Abstract

The real estate sector has been a key factor in development of economy in every country. The valuation of property is also vital for the real estate industry. Thus, this paper presents the best fitting model in conducting the valuation of residential real estate. The main objective of this work was to understand the standard valuation procedures by multiple regression approaches. The type of properties that are used in this study is condominiums that are located within Kuala Lumpur. Multiple regression approach is used in conducting the valuation for these condominiums selected as sample. The data were analyzed using SPSS software based on the dependent variable (asking price) and six independent variable, which were number of bedrooms, number of bathrooms, number of stories, square feet, distance towards rail station and distance towards KLCC. Results of this work showed that multiple regression approach can be utilized to model the value of residential real estate and key findings showed that that all of the independent variables contribute to the model except the distance towards rail station. Our analysis has indicated that the distance towards rail station does not affect the price of condominium in Kuala Lumpur.

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