Literature Review: Pendekatan K-Nearest Neighbors untuk Klasifikasi Penyakit Kardiovaskular

Adinda Sri Wahyuni; Aditya Firsyananda; Nurdiasih; Raden Achmad Ajru Ramadhan

Authors

Adinda Sri Wahyuni Universitas Pamulang
Aditya Firsyananda Universitas Pamulang
Nurdiasih Universitas Pamulang
Raden Achmad Ajru Ramadhan Universitas Pamulang

Keywords:

Cardiovascular Disease, K-Nearest Neighbors (KNN), Classification, Accuracy, Early Diagnosis

Abstract

This research reviews the literature to analyze the use of the K-Nearest Neighbors (KNN) approach in classifying cardiovascular diseases. Rapid technological advancements significantly impact, including in the machine-based heart disease classification systems. The algorithm frequently used in these studies is KNN, supported by Machine Learning. This research employs the Systematic Literature Review method to summarize and analyze various journals examining the use of KNN in heart disease classification, with these journals found through Google Scholar searches. Based on the literature review results, it was found that the KNN algorithm has great potential to be used as an aid in early diagnosis of heart disease. With a very high accuracy rate, this method offers medical personnel the opportunity to use data-driven guidance in making clinical decisions related to patients' cardiovascular risk. More accurate early diagnosis not only facilitates the determination of necessary intervention steps but also plays a crucial role in preventing the development of more serious disease complications.

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