Brain Stroke Prediction Using Random Forest Method with Tuning Parameter

Brain stroke is a disease that contributes to the number of deaths in Indonesia. The number of victims of brain stroke is still increasing to this day, so a solution is needed that can predict brain stroke attacks in patients. This research is useful so that patients can be given appropriate medical treatment to prevent brain stroke. To predict brain stroke in patients, researchers designed an application that utilizes machine learning to provide accurate predictions based on several variables. The researcher used a dataset consisting of 4981 patient data with 10 non-labeled attributes who had/not had a brain stroke. By using random forest algorithm which then performed parameter tuning, researchers managed to get an accuracy of 98.98% in predicting the occurrence of brain stroke in patients.