Fuzzy Inference System for The Risks Pregnancy Detection

Abstract One of the causes of the high Maternal Mortality Rate (MMR) and Infant Mortality Rate (IMR) in Aceh is the delay in handling cases of at risk pregnancies due to the lack of availability of easily accessible and well-documented information about conditions during pregnancy. So far, manual reporting through data recapitulation report was difficult to access quickly if there are cases maternal and infant mortality. Fuzzy logic can be used as an alternative for classifying pregnant women at risk with supporting data when examining pregnant women. Data related to pregnancy checks will be analyzed with a Fuzzy Inference System (FIS) to obtain information on pregnancy risks. The results of this study indicate that FIS can determine the risk of pregnancy more detailed range than using a manual scoring card. The results of the defuzzyfication value will describe the final decision related to pregnancy risk which can be categorized into low risk, high risk and very high risk. The problem solving steps in this study can be used for algorithms in the development of application programming for risky pregnancy early detection systems based on programming languages. ​​