Abstract

Many researchers conducted research on osteoarthritis. This is due to the large number of osteoarthritis patients. In Indonesia, one of ten people at risk of osteoarthritis. In addition, osteoarthritis cannot be cured, so it is important to know its status earlier. This study only focuses on the Decision Support System on the knee although osteoarthritis can occur in the hip, spine, thumb, index finger and toe. The severity of osteoarthritis which is divided into 5 clusters, namely KL-Grade 0 to KL-Grade 4. KL-Grade 0 shows normal conditions, and KL-Grade 4 is the worst condition. The purpose of this study is to build a Decision Support System (DSS) to determine osteoarthritis severity using Linear Vector Quantization (LVQ) based on First Order (FO) features. The method used is Linear Vector Quantization (LVQ) based on First Order (FO) features. The experiment was divided into four stages: image processing, feature extraction learning process, and testing process. The results obtained were that the system can classified well for KL-Grade 4 and KL-Grade 3, while for KL-Grade 0, KL-Grade 1, and KL-Grade 3 it still cannot properly qualify according to the cluster.

Original languageEnglish
Article number012045
JournalJournal of Physics: Conference Series
Volume1211
Issue number1
DOIs
Publication statusPublished - 7 May 2019
Event2nd International Conference of Combinatorics, Graph Theory, and Network Topology, ICCGANT 2018 - Jember, East Java, Indonesia
Duration: 24 Nov 201825 Nov 2018

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