Accuracy of Predicting the Unemployment Rate in Indonesia
Nanik Istiyani *
Faculty of Economics and Business, University of Jember, Jl. Jawa 37, Jember, East Java, 68122, Indonesia.
Anifatul Hanim
Faculty of Economics and Business, University of Jember, Jl. Kalimantan 37, Jember, East Java, 68121, Indonesia.
Ivana Rosediana Dewi
Faculty of Economics and Business, Universitas Airlangga, Jl. Airlangga 4-6 Surabaya, Indonesia.
M. Khoirun Najib
Faculty of Economics and Business, University of Jember, Jl. Kalimantan 37, Jember, East Java, 68121, Indonesia.
*Author to whom correspondence should be addressed.
Abstract
The Covid-19 pandemic has had numerous detrimental effects on Indonesia's economy. One is a rising unemployment rate due to a slowing economy, resulting in fewer employment prospects. This study aims to forecast the unemployment rate in Indonesia between 2023 and 2025, explicitly following the Covid-19 pandemic. This research utilises time series data for the period 2005 to 2022. The Augmented Dickey-Fuller (ADF) test indicates that the data for the unemployment rate are stationary at the first difference. The method used in this study is forecasting techniques using the ARIMA (1,1,1). Predictions indicate that the unemployment rate in Indonesia has increased during the Covid-19 pandemic. This can happen due to the increasing termination of employment (PHK) in Indonesia and the existence of social distancing which causes difficulties in working. However, after the Covid-19 pandemic, the unemployment rate is predicted to tend to decrease. This can happen because of government policies that help the community's economy, such as providing stimulus for business actors so that they can maintain their businesses and provide social security networks for informal workers. With government policies that help the community's economy, it has caused the unemployment rate in Indonesia to decline after Covid-19.
Keywords: Unemployment rate, forecasting, Covid-19