Forecasting Model Selection of Curly Red Chili Price at Retail Level
Chilli is one of strategic commodity in Indonesia due to its contribution to inflation level. For this reason, future price information is very importance for designing price policy. Future price merely can be provided by conducting a price forecasting. Various forecasting models can be applied for...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
TALENTA
2019-03-01
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| Series: | Indonesian Journal of Agricultural Research |
| Subjects: | |
| Online Access: | https://dev-talenta.usu.ac.id/InJAR/article/view/859 |
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| Summary: | Chilli is one of strategic commodity in Indonesia due to its contribution to inflation level. For this reason, future price information is very importance for designing price policy. Future price merely can be provided by conducting a price forecasting. Various forecasting models can be applied for this purpose; the problem is which the best model for forecasting is. This study aims to select the most accurate forecasting model of curly red chili prices at the retail level. The data used are monthly data, from 2011 - 2017. Five forecasting models are applied and estimated including Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, Decomposition, and ARIMA. The best model is selected based on the smallest MAPE, MSE and MAD values. The results show that the most accurate forecasting model is ARIMA (1,1,9).
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| ISSN: | 2622-7681 2615-5842 |