Web-Expert System for the Detection of Early Symptoms of the Disorder of Pregnancy Using A Forward Chaining and Bayesian Method
Hatta, Heliza Rahmania
Khairina, Dyna Marisa
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Web-Expert system (Web-ES) is used to recognize the symptoms early in women pregnancy disorders. Every pregnancy risk factors will endanger the safety of the mother and the baby, if the information obtained is less in the treatment of pregnancy disorder. This study aims to build web-based expert systems (ES), such as a doctor or a patient to diagnose pregnancy in any place, so it can help women to know about the symptoms of pregnancy disorder. ES is analyzed using forward chaining (FC) method and the Bayesian theorems. One of the Techniques that has been used to make a decision tree, then does a search with FC and the calculation of the probability by Bayesian. Based on the selected input symptoms dataset used 35 patients, the results of a pregnancy disorder which have the highest risk of disruption in eclampsia, with a value of 97% and the suitability of 82.86% system accuracy. Subsequent research, we perform hybrid Bayesian theorem and FC with fuzzy-neural network environments to produce values higher accuracy and will also make a decision in group clinical results.
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