Penerapan Algoritma K-Nearest Neighbor dalam Klasifikasi Penyakit Gagal Jantung

  • Ni Ketut Intan Setiawati Universitas Udayana
  • I Gede Arta Wibawa Universitas Udayana

Abstract

Heart failure is a clinical syndrome caused by an abnormality in the structure of the heart's function that causes the heart to be unable to pump adequate amounts of blood so that the body does not receive enough nutrients for metabolic needs. The high prevalence of heart failure needs serious attention so that it can be treated early and reduce the risk of complications. Along with the development of technology, various classification methods have been used by other researchers to determine whether a person has heart failure or not. In this study, the classification of heart failure will use the K-Nearest Neighbor algorithm. K-Nearest Neighbor (KNN) is a classification algorithm based on the proximity of data to other data. The results of this study are the best accuracy values obtained with k = 7, where after going through an evaluation with the confusion matrix, the accuracy of the classification of heart failure with KNN is 91%.

Published
2022-11-25
How to Cite
SETIAWATI, Ni Ketut Intan; WIBAWA, I Gede Arta. Penerapan Algoritma K-Nearest Neighbor dalam Klasifikasi Penyakit Gagal Jantung. Jurnal Nasional Teknologi Informasi dan Aplikasinya (JNATIA), [S.l.], v. 1, n. 1, p. 347-352, nov. 2022. Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/92598>. Date accessed: 26 jan. 2023.

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.