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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
Pramana, I Gst Bgs Bayu Adi
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Computer Science & IT

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Implementasi Learning Vector Quantization(LVQ) untuk KLasifikasi Penyakit Ginjal Kronis Pramana, I Gst Bgs Bayu Adi; Widiartha, I Made; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i02.p11

Abstract

Chronic kidney disease is a disruption in the function of the kidney organs. When the kidneys are no longer fully functioning, the body is filled with water and a waste product called uremia. As a result, the body or legs will experience swelling and feel tired quickly because the body needs clean blood. Therefore, impaired kidney function should not be underestimated because it can be fatal. Researchers have conducted research related to the classification of kidney disease to find out what symptoms can cause kidney disease. One method that can be used for classification is the Learning Vector Quantization (LVQ) method. In this study, the LVQ algorithm was applied to classify chronic kidney disease. From the research results, the highest accuracy is 81.667% with the optimal learning rate is 0.002.
Co-Authors I Made Widiartha Luh Gede Astuti