Handayani, Riny and Fuad, Anis (2016) POPULATION GROWTH MODEL IN BANTEN PROVINCE. In: Proceeding of International Conference on Social Politics 2016: THE CHALLENGES OF SOCIAL SCIENCES IN A CHANGING WORLD Vol.1. Jusuf Kalla School of Government (JKSG) Universitas Muhammadiyah Yogyakarta, Yogyakarta, pp. 459-467. ISBN 978-602-73900-1-0

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Abstract

Population growth can be seen from the quantitative and qualitative aspects. Both aspects are studied by observing the pattern, distribution, growth, and composition. The main variables of population growth are fertility, mortality and migration are factors that affect the dynamics of the component. Based on data analysis, models of population growth in Banten Province, are represented by two different areas in the aspect of the population. That is Pandeglang in the South of Banten and South Tangerang representing northern Banten also show a model of population growth differently. Pandeglang tends to have a model of population growth that is dominated by components of Fertility and Mortality or known as population growth natural (natural increase), which is inversely proportional to South Tangerang Municipal where components of Fertility and Mortality equally decreased and both already are at levels which are low, it can be ascertained that the influence is small on the rate of population growth, the migration component or the term non-natural population growth (nett migration) that in this case the dominating model of population growth. Fertility Conditions are still relatively high and mortality were also still in effect due to the health status of the population is low to focus mainly on the preparation of infrastructure development of Human Resources in Pandeglang, whereas the development plans in the region of South Tangerang Municipal dominated migration flows were strong also must special attention because the same effects that come along with the migration of which is the population density that directly affects environmental degradation, high crime rate, the growth of slums and rising unemployment.

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