Abstract

Iridology is a scientific study of the shape and structure of the iris that can provide an overview of every organ in the human body. Research on computerized iridology has been carried out. Cases of decreased organ excretion through iridology that are commonly found are the organs of the lungs and kidneys. The purpose of this research using a deep learning approach namely Convolutional Neural Network to detect decreased organ function in the lungs and kidneys through the iris of the eye. The study of iridology and iris image obtained from iridologists. The cropping method is used to extract the identified part of the eye image. The cropping method consists of a median filter to remove noise, a hough circle transforms to get an iris circle and a region of interest to get the identified part. Image cropping results are used as training data and test data. The Convolutional Neural Network training process uses the VGG16 model with 2 classes, normal and not normal. The results of Convolutional Neural Network research can detect decreased organ function in excretion through the iris of the eye. From 40 testing data with details of 20 right eyes and 20 left eyes, the accuracy is 90%.

Authors:

• Juwairiah Information System Program study, Informatic Department Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta, Indonesia
• Herry Sofyan Information System Program study, Informatic Department Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta, Indonesia
• Vincentius Dian Asa Putra Information System Program study, Informatic Department Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta, Indonesia
• Herlina Jayadianti Information System Program study, Informatic Department Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta, Indonesia

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