Abstract
Mamminasata (Makassar, Maros, Gowa, Takalar) is one of the urban or metropolitan areas in Eastern Indonesia. Mamminasata as a strategic area with economic interests has an important role in the development of its city and surrounding areas. Meanwhile, the dynamic development of the city causes demands for space needs to increase, especially the need for residential land. The objectives of this study are to 1) know economic development in the Mamminasata district/city in 2001-2021 2) know the development of built-up land in the Mamminasata district/city in 2001-2021 and 3) know the influence and contribution of economic growth to the development of the Mamminasata region. The research location is Makassar City, Maros Regency, Gowa Regency and Takalar Regency. This type of research is descriptive quantitative qualitative. The required data is collected through literature studies in the form of secondary data, namely Gross Regional Domestic Product (GRDP) at constant prices 2010, and google earth images 2001-2021. The analysis used in the research is literature study analysis, qualitative quantitative descriptive, basic statistics, LQ-DLQ, Shift Share, and multiple linear regression analysis. The result of this study is that during 2001-2021 the real income of the Mamminasata Region continued to increase. With the highest growth rate in Gowa Regency. Makassar City only has one leading sector, Maros Regency has two leading sectors, Gowa Regency has three leading sectors, and Takalar Regency has two leading sectors. Only Kabupaten Maros experienced a shift in economic structure from the tertiary sector to the primary sector in 2021 due to a significant economic decline. Spatially, sub-districts that are adjacent or directly adjacent to Makassar City have the most significant built-up land growth with developments following the main road network pattern. Based on the results of multiple linear regression analysis, it shows that there is no significant influence between the independent variables on the dependent variable either jointly or partially individually. Then the t-test was conducted again between tertiary variables and built-up land and showed a significant influence with a contribution of 33% to built-up land.
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