Sistem Pakar Untuk Menentukan Tingkat Risiko Ibu Hamil Pada Klinik Bersalin Pratama Umi Rahma Menggunakan Metode Forward Chaining

Abstract

Umi Rahma Maternity Clinic which provides pregnancy and childbirth examination services. Eclampsia ranks second in causes of maternal death. Preeclampsia diagnosis, which is a precursor to eclampsia, needs to be implemented to reduce maternal and child mortality rates. The aim of this research is to create an expert system for early diagnosis of preeclampsia in pregnant women using the Forward Chaining method. Research methodology stages include literature study, observation, interviews, data collection, primary and secondary. data preprocessing, database design, system design, analysis the calculation results. ,Gestational Age, Maternal Age, Edema. From the system output results, namely the diagnosis of mild preeclampsia and severe preeclampsia. The use of this expert system is web-based using the PHP programming language. To find out the accuracy of the system, a system evaluation was carried out by comparing the expert results with the system results on 10 testing data, and getting 1 result indicating an incorrect result and 9 correct results. Thus, the system accuracy percentage is 90%. So this research was carried out by creating an expert system which aims to make it easier to access information regarding the symptoms of preerclampsia in pregnant women and is able to provide knowledge to pregnant women online to make it more accurate. This research uses the extreme programming method in developing an expert system which will be built using the PHP and MySQL programming languages ​​as the database and using Unified Modeling Langueage (UML) modeling.