Implementasi Learning Vector Quantization(LVQ) untuk KLasifikasi Penyakit Ginjal Kronis

  • I Gst Bgs Bayu Adi Pramana Universitas Udayana
  • I Made Widiartha Universitas Udayana
  • Luh Gede Astuti Universitas Udayana
##plugins.pubIds.doi.readerDisplayName## https://doi.org/10.24843/JLK.2020.v09.i02.p11

Abstrak

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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Diterbitkan
2020-11-24
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PRAMANA, I Gst Bgs Bayu Adi; WIDIARTHA, I Made; ASTUTI, Luh Gede. Implementasi Learning Vector Quantization(LVQ) untuk KLasifikasi Penyakit Ginjal Kronis. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 9, n. 2, p. 241-248, nov. 2020. ISSN 2654-5101. Tersedia pada: <http://103.29.196.112/index.php/jlk/article/view/64470>. Tanggal Akses: 04 mar. 2026 doi: https://doi.org/10.24843/JLK.2020.v09.i02.p11.

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