Prediction of Central Java’s Number of Exports to Four ASEAN Countries Using the Markov Chain Analysis

Authors

  • Ria Novita Awalia Ramadhani Institut Teknologi Telkom Purwokerto
  • Andreas Rony Wijaya Institut Teknologi Telkom Purwokerto
  • ALIFIA ZAHRA WINESTI Institut Teknologi Telkom Purwokerto
  • DESTY MAYANG PRATIWI Institut Teknologi Telkom Purwokerto

DOI:

https://doi.org/10.34123/icdsos.v2023i1.371

Keywords:

Prediction, Exports, Markov Chain, ASEAN, Stochastic

Abstract

Central Java is one of the provinces that has many of natural resources and extraordinary industrial potential, able to offer reliable prospects to various developed countries in ASEAN, namely Singapore, Brunei Darussalam, Malaysia, and Thailand, to become the focus of exploration attention. Therefore, a prediction is made of Central Java's exports to the four ASEAN countries in 2022 and 2023 by applying the Markov chain analysis method. The prediction results obtained that the total exports to Singapore, Brunei Darussalam, Malaysia and Thailand in a row in 2022 are 0.701, 0.001, 0.239, and 0.058. While the predictions for 2023 for the four countries are 0.540, 0.001, 0.409, and 0.050 respectively. Meanwhile, the steady state of the Markov chain is 0.3595 for Singapore, 0.0013 for Brunei Darussalam, 0.6001 for Malaysia, and 0.0389 for Thailand. The results of this prediction can assist parties involved in making economic decisions related to Central Java's exports to developed countries in ASEAN. Information regarding predictions of an increase or decrease in exports from one year to the next can be used as a reference for business people, governments and related organizations to plan more appropriate and efficient economic strategies and policies.

Downloads

Published

2023-12-29

How to Cite

Ramadhani, R. N. A., Wijaya, A. R., WINESTI, A. Z., & PRATIWI, D. M. (2023). Prediction of Central Java’s Number of Exports to Four ASEAN Countries Using the Markov Chain Analysis. Proceedings of The International Conference on Data Science and Official Statistics, 2023(1), 792–797. https://doi.org/10.34123/icdsos.v2023i1.371