Implementation of A Fuzzy Logic for Early Detecting of A Pregnant Women Risk of Hypertension

Abstract

Hypertension is one of the diseases that can cause fatal effects to health, especially for pregnant women. Hypertension during pregnancy can cause serious effects such as pre-eclampsia and eclampsia which can threaten the lives of pregnant women and fetuses. The purpose of this study is to determine the input and output variables related to hypertension during pregnancy and used for analysis using Tsukamoto FIS to determine risk factors for hypertension in pregnant women. This study uses input variables in the form of maternal age, systolic blood pressure (SBP), diastolic blood pressure (DBP), history of hypertension and genetic. Furthermore, it is analyzed using fuzzy logic through the process of fuzzyfication, inference engine and defuzzyfication. The examination of data samples of pregnant women with systolic and diastolic blood pressure categories included in the high category or potentially have hypertension. The Z value (defuzzyfication) shows that the output is in the category of severe hypertension so that the patient needs immediate treatment by medical personnel. The results showed that the risk of a mother having hypertension can be obtained through Tsukamoto FIS in the form of concrete values that can describe risk factors in the form of normal, hypertension and severe hypertension as well as recommended actions related to these risk factors.