Predicting unemployment rates in Indonesia

Umi Mahmudah (School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu)

Economic Journal of Emerging Markets
Volume 9 Issue 1, 2017

The main purpose of this study is to predict the unemployment rate in Indonesia by using time series data from 1986 to 2015 using autoregressive integrated moving average (ARIMA). A differencing process is required due to the actual time series of the unemployment rates in Indonesia is non-stationary. The results show that the best model for forecasting the unemployment rate in Indonesia by using the ARIMA (0,2,1) model. The forecasting results reveal that the unemployment rate in Indonesia tends to decrease continuously. The average of the residuals is close to zero which informs a good result of the forecasting analysis.