Machine Learning and Deep Learning Approach for Predicting Neonatal Mortality in Indonesia

This research explores machine learning approaches to determine the most significant features related to neonatal mortality in Indonesia. We create prediction tasks with deep learning models including MLP, LSTM, and CNN. We found that low birth weight and early breastfeeding becomes the most significant features related to neonatal mortality in Indonesia. For prediction task, implementing feature importance task as feature selection can improve prediction performance and reduce algorithm complexity. LSTM and CNN achieved the best prediction model with 90.91% accuracy.