Implementasi Machine Learning Untuk Prediksi Penyakit Jantung Menggunakan Algoritma Support Vector Machine
Rahmat Hidayat, Yandiko Saputra Sy, Teguh Sujana, Mirdatul Husnah, Haris Tri Saputra, Finanta Okmayura · BIOS Jurnal Teknologi Informasi dan Rekayasa Komputer · 2024
Heart disease is currently a disease that has taken over many human lives. Data shows that more than 17 million people have died from heart disease. The high number of deaths, therefore, requires special handling to treat and prevent heart disease. In the development of technology, diagnosis of heart disease can be done with the help of information technology, one of which is through machine learning. This study aims to implement machine learning through the SVM algorithm to predict heart disease. The model formed by SVM produces an evaluation value indicated by an accuracy value of 0.85, a precision of 0.93, a recall of 0.76, and an f-1 score of 0.83. This model is used as training data to predict heart disease which is then successfully used to create a system through the Streamlit library which can be easily accessed via the website.