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https://doi.org/10.1063/1.5064...
Article . 2018 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1063/1.5064...
Article . 2018 . Peer-reviewed
Data sources: Crossref
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Forecasting Indonesian mortality rates using the Lee-Carter model and ANFIS method

Authors: A. H. A. Zili; S. Mardiyati; D. Lestari;

Forecasting Indonesian mortality rates using the Lee-Carter model and ANFIS method

Abstract

If information about the mortality rate for some future periods can be obtained in the present time then the financial planning and policy to be taken are expected to be better and directed. The model used to calculate the mortality rate in this paper is the Lee-Carter model. There are three parameters of the model, that is ax, bx and kt. Parameter ax will be estimate using average log mortality while bx and kt will be estimate using Singular Value Decomposition (SVD) method. Then the future mortality rates will be forecast with the use of the ARIMA (Auto Regressive Integrated Moving Average) method. Meanwhile, the whole process in this study will be implemented using software R. The final results of the forecasting will be presented in tabular and graphical form. The process show good results of forecasting mortality rate for several years or period based on the pattern and error less than 0.3 %.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
bronze