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The value of land can be viewed from various aspects. One aspect is the location of the land is location. The location of land usually associated with the proximity of the land to certain facilities. in this research, it is discussed the proximity to land and air transportation facilities. Land and...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/22887 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The value of land can be viewed from various aspects. One aspect is the location of the land is location. The location of land usually associated with the proximity of the land to certain facilities. in this research, it is discussed the proximity to land and air transportation facilities. Land and air transportation facilities could lead to positive impacts and negative impacts on land values. This research objective is to develop land value model that can accommodate impact of existence of land and air transport facilities. In this research, modeling the value of land uses Geographically Weighted Regression (GWR). Modelling the value of land by GWR will get a model in each parcel. Transport facilities used as a parameter for the assessment of land value is the radius of land parcel with airport, radius of land parcel with railway, road width, distance between land parcel and station, distance between land parcel and bus station, distance between land parcel and shelter, distance between land parcel and market, distance between land parcel and downton, and land parcel area. GWR models were used for this study using a gaussian kernel fixed and fixed bisquare with optimum bandwidth search using the Akaike Information Criterion (AIC) and Cross Validation (CV). In addition to the GWR, it is also performed by linier regression modeling. Analysis of the model is done by looking at the residue between a dependent variable, which is, mean indication value (NIR) and Land Value Zone (ZNT) of the National Land Agency (BPN) Comparing also performed every parcel with field surveys. The model chosen to represent the Village area Campaka is GWR with fixed gaussian and AIC. Selection is based on the root mean square error (RMSE) and land value condition. |
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