IMPLEMENTASI KLASIFIKASI POTENSI PENYAKIT JANTUNG DENGAN MENGGUNAKAN METODE C4.5 BERBASIS WEBSITE ( STUDI KASUS KAGGLE.COM )

Alfian Rahmat (Teknik Informatika, Universitas Nurul Jadid)
M. Syafiih (Teknik Informatika, Universitas Nurul Jadid)
Mochammad Faid (Teknik Informatika, Universitas Nurul Jadid)

Infotech Journal
Vol. 9 No. 2 (2023)

Heart disease is one of the leading causes of death worldwide. Therefore, early detection and classification of potential heart diseases are very important in prevention and early treatment efforts. In this study, we implemented the C4.5 classification method to analyze the dataset obtained from the Kaggle.com platform. This research aims to build an efficient and accurate classification model to identify potential heart diseases based on relevant medical features. The dataset used includes demographic information, medical history, and other health parameters of a number of patients. The results obtained from using the C4.5 method to make predictions get 85% accuracy so that it can be expected to be a source of information for further research on predictions using the C4.5 method