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Results for Topics : "Population"
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Unjuran kadar kesuburan penduduk di Malaysia dengan menggunakan pemodelan kebarangkalian Bayesian
Item Type: Conference or Workshop Item
Editor:
Year: 00/11/2025
Abstract: Bayesian Probabilistic Modelling provides a more accurate, flexible and probability-based method of fertility rate projection. This method is not limited to a single projected value, but produces probability distributions and confidence intervals (80%/95%) for various future scenarios. This approach is widely used by the United Nations (UN DESA) for global and national population projections. It allows policymakers to assess risks, uncertainties and policy impacts more comprehensively than deterministic methods. As a national agency that advises the Government in the field of demography and population, LPPKN is recommended to adopt the Bayesian method to improve the accuracy and reliability of the country's fertility rate projections and support long-term planning related to population and family
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Unmet fertility desires: a case study among working women in Selangor, Kuala Lumpur and Putrajaya
Item Type: Scientific Poster
Editor:
Year: 00/00/2015
Abstract: Malaysia population will be estimated to reach aging population by 2035. This projection was inflated by many factors. One of the factors that influence the demographic changes is fertility. Malaysia is already at the level of substitute of total fertility rate (TFR) and this number was decreasing by time. From previous studies showed that fertility desires can predict the subsequent fertility behavior. There is always a disjoint between desired and actual family size. The difference between the actual number of children and the desired number of children is called unmet fertility desired. Since Malaysia is having a declining Total Fertility Rate (TFR), the dynamics of the difference between actual number of children and the desired number of children must be examined. Past research on fertility desires found that the rising age at marriage, economic factors, infertility, and social factors were the important factors that will affect the fertility desired. Also, education level, early and late childbearing, locality and household income influenced the unmet fertility desires.
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