PREDICTION OF TIN EXPORTS, POPULATION, POVERTY, AND LABOR FORCE IN THE PROVINCE OF BANGKA BELITUNG ISLANDS

  • Elyas Kustiawan Department of Mathematics, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia
  • Desy Yuliana Dalimunthe Department of Mathematics, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia https://orcid.org/0000-0002-4021-8130
  • Vebtasvili Vebtasvili Department of Accounting, Faculty of Economics and Business, Universitas Bangka Belitung, Indonesia
  • Haslen Oktarianty Department of Mining Engineering, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia
  • Yabes Sentosa Silaban Department of Mathematics, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia
  • Fadillah Luthfiyah Department of Mathematics, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia
  • Dita Rahmania Department of Mathematics, Faculty of Science and Engineering, Universitas Bangka Belitung, Indonesia
DOI: https://doi.org/10.30598/barekengvol18iss4pp2589-2596
Keywords: Economic Recession, Exponential Smoothing, Moving Average

Abstract

The COVID-19 virus has also caused shocks to the Bangka Belitung Islands Province in various sectors, especially the economy. To overcome this problem, of course the government has prepared responsive policies, both fiscal and monetary policies to prevent post-COVID-19 risks, especially in the economic recession. To prevent a post-COVID-19 economic recession, a prediction or time series forecast is needed on four variables that influence the economic recession, namely the number of tin exports, population, poverty and labor force in the Bangka Belitung Islands Province so that economic growth is maintained. This research aims to predict the four research variables by comparing the Moving Average and Exponential Smoothing methods. This research also uses Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) as indicators of model accuracy. Based on the results of the accuracy indicators of this model, it was found that the Exponential Smoothing method was better than the Moving Average method. The predicted results for the value of tin exports in 2024 are -3.3645811 with The RMSE value is 42293770, MAE is 29558091, and MAPE is 84.46131. The negative value in the tin export prediction means that the decline in the value of tin exports in 2024 will not have a significant effect because it is still within a reasonable figure. The total labor force in 2024 will be 11057.23 with RMSE value is 16536.48, MAE value is 14194.02, and MAPE is 112.8078. Then for population the predicted result is 21241.92 with RMSE is 19537.82, MAE is 11548.41, and MAPE is 37.51894. Then for the predicted results the number of poverty is 70.22749 with RMSE, MAE, and MAPE respectively of 3992.146, 3205.528, and 139.1129. The alpha value used is 0.0183.

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Published
2024-10-14
How to Cite
[1]
E. Kustiawan, “PREDICTION OF TIN EXPORTS, POPULATION, POVERTY, AND LABOR FORCE IN THE PROVINCE OF BANGKA BELITUNG ISLANDS”, BAREKENG: J. Math. & App., vol. 18, no. 4, pp. 2589-2596, Oct. 2024.
Issue
Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2024 Elyas Kustiawan, Desy Yuliana Dalimunthe, Vebtasvili Vebtasvili, Haslen Oktarianty, Yabes Sentosa Silaban, Fadillah Luthfiyah, Dita Rahmania

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