Authors:

I Gst Bgs Bayu Adi Pramana, I Made Widiartha, Luh Gede Astuti

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.”

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PDF:

https://jurnal.harianregional.com/jlk/full-64470

Published

2020-11-24

How To Cite

PRAMANA, I Gst Bgs Bayu Adi; WIDIARTHA, I Made; ASTUTI, Luh Gede. Implementation Learning Vector Quantization(LVQ) for Chronic Kidney Disease Classification.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 9, n. 2, p. 241-248, nov. 2020. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/64470. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JLK.2020.v09.i02.p11.

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ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License