Analisis Data Jumlah Pengangguran Sebelum dan Sesudah Pandemi Covid-19 di Indonesia Menggunakan Uji Wilcoxon

Abstract

Covid-19 or the corona virus is an outbreak of an infectious disease whose transmission rate is so fast and affects all ages that it can cause death. The Covid-19 pandemic has made the government issue various policies such as the enactment of large-scale social restrictions so that companies that are affected and the worst have to stop operating which causes mass terminations. This can lead to a significant increase in the unemployment rate. The latest data from the Central Statistics Agency in August 2019, the open unemployment rate in Indonesia reached 7.05 million people or 5.28% of the total labor force. This study aims to analyze data on the number of unemployed before and after the Covid-19 pandemic in Indonesia using the Kolmogorov Smirnov test and the Wilcoxon test. Wilcoxon test to find out if there is a difference between two samples paired with the ordinal data form, where the data must be abnormally distributed by performing the kolmogorov smirnov test. The data used in this study is secondary data obtained from the publication of the Indonesian Central Statistics Agency, namely the number of unemployed before (2017-2019) and after (2020-2022) the Covid-19 pandemic in 34 provinces in Indonesia. The results of the kolmogorov smirnov test showed that the data on the number of unemployed before and after the Covid-19 pandemic in Indonesia were not normal because the p-value For the results of the Wilcoxon test, the Value of Asymprejected, meaning that there is a difference between the number of unemployed before and after the Covid-19 pandemic in Indonesia.