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: Ketut Sukiyono, Miftahul Janah
Format: Article
Language:English
Published: TALENTA 2019-03-01
Series:Indonesian Journal of Agricultural Research
Subjects:
Online Access:https://dev-talenta.usu.ac.id/InJAR/article/view/859
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author Ketut Sukiyono
Miftahul Janah
author_facet Ketut Sukiyono
Miftahul Janah
author_sort Ketut Sukiyono
collection DOAJ
description 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).
format Article
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institution Kabale University
issn 2622-7681
2615-5842
language English
publishDate 2019-03-01
publisher TALENTA
record_format Article
series Indonesian Journal of Agricultural Research
spelling doaj-art-369f12632a39425681073be2b12c45262025-01-04T11:23:46ZengTALENTAIndonesian Journal of Agricultural Research2622-76812615-58422019-03-0121Forecasting Model Selection of Curly Red Chili Price at Retail LevelKetut Sukiyono0Miftahul Janah1Department of Agricultural Socio Economics, Faculty of Agriculture, Universitas Bengkulu, IndonesiaDepartment of Magister Agribusiness, Faculty of Agriculture, University of Bengkulu, Indonesia 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). https://dev-talenta.usu.ac.id/InJAR/article/view/859curly red chiliforecastingretail
spellingShingle Ketut Sukiyono
Miftahul Janah
Forecasting Model Selection of Curly Red Chili Price at Retail Level
Indonesian Journal of Agricultural Research
curly red chili
forecasting
retail
title Forecasting Model Selection of Curly Red Chili Price at Retail Level
title_full Forecasting Model Selection of Curly Red Chili Price at Retail Level
title_fullStr Forecasting Model Selection of Curly Red Chili Price at Retail Level
title_full_unstemmed Forecasting Model Selection of Curly Red Chili Price at Retail Level
title_short Forecasting Model Selection of Curly Red Chili Price at Retail Level
title_sort forecasting model selection of curly red chili price at retail level
topic curly red chili
forecasting
retail
url https://dev-talenta.usu.ac.id/InJAR/article/view/859
work_keys_str_mv AT ketutsukiyono forecastingmodelselectionofcurlyredchilipriceatretaillevel
AT miftahuljanah forecastingmodelselectionofcurlyredchilipriceatretaillevel