Klasifikasi Penyakit Gagal Jantung dengan Algoritma XGBoost - I Gusti Gde Bagus Bhadrika Artawibawa; Anak Agung Istri Ngurah Eka Karyawati (Jurnal Nasional Teknologi Informasi dan Aplikasinya, 2024)
Heart, as one of the most important organs in the body, carries a risk of death if abnormalities occur. Heart problems are divided into two categories: heart failure and heart attacks. According to WHO data, approximately 7.3 million people worldwide die due to heart disease. This study uses a dataset of heart disease patients and applies the XGBoost algorithm. The objectives of this study are to process and analyze the data, implement the XGBoost algorithm for heart disease classification, and evaluate the performance of the XGBoost algorithm. The result of this study is the performance evaluation of the XGBoost algorithm, which achieved an accuracy of 93%.