Prediction of export and import in Indonesia using vector autoregressive integrated (VARI)

Vievien Abigail D. Djara, Dhita Diana Dewi, Harifa Hananti, Nurul Qisthi, Rosa Rosmanah, Zulfi Hm, Toni Toharudin, Budi Nurani Ruchjana

Abstract


This study aims to analyze the VARI model on the data of Indonesia's exports and imports from January 2015 to March 2021. The data from September 2020 to March 2021 became the out sample to measure the success of the VARI model in predicting exports and imports, which is measured by the value of MAPE (mean absolute percentage error). The R shiny program was developed to estimate the model parameter. Based on the Granger test, there was a causal relationship between exports and imports, so that past information on the export value can be used to predict the import values, and vice versa. The results of the analysis of the VARI model showed that simultaneously exports and imports in the previous period have a significant effect on the export and import value in the period of t. Based on the diagnostic test, the residuals have met the white noise assumption, and based on the MAPE value, the prediction results of the export and import values from October 2020 to March 2021 yielded a good result.

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Published: 2022-03-14

How to Cite this Article:

Vievien Abigail D. Djara, Dhita Diana Dewi, Harifa Hananti, Nurul Qisthi, Rosa Rosmanah, Zulfi Hm, Toni Toharudin, Budi Nurani Ruchjana, Prediction of export and import in Indonesia using vector autoregressive integrated (VARI), J. Math. Comput. Sci., 12 (2022), Article ID 105

Copyright © 2022 Vievien Abigail D. Djara, Dhita Diana Dewi, Harifa Hananti, Nurul Qisthi, Rosa Rosmanah, Zulfi Hm, Toni Toharudin, Budi Nurani Ruchjana. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 

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