Implementasi Metode Backpropagation Neural Network Dalam Memprediksi Hasil Produksi Kedelai Berdasarkan Pengaruh Iklim

Laili, Barorotus Sulusayil (2020) Implementasi Metode Backpropagation Neural Network Dalam Memprediksi Hasil Produksi Kedelai Berdasarkan Pengaruh Iklim. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

Soybean production increased, but still could not meet the increasing need for soy consumption. One of the environmental components that determines the success of soybean production is climate factors such as temperature, sunlight, rainfall and exposure time. A system of climate prediction and crop production is needed to find out how much development the level of soybean production in Indonesia in the future. The method used in this forecasting uses Artificial Neural Networks or better known as Neural Networks, and the Artificial Neural Network algorithm used in this study is backpropagation because of its simplicity and good performance. The results in this study obtain accuracy from the Backpropagation Neural Network method of 96.5%.

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