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Nur Aini
Universitas Dinamika Bangsa, Jambi
Computer Science & IT

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Klasifikasi Penyakit Gagal Jantung Menggunakan Algoritma K-Nearest Neighbor Yovi Pratama; Anton Prayitno; Defrin Azrian; Nur Aini; Yoga Rizki; Errissya Rasywir
Bulletin of Computer Science Research Vol. 3 No. 1 (2022): Desember 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v3i1.203

Abstract

Cardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated 17.9 million lives each year, which accounts for 31% of all deaths worldwide. Four out of 5CVD deaths are due to heart attacks and strokes, and one-third of these deaths occur prematurely in people under 70 years of age. Heart failure is a common event caused by CVDs and this dataset contains 11 features that can be used to predict a possible heart disease. People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need early detection and management wherein a machine learning model can be of great help.
Co-Authors Anton Prayitno Defrin Azrian Errissya Rasywir Yoga Rizki Yovi Pratama