Pengenalan Gangguan Ginjal Melalui Iridologi Menggunakan Hidden Markov Model (HMM)

Reza Satria Rinaldi (Program Studi Teknik Elektro Fakultas Teknik Universitas Bengkulu)
Wagiasih Wagiasih (Program Studi Teknik Elektro Fakultas Teknik Universitas Bengkulu)
Ika Novia Anggraini (Program Studi Teknik Elektro Fakultas Teknik Universitas Bengkulu)

Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer
Vol 9, No 2 (2019): Amplifier November 2019 Vol 9 No 2

ABSTRACTIridology has not been widely applied for the recognition of kidney disorders. identification of kidney disorders through iris image using iridology chart, can make it easier to make diagnosis to find out about kidney disorders. The method used in the process of recognition of kidney disorders through iridology is the Hidden Markov Model (HMM) method, with a HMM parameter determination system using the calculation of the koefisien Singular Value Decomposition (SVD) coefficient. The size of the codebook used is 7, i.e. 16, 32, 64, 128, 256, 512 and 1024. Different sizes of codebooks will result in different recognition times. The time needed will be longer when the size of the codebook is getting bigger. The accuracy of the process of recognition of kidney disorders through iridology using the HMM method in this study is 68.75% for codebook 16, 87.5% for codebook 32, 100% for codebook 128 and 100% for codebook 512. Keywords : iridology, codebook, image processing, singular value decomposition (SVD), Hidden Markov Model (HMM).