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All Journal Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer
Wagiasih Wagiasih
Program Studi Teknik Elektro Fakultas Teknik Universitas Bengkulu
Computer Science & IT Electrical & Electronics Engineering Engineering

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Pengenalan Gangguan Ginjal Melalui Iridologi Menggunakan Hidden Markov Model (HMM) Reza Satria Rinaldi; Wagiasih Wagiasih; Ika Novia Anggraini
JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER Vol 9, No 2 (2019): Amplifier November 2019 Vol 9 No 2
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jamplifier.v9i2.15379

Abstract

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).
Co-Authors Ika Novia Anggraini Reza Satria Rinaldi