Main Article Content
Abstract
The demographic process cannot be inseparable from the mortality rate. The appropriate models for forecasting mortality rates are essential in assisting governments, companies, and other agencies in formulating policies or making decisions. As one of the countries with the highest death rate, Japan is influenced by several factors. This research uses the Generalized Lee-Carter Model), which is one of the developments of the Lee-Carter (LC) model. The Lee-Carter model was prevalent by Lee and Carter (1995) as an alternative that is suspected to predict the mortality rate of an area. The first step in this research is to formulate the Generalized Lee-Carter function. Through the function formula, the estimator value of the Generalized Lee-Carter model will be searched in the second stage. And the third stage, through the Generalized Lee-Carter model, will find the RMSE value and then use it in the fourth stage, namely forecasting the future period using ARIMA. The data in this study is facilitated through www.mortality.org, which is one of the Japanese population data. The result of the study showed that the RMSE value for females was 0.01670 and 0.016292 for males. So, it concluded that the Generalized Lee-Carter Model is great for forecasting mortality rates.
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References
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References
M.A.F. Alfana, M. Iffani, and W.A.N.P Hanif, “Mortalitas di Indonesia (Sejarah Masa Lalu dan Proyeksi ke Depan),” 05-Sep-2017. [Online]. Available: osf.io/2d7yk.
D.A. Swanson and J.S Siegel, The Methods and Materials of Demography, 2nd ed. Bingley, U.K.: Emerald Publishing, 2004.
A. Widiandari, “Fenomena Shoushika Di Jepang: Perubahan Konsep Anak,” Izumi, vol. 5, no. 1, pp. 32–39, 2016, doi:10.14710/izumi.5.1.32-39.
S.I. Trahutami, “Kasus Bunuh Diri pada Masyarakat Jepang (Penyebab dan Tren Dewasa Ini),” Kiryoku, vol. 1, no. 1, pp. 12–17, 2017, doi: https://doi.org/10.14710/kiryoku.v1i1.%p.
M.T.B. Karo, I. Hikmatullah, M.D. Puteri, Q.N. Aulia, and N.S. Shafira, “Fenomena Shoushika: Analisis Kebijakan Pemerintah Jepang Pada Era Kepemimpinan Shinzo Abe,” TransBORDERS: Internasional Relation Journal, vol. 4, no. 2, pp. 96–110, 2021, doi: https://doi.org/10.23969/transborders.v4i2.3939.
I.G. Nyoman, Y. Hartawan, and K.M. Pranata, “Peramalan Tingkat Kematian Penduduk Kabupaten Buleleng Menggunakan Model Cairns-Blake-Dowd (CBD),” Undiksha Press. Seminar Nasional Riset Inovatif, 2020, pp. 36–43.
R.D. Lee and L.R. Carter, “Modeling and Forecasting U.S. Mortality,” Journal of the American Statistical Association, vol. 87, no. 419, pp. 659-671, 1992, doi:10.2307/2290201.
A. Hunt and A.M. Villegas, “Robustness and Convergence in the Lee-Carter Model with Cohort Effects,” Insurance: Mathematics and Economics, vol. 64, pp. 186–202, 2015, doi: 10.1016/j.insmatheco.2015.05.004.
S. Tuljapurkar, N. Li, and C. Boe, “A Universal Pattern of Mortality Decline in the G7 Countries,” Nature, vol. 405, pp. 789–792, 2000, doi:10.1038/35015561.
Robinson et al., “City Research Online City, University of London Institutional Repository,” City Res. Online, vol. 37, no. 9, pp. 1591–1601, 2008.
A. Renshaw and S. Haberman, “Lee-Carter Mortality Forecasting: A Parallel Generalized Linear Modeling Approach for England and Wales Mortality Projections,” Journal of the Royal Statistical Society. Series C (Applied Statistics), vol. 52, no. 1, pp. 119–137, 2003, doi:10.1111/1467-987600393.
A.E. Renshaw and S. Haberman, “A Cohort-Based Extension to the Lee-Carter Model for Mortality Reduction Factors,” Insurance: Mathematics and Economics, vol. 38, no. 3, pp. 556–570, 2006, doi:10.1016/j.insmatheco.2005.12.001.
Z. Butt, S. Haberman, and H.L. Shang, “Lee-Carter Mortality Models using Iterative Fitting Algorithms,” Package ‘ilc’ Version 1.0, Nov. 19, 2014. [Online]. Available http://cran.nexr.com/web/packages/ilc/ilc.pdf.
A.M. Villegas, P. Millossovich, and V.K. Kaishev, “StMoMo: Stochastic Mortality Modeling in R,” Journal of Statistical Software, vol. 84, no. 3, 2018, doi:10.18637/jss.v084.i03.
S. Haberman and A. Renshaw, “A Comparative Study of Parametric Mortality Projection Models,” Insurance: Mathematics and Economics, vol. 48, no. 1, pp. 35–55, 2011, doi:10.1016/j.insmatheco.2010.09.003.