Model penilaian massa berasaskan sistem maklumat geografi bersepadu bagi tujuan kadaran
Generally in Malaysia, the property valuation method for an assessment purposes are still using the traditional single valuation method. This contributes to the inconsistency of assessed value because location factors are not considered objectively. In order to eliminate this weakness, the suitable...
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| 格式: | Thesis |
| 語言: | English |
| 出版: |
2012
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| 主題: | |
| 在線閱讀: | http://eprints.utm.my/id/eprint/28152/4/RazwinNoorRazaliMFKSG2010.pdf |
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| 總結: | Generally in Malaysia, the property valuation method for an assessment purposes are still using the traditional single valuation method. This contributes to the inconsistency of assessed value because location factors are not considered objectively. In order to eliminate this weakness, the suitable solution is by using mass appraisal. Mass appraisal is a systematic method to estimate the value in the scale and scope that is greater than a single assessment. Data is the most important element in developing a model. The utilization of all the data from each department within local authority can be done by the application of Enterprise GIS (EGIS) concept. Therefore, the main objective of this research was to develop a mass appraisal model based on the application of Enterprise GIS (EGIS) concept. In order to achieve the objective, Majlis Perbandaran Kulai was chosen as a study area. As many as 504 transaction data between 2008 and 2011 representing 30 housing areas were utilized and analyzed. Result shows the ability of EGIS to generate location variables factor through spatial analysis includes Buffer and Overlay analysis. These location variables factor will be used in forming mass appraisal model. Based on the results, EGIS produced 25 location variables factor for the development of mass appraisal model. In addition, EGIS is capable to produce extra mass appraisal model not than just OLS model which looking at the whole, in terms as Global perspective, but focus on Locally perspective such as GWR model. This study had shown that the model from GWR is better than the OLS model even though the R2 value acquired did not largely differentiate |
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