APPLICATION OF BACKPROPAGATION NEURAL NETWORK ALGORITHM FOR CIHERANG RICE IMAGE IDENTIFICATION - Aprilia, Dita; Jaman, Jajam Haerul; Adam, Riza Ibnu (LPPM Universitas Nusa Mandiri, 2020)
Rice is a food source for carbohydrates that are most consumed in Indonesia, because of this the production is higher compared to other food crops. There are several superior rice varieties planted by the farmers, one of them is Ciherang. This type is widely planted by farmers because has high selling as economic value and can be used as premium rice. The existence of several types of rice that had a high sales value makes some person was deceitfulness by mix the rice with premium quality with bad quality. Many people do not know the problem of distinguishing types of rice from one to another that has the same shape. Classification techniques using the backpropagation neural network algorithm and image processing are used to identify one of the most preferred types of rice, Ciherang. The network architecture model on the backpropagation algorithm is very influential on the value of accuracy. In determining the best network’s architectures, 4 times attempted where network architecture with 5 nodes in the input layer, 8 nodes in the hidden layer, and 1 node in output layer produce the highest accuracy of 82,66%.