PREDIKSI KELAHIRAN BAYI BERBASIS SISTEM INFORMASI MENGGUNAKAN MACHINE LEARNING

Abstract

This study focuses on developing an information system to more accurately predict the date of childbirth. The system utilizes a machine learning algorithm trained on clinical and demographic data from electronic medical records. Of the three models tested—Random Forest, Support Vector Machine (SVM), and Artificial Neural Network (ANN)—the Random Forest model demonstrated superior performance with an accuracy of 92.5%. This accuracy significantly surpasses conventional prediction methods. Therefore, this system can serve as an effective decision-support tool for medical professionals to manage labor and reduce potential complications.

Keywords: Information System, Prediction, Algoritm, Machine Learning, Childbirth