The baby delivery method estimation using naïve bayes classification model for mobile application

作     者：Ewika Nadya Iftitah Riries Rulaningtyas Ernawati 

作者机构：Biomedical Engineering Study Program Department of Physics Airlangga University Jl. Mulyorejo Surabaya 60115 Indonesia Department of Obstetric and Gynecology Medical Faculty Airlangga University Jl. Mulyorejo Surabaya 60115 Indonesia 

出 版 物：《Journal of Physics: Conference Series》 

年 卷 期：2018年第1120卷第1期

学科分类：07[理学] 0702[理学-物理学] 

摘      要：The maternal mortality rate because of cesarean delivery is still high caused by lack of knowledge of pregnant women about the high risk of pregnancy. Cesarean delivery is an alternative labor but remains at high risk for both mother and fetus. The awareness of the mother to check her pregnancy early and precisely is very important. To support the awareness attitude of pregnant women to their health, so in this research has made an application program for the mobile application based on Android by using Naïve Bayes classification model to predict early childbirth process that will be undertaken. From this research, it can be concluded that the application of the baby delivery method estimation with Naïve Bayes model based on Android can educate pregnant women about high-risk pregnancy condition and prediction of delivery method that will be done with 90% accuracy, 100% sensitivity, and 80% specificity.