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Submitted
April 24, 2020
Accepted
June 6, 2020
Published
December 30, 2020
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Abstract

The inflation and interest rates in Indonesia have a significant impact on the country's economic development. Indonesian inflation and interest rates data are multivariate time series data that show activity over a certain period of time. Vector Autoregressive Integrated Moving Average (VARIMA) is a method for analyzing multivariate time series data. This method is a simultaneous equation modeling that has several endogenous variables simultaneously. This study aimed to model the inflation and interest rates data, from January 2009 to December 2016 and predict inflation and interest rates by using VARIMA method. The model obtained was the VARIMA(0,2,2) model, with estimated parameters using the maximum likelihood method. The choice of the VARIMA(0,2,2) model was based on the smallest AIC value of -4,2891, with a MAPE value for the inflation and interest rates forecasting were 6,04% and 1,84%, respectively, which indicates a very good forecast results.

Keywords

Akaike’s Information Criterion (AIC)Mean Absolute Percentage Error (MAPE)Multivariate time seriesVARIMA

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All articles published in the Eigen Mathematics Journal will be available for free reading and downloading. The license applied to this journal is Creative Commons Attribution-Non-Commercial-Share Alike (CC BY-NC-SA).

How to Cite
Jusmawati, J., Hadijati, M., & Fitriyani, N. (2020). Penerapan Model Vector Autoregressive Integrate Moving Average dalam Peramalan Laju Inflasi dan Suku Bunga di Indonesia. EIGEN MATHEMATICS JOURNAL, 3(2), 73–82. https://doi.org/10.29303/emj.v3i2.62
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