The Best Forecasting Model For Cassava Price

Rahmi Yuristia(1), Dodi Apriyanto(2), Ketut Sukiyono(3),
(1) University of Bengkulu, Indonesia
(2) University of Bengkulu, Indonesia
(3) University of Bengkulu, Indonesia


This study aims to analyze and select the most accurate forecasting for predicting cassava prices in Indonesia. The data used is monthly data during the period of 2009 to 2017. This predicting uses the forecasting model, such as Moving Average, Exponential Smoothing, and Decomposition. Selecting the models found by comparing the smallest values of MAPE, MAD, and MSD. Therefore, it concluded that the Moving Average model is the most appropriate to Forecasting the price of cassava. Keywords : Selection, Forecasting model, cassava, prices

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Copyright (c) 2019 Rahmi Yuristia, Dodi Apriyanto, Ketut Sukiyono

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