Predicting unemployment rates in Indonesia
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-stationa...
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| Format: | Article |
| Language: | English |
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Universitas Islam Indonesia
2017-03-01
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| Series: | Economic Journal of Emerging Markets |
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| Online Access: | https://jurnal.uii.ac.id/JEP/article/view/7090 |
| _version_ | 1827395856961110016 |
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| author | Umi Mahmudah |
| author_facet | Umi Mahmudah |
| author_sort | Umi Mahmudah |
| collection | DOAJ |
| description |
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.
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| first_indexed | 2024-03-08T18:40:53Z |
| format | Article |
| id | doaj.art-6917bf2de96a4d539a96584dd812efbf |
| institution | Directory Open Access Journal |
| issn | 2086-3128 2502-180X |
| language | English |
| last_indexed | 2024-03-08T18:40:53Z |
| publishDate | 2017-03-01 |
| publisher | Universitas Islam Indonesia |
| record_format | Article |
| series | Economic Journal of Emerging Markets |
| spelling | doaj.art-6917bf2de96a4d539a96584dd812efbf2023-12-29T06:55:53ZengUniversitas Islam IndonesiaEconomic Journal of Emerging Markets2086-31282502-180X2017-03-0191Predicting unemployment rates in IndonesiaUmi Mahmudah0School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu 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. https://jurnal.uii.ac.id/JEP/article/view/7090ForecastingUnemployment rateARIMA |
| spellingShingle | Umi Mahmudah Predicting unemployment rates in Indonesia Economic Journal of Emerging Markets Forecasting Unemployment rate ARIMA |
| title | Predicting unemployment rates in Indonesia |
| title_full | Predicting unemployment rates in Indonesia |
| title_fullStr | Predicting unemployment rates in Indonesia |
| title_full_unstemmed | Predicting unemployment rates in Indonesia |
| title_short | Predicting unemployment rates in Indonesia |
| title_sort | predicting unemployment rates in indonesia |
| topic | Forecasting Unemployment rate ARIMA |
| url | https://jurnal.uii.ac.id/JEP/article/view/7090 |
| work_keys_str_mv | AT umimahmudah predictingunemploymentratesinindonesia |