Prediction of Corn Crop Yield Using Backpropagation Neural Network Algorithm

Abstract

Corn is one type of food crop commodity in Indonesia. Malang Regency is one of the producers that ranks 10th in corn production in the East Java region. People are very interested in planting corn because this crop commodity has many benefits so as to make the demand for production increase. There was a significant increase in market demand, but the uncertain amount of production made the supply of corn plants unable to be fulfilled properly. In this study, it predicted the demand for corn by using the Backpropagation Neural Network algorithm in Malang Regency. The data in this study were obtained from the Department of Agriculture and Food Security of East Java Province starting from 2007-2020 every month using maize data from the Malang area. The results showed that the backpropagation algorithm produced an MSE value of 0.00004178.