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Feralia Fitri
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Prediksi Mortalitas Gagal Jantung Menggunakan PCA dan K-Nearest Neighbors: Analisis Komparatif Metrik Jarak Feralia Fitri; Navessa Julieth
Technology Sciences Insights Journal Vol. 2 No. 2 (2025): Technology Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/qw66gg22

Abstract

Heart failure is a condition in which the heart is unable to pump blood optimally to meet the body’s metabolic demands. Accurate prediction is essential to support timely medical intervention. This study examines the use of the K-Nearest Neighbors (KNN) method to classify heart failure patient outcomes based on nearest-neighbor data from the training set. The method is combined with Principal Component Analysis (PCA) for data dimensionality reduction to predict patient mortality, demonstrating that KNN is a simple and effective approach for medical data analysis.
Co-Authors Navessa Julieth