Upper Stomach Disorder Detection System using Backpropagation Artificial Neural Network
The study aims to make simple detection of upper stomach disorders of the iris image based on the chart to iridology, making anupper stomach disorder detection system using backpropagation artificial neural network method and determining the accuracy of the system. Backpropagation artificial neural networks is a type of neural network that trains the network to get a balance between the network’s ability to recognize patterns used during training as well as networking capabilities to provide a correct response to similar input patterns but not identical with patterns during training. Iridology is the science of analyzing the subtle structures of the iris. This research was conducted from the shooting stage of the eye image using the camera, data obtained as 40 iris images. Detection of disorders using chart to iridology from the iris imagery data of 20 pairs of eyes consisting of left and right. This results of 10 pairs of eye image showed that upper stomach disorder and 10 pairs of eye image showed no upper stomach disorder
Detection of body disorders using the chart to iridology of the 20 pairs of iris-image data consisting of left and right is detected as much as 10 pairs of eye image suffered by upper stomach disorder and 10 pairs of eye image did not suffer upper stomach disorder. The upper stomach disorder detection system is made using the backpropagation artificial neural networks method. In 20 eye data tested were obtained 11 iris imagery that corresponds to the detection using chart to iridology and 9 inappropriate iris imagery.
Fitria Hidayanti, Hari Hadi Santoso, Handoko Endo Prasetyo
Engineering Physics Department, Universitas Nasional, Jakarta 12520 Indonesia