Predicting the Risk of Premature Birth Using Naive Bayes Based on Maternal Health Data at Rantauprapat Regional Hospital - Adawiyah, Quratih; Handayani, Rika; Nadrah, Nailatun; Nasution, Fitriyani; Ramadani, Putri (PT Inovasi Pratama Internasional, 2025)
Premature birth is one of the leading causes of infant mortality and complications. Early identification of pregnant women at risk of premature delivery is crucial for appropriate management. This study aims to develop a predictive model for premature birth risk using the Naïve Bayes method based on maternal health data from RSUD Rantauprapat. The data used includes variables such as mother's age, nutritional status, blood pressure, and history of premature birth. The study applies Naïve Bayes to predict the classes of premature birth risk, namely