Thirty-five users evaluated the system, and the result of the usability testing shows that the user satisfaction level using SUS (System Scale Usability) method is 79.57, which is in Grade A-. This grade indicates that the system can be well understood by the user and can help mothers in choosing breastfeeding recipes or menus.