Comparison of Vector Error Correction Model Prediction and Multiresponse Fourier Series, Case Study: Open Unemployment Rate in Indones IA

Suliyanto Suliyanto; Dita Amelia; Kezya Bato Raya; Jennifer Evelyn

doi:10.31764/jtam.v8i4.24108

Comparison of Vector Error Correction Model Prediction and Multiresponse Fourier Series, Case Study: Open Unemployment Rate in Indones IA

Suliyanto Suliyanto, Dita Amelia, Kezya Bato Raya, Jennifer Evelyn

Abstract

Unemployment is someone who has been classified in the active labour force is looking for work at a certain wage level, but not getting the job they want. According to the International Monetary Fund (IMF) 2023, Indonesia is ranked second highest in Southeast Asia, ranked 16th in Asia and ranked 58th in the world with a percentage of 5.45%. The data used in this study is semester data (February and August) regarding the number of open unemployment according to the highest education completed in Indonesia taken from the website of the Central Statistics Agency (BPS) starting from 2000 to 2022. This study using comparison of multi response Fourier series regression with trigonometry method using Gamma and the Vector Error Correction Model (VECM). The result of this study is Fourier series regression method of the cos function with gamma is the best model in predicting because this method has smaller MAPE value compared to VECM method. The MAPE of Fourier Series method is 0.01%, in other hand the MAPE of VECM method is 18.90% which can be categorized as prediction results with the Fourier Series method are very accurate. The results of prediction are expected to be used as reference for government to making ideal future plan to minimalize the rate of open unemployment in Indonesia.

Keywords

Open Unemployment; Fourier Series; VECM.

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DOI: https://doi.org/10.31764/jtam.v8i4.24108