Jaringan Syaraf Tiruan Untuk Klasifikasi Penyakit Demam Menggunakan Algoritma Backpropagation

Abstract

Technological advances have helped solve problems in various fields, especially in the health sector, one of which is in disease classification which makes it easier to control disease management to see what type of disease the disease belongs to. The classification process using a computer can be applied using various classification methods, one of which is the Artificial Neural Network method with the Backpropagation Algorithm. An artificial neural network is an information processing system that is designed to imitate the workings of the human brain by carrying out the learning process through changes in the weight of its synapses. One of the problems that can apply the Backpropagation algorithm in the case of classification is the classification of Fever Disease (Dengue and Typhoid) because of the similarity of the symptoms of the two diseases. The application of the Backpropagation algorithm in the Classification of Fever (Dengue and Typhoid Dengue Fever) begins with the training stages on 135 training data, and the best variation of learning rate and hidden layer neurons is obtained by trial and error. The test was carried out on test data as many as 15 data, the test results were in the form of a classification of fever diseases which were compared with the actual target.