Open AccessExpert System Using Dempster Shafer Method for Pre-Eclampsia Detection
Author(s) -
Endah Purwanti,
Nurrahmah Wida Achmadi,
Ernawati Ernawati,
M. Arief Bustomi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1805/1/012030
Subject(s) - eclampsia , predictive value , pregnancy , test (biology) , expert system , medicine , proteinuria , obstetrics , disease , computer science , artificial intelligence , paleontology , genetics , biology , kidney
Pre-eclampsia is a complication in pregnancy that is often diagnosed by hypertension and proteinuria in the second tri-semester of pregnancy. Pre-eclampsia could cause suffering for mother and fetus and also increase the risk of mother and child death. The main objective of this research is to develop an expert system to identify the risk of pre-eclampsia in pregnant women. The device was designed with 16 inputs in the form of symptoms and risk factors that influence the disease. This system uses the Dempster Shafer method for classification of 2 classes: there is a risk of pre-eclampsia and no risk of pre-eclampsia. The test consists of 2 aspects, namely the performance test and user satisfaction test. The results of the research for the performance test showed that the system accuracy reached 88.18% with sensitivity, specificity, Positive Predictive Value, and Negative Predictive Value were 92.72%, 83.63%, 85%, and 92%. User satisfaction test results show “good” in all aspects.