APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO IDENTIFY DISEASES IN BROILER CHICKENS USING THE BACKPROPAGATION METHOD

rohul Iman

doi:10.23960/jitet.v14i1.8322

Authors

rohul Iman universitas mataram

DOI:

https://doi.org/10.23960/jitet.v14i1.8322

Abstract Views: 83 File Views: 50

Keywords:

Artificial Neural Network; Backpropagation Method; Image Data; Matlab

Abstract

Artificial neural networks can be applied in the health sector. In this research, artificial neural networks were used to identify diseases in broiler chickens using the Backpropagation method. Diseases in chickens include salmonella, cocidiossis, and new castle disease. Identification of diseases in chickens based on image data from chicken droppings. The method used is backpropagation or error propagation. The data used in this research was 700 image data. The data in this research was obtained from Kaggle. The best accuracy results were obtained with a total of 600 data with 1000 iterations, and an alpha value of 0.9 obtained testing accuracy results of 90% with an error value of 10%. The accuracy results of artificial neural networks are influenced by the amount of training data. The more data used, the higher the accuracy results.

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