PENGENALAN POLA CITRA IRIS MATA MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION UNTUK MENDETEKSI PENYAKIT KULIT PADA MANUSIA

AINIR ROHMAH, NIM. 09651008 (2016) PENGENALAN POLA CITRA IRIS MATA MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION UNTUK MENDETEKSI PENYAKIT KULIT PADA MANUSIA. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Skin disease caused by toxin cumulated at skin makes a black hole around the iris called scurf rim. At the iridologist chart, scurf rim areas located at 7th topography or outer of eye iris connect the sclera. Eye iris can be read by the expert (iridologist) make a difference because every people had a different subjectivity. For anticipated, we made an automation in this research. In this research, the data taken from a public database called CSBR (Center for Biometric and Security Research). 50 image data divided by 2, 40 train data and 10 test data. The process in preprocess steps are cropping, histogram equalizing, changing polar image to rectangular, automating crop to take the scurf rim area, and canny edge detection. The process steps are pattern recognizing using GLCM (Grey Level Co-occurrence Matrix) and pattern classification using backpropagation neural network. The image tested use Matlab 7.1. The result from averages of all image that extract using GLCM using contrast, homogeneity, energy and correlation for normal condition are 7,469835; 0,850391; 0,646432 and 0,145386. For the abnormal image are 6,784483; 0,863412; 0,671574 and 0,157455. The presentation of recognizing train data is 100% from 40 train data and 80% for the test data from 10 data.

Item Type: Thesis (Skripsi)
Additional Information / Pembimbing: Dr. Shofwatul ‘Uyun, M.Kom
Uncontrolled Keywords: backpropagation artificial neural network, eye iris image, GLCM, iridology, skin, scurf rim
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User / Editor: Miftahul Ulum [IT Staff]
Date Deposited: 22 Feb 2016 09:29
Last Modified: 22 Feb 2016 17:27
URI: http://digilib.uin-suka.ac.id/id/eprint/19478

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