Dinamika Komposisi Penduduk: Dampak Potensial Pandemi Covid-19 terhadap Demografi di Indonesia

https://doi.org/10.22146/jp.63351

Sari Lestari Zainal Ridho(1*), Syaiful Aqli Yusuf(2)

(1) Politeknik Negeri Sriwijaya, Palembang, Sumatera Selatan.
(2) Politeknik Negeri Sriwijaya, Palembang, Sumatera Selatan.
(*) Corresponding Author

Abstract


This study aims to observe and analyze the development of trend of COVID 19 and its potential impact on changes in population composition based on age structure in Indonesia. Using Covid-19 cases data obtained from the Ministry of Health of the Republic of Indonesia and forecasting method by comparing several models, the study findings indicate that the trend shows increasing cases and will continue to rise as long as there is no intervention. Experimentally, the mortality cases dominated by the male and elderly population are the possible causes to the change in the composition of the population based on the age structure. Hence, it is necessary to immediately intervene it in the form of policies in health sector that are more appropriate to maintain the sustainability of Indonesia’s human resources since demographic dynamics, particularly in terms of sex, age structure, and health conditions, also have a significant macroeconomic implication.


Keywords


covid-19; demography; mortality; human resources

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References

Aslam, M. (2020). Using the kalman filter with Arima for the COVID-19 pandemic dataset of Pakistan. Data in Brief, 31, 105854. https://doi.org/10.1016/j. dib.2020.105854.

Bender, L. C. (2018). Age structure and population dynamics. In Encyclopedia of Ecology (2nd ed., Issue October 2017). Elsevier Inc. https://doi. org/10.1016/B978-0-12-409548- 9.10925-X.

Bloom, D. E., & Williamson, J. G. (1998). Demographic transitions and economic miracles in emerging Asia. World Bank Economic Review, 12(3), 419–455. https://doi.org/10.1093/ wber/12.3.419.

Duan, X., & Zhang, X. (2020). ARIMA modelling and forecasting of irregularly patterned COVID-19 outbreaks using Japanese and South Korean data. Data in Brief, 31, 105779. https://doi. org/10.1016/j.dib.2020.105779.

Goh, S. K., McNown, R., & Wong, K. N. (2020). Macroeconomic implications of population aging: Evidence from Japan. Journal of Asian Economics, 68, 101198. https://doi.org/10.1016/j. asieco.2020.101198.

Hanke, John E., Wichern, D. (2014). Business Forecasting. In Pearson Education Limited. Pearson Education Limited. https://doi.org/10.16309/j.cnki. issn.1007-1776.2003.03.004.

Hibon, M., & Makridakis, S. (2000). The M3- Competition: Results, conclusions and implications. International Journal of Forecasting, 16, 451–476.

Ika. (2020). Pakar UGM Paparkan Penyebab Lansia Rentan Terinfeksi Covid. April. https://ugm.ac.id/id/berita/19320- pakar-ugm-paparkan-penyebab- lansia-rentan-terinfeksi-covid.

Karagiannis, R., & Karagiannis, G. (2020). Constructing composite indicators with Shannon entropy: The case of Human Development Index. Socio- Economic Planning Sciences, 70(January 2018), 100701. https:// doi.org/10.1016/j.seps.2019.03.007.

KEMENKES, R. (2020). BERANDA Indonesia Masuki Periode Aging Population LIHAT VERSI MOBILE. Kemenkes, 1–4. https://www.kemkes. go.id/article/view/19070500004/ indonesia-masuki-periode-aging- population.html.

Khan, F. M., & Gupta, R. (2020). ARIMA and NAR based Prediction Model for Time Series Analysis of COVID-19 cases in India. Journal of Safety Science and Resilience, 1(April), 12–18. https:// doi.org/10.1016/j.jnlssr.2020.06.007.

Kırbaş, İ., Sözen, A., Tuncer, A. D., & Kazancıoğlu, F. Ş. (2020). Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches.

Chaos, Solitons and Fractals, 138. https://doi.org/10.1016/j.chaos. 2020.110015.

Lieber, J., Clarke, L., Timæus, I. M., Mallinson, P. A. C., & Kinra, S. (2020). Changing family structures and self-rated health of India’s older population (1995-96 to 2014). SSM - Population Health, 11(August 2019), 100572. https://doi. org/10.1016/j.ssmph.2020.100572.

McGillivray, M. (1991). The human development index: Yet another redundant composite development indicator? World Development, 19(10), 1461–1468. https://doi.org/10. 1016/0305-750X(91)90088-Y.

Peña, W. (2020). Population Aging and Public Finances: Evidence from El Salvador. Journal of the Economics of Ageing, 17(April), 100260. https:// doi.org/10.1016/j.jeoa.2020.100260.

Persson, E., & Tinghög, G. (2020). Opportunity cost neglect in public policy. Journal of Economic Behavior and Organization, 170, 301–312. https://doi.org/10.1016/j.jebo. 2019.12.012.

Putranto, Windhiarso Ponco Adi;Larasaty, Putri;Kurniasih, Anna; Pratiwi, Aprilia Ira; Saputri, Valent Gigih; Meilianingsih, T. (2020). Hasil Survei Sosial Demografi Dampak Covid-19 2020 (S. I. Statistik (ed.)). Badan Pusat Statistik. https://doi.org/10.16309/j. cnki.issn.1007-1776.2003.03.004

Republik Indonesia, Kementerian Kesehatan. (2020a). COVID-19 dalam Angka Kondisi 10 Juni 2020. www.kemkes.go.id.

Republik Indonesia, Kementerian Kesehatan. (2020b). COVID-19 dalam Angka Kondisi 27 Mei 2020. www.kemkes.go.id.

Republik Indonesia, Kementerian Kesehatan. (2020c). COVID-19 dalam Angka Kondisi 3 Juni 2020.

www.kemkes.go.id.

Republik Indonesia, Kementrian Kesehatan.

(2020). COVID-19 dalam Angka Kondisi 19 Mei 2020. www.kemkes. go.id.

Singh, S., Parmar, K. S., Makkhan, S. J. S., Kaur, J., Peshoria, S., & Kumar, J. (2020). Study of ARIMA and least square support vector machine (LS- SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries. Chaos, Solitons and Fractals, 139. https://doi. org/10.1016/j.chaos.2020.110086.

The World Bank. (2014). The Economic Impact of the 2014 Ebola Epidemic: Short and Medium Term Estimates for West Africa. The World Bank. https:// doi.org/10.1596/978-1-4648-0438-0.



DOI: https://doi.org/10.22146/jp.63351

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