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*Sufia Nur Janah  -  Jurusan Matematika, FMIPA, Universitas Sebelas Maret, Indonesia
Winita Sulandari  -  Jurusan Matematika, FMIPA, Universitas Sebelas Maret, Indonesia
Santoso Budi Wiyono  -  Jurusan Matematika, FMIPA, Universitas Sebelas Maret, Indonesia

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Hybrid model discussed in this paper combining ARIMA and backpropagation is applied to grain price forecasting in Indonesia for period January 2008 until April 2013. The grain price time series consists of linear and nonlinear patterns. Backpropagations can recognize non linear patterns that can not be done by ARIMA. In order to find the best model, some combinations of prepocessing transformations, the number of input and hidden units, and the activation function were applied in the contruction of the network structure. Based on the experiments, it can be showed that ARIMA backpropagation hybrid model provides more accurate results than ARIMA model.  The hybrid model would rather be used in the short-term forecasting, no more than three periods.


Keywords: ARIMA, Backpropagation, Hybrid, Grain Price

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