Prediction of Tuberculosis Treatment Outcomes in Indonesia Using Support Vector Machine and Random Forest - Triloka, Joko; Sugianto, Dian (Politeknik Negeri Batam, 2025)
Tuberculosis (TB) remains a global health challenge, particularly in developing countries such as Indonesia, which ranks third worldwide in the number of TB cases. This study aims to evaluate the performance of Support Vector Machine (SVM) and Random Forest (RF) algorithms in predicting TB patient recovery rates based on clinical data obtained from healthcare facilities in Indonesia. Evaluation results indicate that the model achieved very high precision scores (100%) for the