PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA

  • Grace Lucyana Koesnadi Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Bagas Shata Pratama Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Dzuria Hilma Qurotu Ain Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Elly Pusporani Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0001-7948-3719
  • M. Fariz Fadillah Mardianto Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-4541-4552
DOI: https://doi.org/10.30598/barekengvol18iss4pp2247-2262
Keywords: ARIMA, Export, Fourier Series Estimator, SITC, SVR

Abstract

Export is an international trade activity that plays an important role in the economic progress in Indonesia. One of Indonesia's leading commodities that dominate the export market is jewelry. In export activities, the export unit value index is an important component that serves to describe the development of export commodity prices. This unit value index always changes every time and fluctuates. This research conducts a comparative analysis of the performance of parametric method, non-parametric method, and machine learning, specifically, ARIMA, Fourier series estimator, and Support Vector Regression (SVR). This study aims to evaluate the effectiveness of various methods in improving prediction accuracy for the unit value index of the SITC code 897 in Indonesia. The research data used is secondary data including monthly export unit value index data with SITC code 897 in Indonesia obtained from the Central Bureau of Statistics. The data divided into 90% training data and 10% testing data. The methods used in this analysis are ARIMA, Fourier series estimator, and SVR. The best model obtained from each method is ARIMA (1,1,1) with MAPE of 10.92%, Fourier series estimator with MAPE of 8.47%, and an SVR RBF kernel function with MAPE of 3.73%. The results of this study obtained the best method for predicting the unit value index of SITC code 897 is SVR with an RMSE value of 8.288 and very good prediction accuracy.

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Published
2024-10-11
How to Cite
[1]
G. Koesnadi, B. Pratama, D. Ain, E. Pusporani, and M. Mardianto, “PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA”, BAREKENG: J. Math. & App., vol. 18, no. 4, pp. 2247-2262, Oct. 2024.
Issue
Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2024 Grace Lucyana Koesnadi, Bagas Shata Pratama, Dzuria Hilma Qurotu Ain, Elly Pusporani, M. Fariz Fadillah Mardianto

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