Time series analysis and forecasting of unemployment in Purbalingga Regency using Brown’s double exponential smoothing: An accuracy-based evaluation

Dian Pratama; Chandra Sari Widyaningrum; Priska Sari Dewi

doi:10.66256/permata.v2i1.43

Authors

Dian Pratama Universitas Nahdlatul Ulama Purwokerto Author
Chandra Sari Widyaningrum Universitas Nahdlatul Ulama Purwokerto Author
Priska Sari Dewi Universitas Nahdlatul Ulama Purwokerto Author

DOI:

https://doi.org/10.66256/permata.v2i1.43

Keywords:

Unemployment, Forecasting, Double Exponential Smoothing, Brown Method

Abstract

Unemployment remains a persistent socioeconomic challenge in Indonesia, including Purbalingga Regency, Central Java. This study analyzes the unemployment trend and forecasts the number of unemployed individuals in Purbalingga Regency using a time-series approach. Annual unemployment data for 2010–2024 from the Central Bureau of Statistics (BPS) were modeled using Brown’s Double Exponential Smoothing (DES), which is suitable for non-seasonal series with a linear trend. The smoothing parameter (α) was examined from 0.1 to 0.9, and model performance was evaluated using MAD, MSE, and MAPE based on in-sample fitted errors over the 2010–2024 period. The results indicate a fluctuating but upward trend, particularly after the COVID-19 period. The best-performing parameter was α = 0.2, producing the lowest MAD and MAPE; under this evaluation setting, MAPE was below 1%, indicating low in-sample error. Using the selected model, unemployment in 2025 is forecast at approximately 31,795 people. These findings suggest that Brown’s DES can provide a practical baseline forecast to support evidence-based labor market policy and regional economic planning, while the results should be interpreted with caution, given the linear-trend and univariate assumptions.

Downloads

Download data is not yet available.

References

[1] Badan Pusat Statistik, “Kabupaten purbalingga dalam angka 2024”, 2024, Accessed: Jan. 14, 2026. [Online]. Available: https://purbalinggakab.bps.go.id/id/publication/2024/02/28/536efeb76f0e327ceaf0c958/kabupaten-purbalingga-dalam-angka-2024.html

[2] Badan Pusat Statistik, “Kabupaten purbalingga dalam angka 2023”, 2023, Accessed: Jan. 14, 2026. [Online]. Available: https://purbalinggakab.bps.go.id/id/publication/2023/02/28/5869f3ccc17f3fc31d2856ca/kabupaten-purbalingga-dalam-angka-2023.html

[3] E. S. Gardner, “Exponential smoothing: The state of the art”, J. Forecast., vol. 4, no. 1, pp. 1–28, Jan. 1985, Accessed: Jan. 14, 2026. [Online]. Available: /doi/pdf/10.1002/for.3980040103

[4] B. Billah, M. L. King, R. D. Snyder, and A. B. Koehler, “Exponential smoothing model selection for forecasting”, Int. J. Forecast., vol. 22, no. 2, pp. 239–247, Apr. 2006, doi: 10.1016/J.IJFORECAST.2005.08.002.

[5] R. Gustriansyah, N. Suhandi, F. Antony, and A. Sanmorino, “Single exponential smoothing method to predict sales multiple products”, J. Phys. Conf. Ser., vol. 1175, no. 1, p. 012036, Mar. 2019, doi: 10.1088/1742-6596/1175/1/012036.

[6] N. L. Marpaung, K. R. Salim, R. Amri, and E. Ervianto, “Application of single exponential smoothing in forecasting number of new students acceptance”, International Journal of Technology and Engineering Studies, vol. 5, pp. 169–182, 2019, doi: 10.20469/ijtes.5.10001-6.

[7] A. Aliniy, Y. P. Pasrun, and A. T. Sumpala, “Prediksi jumlah mahasiswa baru FTI USN Kolaka menggunakan metode single exponential smoothing”, SATESI: Jurnal Sains Teknologi dan Sistem Informasi, vol. 3, no. 1, pp. 20–25, Apr. 2023, doi: 10.54259/SATESI.V3I1.1573.

[8] S. Hansun, “A new approach of Brown’s double exponential smoothing method in time series analysis”, Balkan Journal of Electrical and Computer Engineering, vol. 4, no. 2, pp. 75–78, Sep. 2016, doi: 10.17694/bajece.14351.

[9] S. Hansun and Subanar, “H-WEMA: A new approach of double exponential smoothing method”, TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 14, no. 2, pp. 772–777, Jun. 2016, doi: 10.12928/TELKOMNIKA.V14I2.3096.

[10] S. Widyantri, D. K. Hakim, E. A. Pambudi, and M. A. Fitriani, “Rainfall forecasting using triple exponential smoothing for rice cultivation in Lamongan, Jawa Timur”, Journal of Soft Computing Exploration, vol. 6, no. 1, pp. 9–16, Mar. 2025, doi: 10.52465/JOSCEX.V6I1.519.

[11] S. Dev, T. Alskaif, M. Hossari, R. Godina, A. Louwen, and W. Van Sark, “Solar irradiance forecasting using triple exponential smoothing”, 2018 International Conference on Smart Energy Systems and Technologies, SEST 2018 - Proceedings, Oct. 2018, doi: 10.1109/SEST.2018.8495816.

[12] R. Nelfi Yolanda, D. Rahmi, A. Kurniati, S. Yuniati, J. H. Pendidikan Matematika Fakultas Tarbiyah dan Keguruan Universitas Islam Negeri Sultan Syarif Kasim Riau Jl Soebrantas NoKm, and T. Karya Kec Tampan Riau, “Penerapan metode triple exponential smoothing dalam peramalan produksi buah nenas di Provinsi Riau”, Jurnal Teknologi dan Manajemen Industri Terapan, vol. 3, no. I, pp. 1–10, Mar. 2024, doi: 10.55826/TMIT.V3II.285.

[13] D. Ulya Rosa, M. Sururil Alan, H. Wulandari, and S. Ramadhan, “Metode exponential smoothing dalam memproyeksikan jumlah penduduk miskin di Nusa Tenggara Barat”, Jurnal Pemikiran dan Penelitian Pendidikan Matematika, vol. 2, no. 1, pp. 42–53, 2019, Accessed: Jan. 14, 2026. [Online]. Available: https://journal.rekarta.co.id/index.php/jp3m/article/view/210

[14] A. Sulaiman and A. Juarna, “Peramalan tingkat pengangguran di Indonesia menggunakan metode time series dengan model ARIMA dan Holt-Winters”, Jurnal Ilmiah Informatika Komputer, vol. 26, no. 1, pp. 13–28, 2021, doi: 10.35760/IK.2021.V26I1.3512.

[15] Z. U. Arifin, J. Herliani, and Hamdani, “Peramalan pengangguran menggunakan metode double exponential smoothing di Provinsi Kalimantan Timur”, in Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi, 2019.

[16] R. J. Hyndman and G. Athanasopoulos, “Forecasting: Principles and practice,” 2018, OTexts. Accessed: Jan. 14, 2026. [Online]. Available: https://research.monash.edu/en/publications/forecasting-principles-and-practice-2/

[17] S. G. , author Makridakis, “Metode dan aplikasi peramalan; Jilid 1”, 1991, Erlangga. Accessed: Jan. 14, 2026. [Online]. Available: https://lib.ui.ac.id

[18] M. I. Hasan, “Pokok-pokok materi statistik 1”, 2002, Accessed: Jan. 14, 2026. [Online]. Available: https://openlibrary.telkomuniversity.ac.id/home/catalog/id/223948/slug/pokok-pokok-materi-statistik-1.html

[19] D. C. Montgomery, C. L. Jennings, and M. Kulahci, “Introduction to Time Series Analysis and Forecasting 3rd Edition”, 2024, Accessed: Jan. 14, 2026. [Online]. Available: https://www.wiley.com/en-us/Introduction+to+Time+Series+Analysis+and+Forecasting%2C+3rd+Edition-p-9781394186709

[20] A. Hajjah and Y. N. Marlim, “Analisis error terhadap peramalan data penjualan”, Techno.com, vol. 20, no. 1, p. 1, Feb. 2021, doi: 10.33633/TC.V20I1.4054.