A Knowledge-based Model of Expert System to Assist Exclusive Breastfeeding Mother

Exclusive breastfeeding is crucial in the early newborn nutrition fulfillment with many benefits such as preventing mental and behavioral disorders, supporting brain development and intelligence, and providing more than 100 enzymes. In this study, we develop a knowledge-based model which can assist exclusive breastfeeding mother against clinical finding found during the first six months period. The model takes the information of experienced symptoms/conditions (in both the mother and the newborn), gives the calculation of certain clinical finding's risk factor based on Certainty Factor (CF) given, and gives recommendation of follow up to the user. Therefore, the newborn's mother can monitor their health condition and use this model as a precaution to get health assistance as soon as possible through health service providers in her surroundings. The knowledge base and its CF are built from domain experts knowledge acquisition and Indonesian related health literature. The model is evaluated based on 25 different random trials against experts' assessment. The precision from this evaluation reaches 88% by taking given symptom/condition only, which shows that the developed model performs very well in detecting clinical finding through CF-based risk factor calculation. However, in the end of this paper we also point out the way to increase higher precision to close to perfection by drilling the information of symptom/condition given.