Proceedings of 2nd Annual Management, Business and Economic Conference (AMBEC 2020)

<Previous Article In Volume
Next Article In Volume>

Inflation Forecasting by Commodity Using the Autoreggressive Integrated Moving Average (ARIMA) Method

Authors
Devi Ambar Wati, Nurafni Eltivia, Ludfi Djajanto
Corresponding Author
Devi Ambar Wati
Available Online 19 July 2021.
DOI
10.2991/aebmr.k.210717.045How to use a DOI?
Keywords
forecasting, inflation, Autoreggressive Integrated Moving Average (ARIMA)
Abstract

The aim of this research is to determine the best Autoregressive Integrated Moving Average (ARIMA) model and its implementation to predict monthly inflation in Indonesia. The data used is the inflation data on the expenditure group of foods, beverages, cigarettes and tobaccos in period January 2010 until December 2019. The method used in this study is the documentation technique. The data analysis technique used is the Autoregressive Integrated Moving Average (ARIMA) which is calculated using the SPSS version 26. The result of this research shows that ARIMA model (12,0,12) is the best model to predict monthly inflation on the expenditure group of foods, beverages, cigarettes and tobaccos in Indonesia for the next period. The results of forecasting 12 months in 2020 with the ARIMA model (12,0,12), in January until April decrease, then for May until August increase while September decrease and in October until December experienced an increase. Therefore, inflation is considered a major problem in the modern economy so that inflationary forecasting can be used in making an economic policy of the coming period which aims to reduce and stabilize price growth.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of 2nd Annual Management, Business and Economic Conference (AMBEC 2020)
Series
Advances in Economics, Business and Management Research
Publication Date
19 July 2021
ISBN
10.2991/aebmr.k.210717.045
ISSN
2352-5428
DOI
10.2991/aebmr.k.210717.045How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Devi Ambar Wati
AU  - Nurafni Eltivia
AU  - Ludfi Djajanto
PY  - 2021
DA  - 2021/07/19
TI  - Inflation Forecasting by Commodity Using the Autoreggressive Integrated Moving Average (ARIMA) Method
BT  - Proceedings of 2nd Annual Management, Business and Economic Conference (AMBEC 2020)
PB  - Atlantis Press
SP  - 226
EP  - 231
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210717.045
DO  - 10.2991/aebmr.k.210717.045
ID  - Wati2021
ER  -