Andika Putra, Muhammad Rafael
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Estimation of Gompertz Mortality Parameter Models on Indonesian Population Mortality Table 2023 Andika Putra, Muhammad Rafael; Nurjannah, Nurjannah; Kurniawaty, Mila
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.33319

Abstract

The research article discuss Gompertz Mortality Law parameter estimation using several methods to get the best models. The data based from Indonesian population mortality table or called Tabel Mortalitas Penduduk Indonesia (TMPI) 2023. Parameter estimation using several methods, includes Nonlinear Least Square (NLLS) with the Gauss-Newton algorithm, Weighted Least Squares (WLS), and Poisson Regression. Model validation is done by calculating root mean square error (RMSE) to determine the most accurate method. The analysis includes calculation of values in the mortality table, transformation of the gompertz model, estimated parameters with each method, and RMSE calculation. In the WLS method, the estimation is carried out by transformation of natural logarithms from the force of mortality function, then minimizes the number of squares of error, with ???????? as weight and forming the ???????? function and maximizing the logordered function on Poisson regression. Model accuracy is assessed from the suitability between the ???????? function value of the model results with the ???????? value in TMPI, both visually and mathematically through RMSE. The analysis results show that the NLLS method with the Gauss-Newton algorithm produces the most accurate Gompertz model.