KLASIFIKASI NAÏVE BAYES UNTUK PREDIKSI KELAHIRAN PADA DATA IBU HAMIL; NAÏVE BAYES CLASIFICATION FOR PREGNANCY DATA PREDICTION

ARIS NUGROHO, Subanar

2013 | Disertasi | PROGRAM STUDI S2 MATEMATIKA

In the health sector particularly in view of Maternal and Child Health, predicts a high risk event (resti) the emergence of risk pregnancies that can be addressed at an early stage will greatly affect the decline in Maternal Mortality Rate (MMR) and Infant Mortality Rate (IMR). With models such as Bayesian classification approach with Naïve Bayes HMAP (Maximum A Posteriori hypothesis) which will be used to predict birth experienced by pregnant women with maternal age characteristics, Height, Total hemoglobin, blood pressure, and pregnancy history and congenital disease. All data used discritization based limits and the Department of Health in the form of results predicted probability of the risk, can be used as a reference to place of birth or the performance appraisal of delivery service providers. With klasifNB function in R language through training phase for maximum likelihood estimation and in prediction phase according to criteria / characteristics of pregnant women , a dynamic application to predict corresponding selected area

Kata Kunci : KLASIFIKASI; NAÏVE BAYES; PREDIKSI; KELAHIRAN IBU HAMIL