Analisis Tingkat Kapitalisasi Sektor Perumahan dan Faktor-faktor yang Mempengaruhinya di Kecamatan Mataram NTB

This research aims to analyze the property capitalization rates to determine the pattern of housing rent in District of Mataram and to analyze the significance of factors that influence it. In this research, factors wich analyzed are distance to the city center, lease term, availability of telephone...

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Bibliographic Details
Main Authors: , SAFWIRA GUNA PUTRA, , Dr. Tri Widodo, M. Ec. Dev.
Format: Thesis
Published: [Yogyakarta] : Universitas Gadjah Mada 2012
Subjects:
ETD
Description
Summary:This research aims to analyze the property capitalization rates to determine the pattern of housing rent in District of Mataram and to analyze the significance of factors that influence it. In this research, factors wich analyzed are distance to the city center, lease term, availability of telephone and PDAM facilities, site area per square feet, building area per square feet, building conditions and the number of floors. This research used cross section data through purposive sampling that cover all villages that are West Pagutan, East Pagutan, Pagutan, Punia, Pagesangan, West Pagesangan, East Pagesangan, East Mataram and Pejanggik. This research use 70 samples and the collected data was primary data from field research and secondary data obtained from REI Mataram, real estate agents and The Office of Property Tax Service (PBB) Mataram. The analysis method used in this research was divided to two method, the first method was statistical analysis that used to measure central tendency and dispersion, regressivity/progressivity. The second method on this analysis was multiple regression analysis, used to determine level of significance of factors mentioned above and also determine the best estimator model. The empirical results shows that average overall capitalization rates is 5.89 percent, while the average capitalization rate for each village is quite varied from 4.58 percent to 7.46 percent and tend to regressive against the market price. The results of regression analysis from the chosen model shows that eight independent variables included in the model there are five variables that significantly influence the dependent variable, while the three variables had no significant effect, with explanation power (R2) 36.18 percent.