Hasil Pencarian  ::  Simpan CSV :: Kembali

"besides physical test normally, early detection on the condition of the body by using the image processing of iris is an alternative method to observe the health of human's body, especially the internal organ of the body. in this paper, some image processing methodes are used to enhance the quality of iris image so that the problem that happens in area of pancreas can be detected clearly. the problem is represented by the form of broken tissue in iris. by using genetic programming, this iris image will be used as an input of an artificial intelligence system in detecting the internal organ disorder. the result of this detecting will be compared with the insulin normally test"

"Diabetes mellitus merupakan salah satu penyakit tidak menular dengan angka kematian tertinggi di dunia. Hal ini terjadi karena tingginya resiko komplikasi yang disebabkan pernyakit tersebut. Salah satu cara pencegahan yang dapat dilakukan adalah dengan melakukan pendeteksian lebih awal, salah satunya dengan menggunakan metode iridologi. Metode ini dapat mendeteksi kerusakan organ tubuh melalui tanda-tanda yang muncul pada iris. Dengan menggunakan metode tersebut penelitian ini dilakukan untuk mengklasifikasi penyakit diabetes menggunakan Convolutional Neural Network. Sistem ini mengevaluasi sebanyak 35 subjek normal dan 14 subjek diabetes. Adapun beberapa tahapan yang dilakukan untuk mengelola citra, di antaranya filtering, grayscaling, normalisasi, segmentasi, dan klasifikasi. Selain itu, sistem ini juga melakukan berbagai variasi untuk memperoleh konfigurasi terbaik, seperti variasi citra segmentasi dan tanpa segmentasi, variasi lebar iris, variasi bagian-bagian pankreas, variasi jumlah k-fold, dan variasi algoritma pengoptimalan menggunakan SGDM, Adam dan RMSProp. Sistem ini memperoleh akurasi sebesar 96,43% dengan variasi citra tanpa segmentasi berukuran  piksel menggunakan algoritma Adam dengan learning rate 0,001.

---

Diabetes mellitus is one of the uncontagious diseases with the highest mortality rate in the world. This happens because of the high risk of complications caused by this disease. One of the preventative ways is to do early detection, one of which is by using the iridology method. This method detects damage to the body's organs through the signs that appear on the iris. Using that method, this study was conducted to classify diabetes using Convolutional Neural Network. This system evaluates 35 normal subjects and 14 diabetes subjects. Several steps are taken to process the image, such as filtering, grayscaling, normalization, segmentation, and classification. Other than that, this system also performs various variations to obtain the best configuration, such as variations in image segmentation and without segmentation, variations in iris width, variations in parts of the pancreas, variations in the number of k-fold, and variations in optimization algorithms using SGDM, Adam and RMSProp. This system obtained an accuracy of 96.43% with variations image without segmentation size pixel using Adam's algorithm with a learning rate of 0.001."