JOURNAL ARTICLE

Implementation of K-Nearest Neighbor Algorithm in Heart Disease Classification

Ni Kadek Sukma Putri RahayuI Komang Ari Mogi

Year: 2021 Journal:   JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol: 10 (1)Pages: 39-39

Abstract

The heart is an important organ that exists in the human body. The main function of the heart is to pump blood throughout the body through blood vessels. The WHO states that as many as 7.3 million people die from heart disease. In this study heart disease will be classified using the K-Nearest Neighbor algorithm. K-Nearest Neighbor algorithm is a classification algorithm based on the distance from data testing against training data with a pre-defined number of k. The results were obtained from performance measurements for the classification of heart disease with the K-Nearest Neighbor algorithm measured using the K-Fold Cross Validation algorithm, from an accuracy rate of 65.89%, a precision level of 66.27%, and a recall of 74.67%.

Keywords:
k-nearest neighbors algorithm Heart disease Algorithm Pattern recognition (psychology) Statistical classification Computer science Precision and recall Artificial intelligence Cardiology Medicine

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Citation History

Topics

Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems
Edcuational Technology Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Artificial Intelligence in Healthcare
Health Sciences →  Health Professions →  Health Information Management
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