Forecasting educated unemployed people in Indonesia using the Bootstrap Technique

Document Type : Research Paper

Authors

1 Department of Mathematics Education, IAIN Pekalongan, Pekalongan, Central Java, Indonesia

2 Department of Mathematics, Universitas Ahmad Dahlan,Yogyakarta, Indonesia

3 Department of Mathematics Education, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

Abstract

Forecasting is an essential analytical tool used to make future predictions based on preliminary data. However, the use of small sample sizes during analysis provides inaccurate results, known as asymptotic forecasting. Therefore, this study aims to analyze the unemployment rate of educated people in Indonesia using the bias-corrected forecasting bootstrap technique. Data were collected from a total of 30 time series of educated unemployed from 2015 to 2019 using the bias-corrected bootstrap technique and determined using the interval prediction method. The bootstrap replication used is at intervals of 100, 250, 500, and 1000. The results obtained using the R program showed that the bootstrap technique provides consistent forecasting results, better accuracy, and unbiased estimation. Moreover, the results also show that for the next 10 periods, the number of educated unemployed people in Indonesia is projected to decline. The bootstrap coefficient also tends to decrease with an increase in the number of replications, at an average of 0.958. The interval prediction is also known to be smooth, along with a large number of bootstrap replications.

Keywords

References

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Journal of Mahani Mathematical Research
Volume 12, Issue 1 - Serial Number 24
January 2023
Pages 171-182

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History

  • Receive Date: 21 April 2022
  • Revise Date: 02 June 2022
  • Accept Date: 06 July 2022

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