Ewika Nadya Iftitah and Riries Rulaningtyas and Ernawati (2018) The baby delivery method estimation using naïve bayes classification model for mobile application. IOP Conference Series: Journal of Physics, 1120. pp. 1-5. ISSN 17426588

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Abstract

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.

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