PEMODELAN BANDWIDTH NIR PADA GAUSS-GWR BERDASARKAN INTERPOLASI IDW (Studi Kasus : Bandung Timur)
East Bandung is a highly developed region, such as adequate infrastructure so that many people want to use land as a place to live and industrial area. In this area, land is a rare and very productive item consider to this area near the government of West Java, it promising as a property business...
Saved in:
| Main Author: | |
|---|---|
| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/39875 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | East Bandung is a highly developed region, such as adequate infrastructure so that
many people want to use land as a place to live and industrial area. In this area, land
is a rare and very productive item consider to this area near the government of West
Java, it promising as a property business development. With the increase in
population, demand for land increasing but the land area in the city of Bandung is
limited. As a result, the price of land is increasing every year. Based on Circular of
the Ministry of Finance of the Republic of Indonesia, Director General of Tax Number
KEP 55 / PJ.6 / 1999 concerning Technical Guidelines for Determining NIR Value.
Determination of NIR to go through the preparation stage, selling price data
collection, data compilation, data recapitulation and plot transaction data on ZNT
work maps, data analysis, making ZNT map, and ZNT & NIR analysis books, to
determine the price of land in an area requires a relatively long time and requires a
relatively expensive cost. In this research, modeling of NIR bandwidth in the East
Bandung region uses Geograpically Weighted Regression (GWR) with Adaptive
Gaussian kernel type, then Interpolated with Inverse Distance Weighting (IDW),
which is interpolation that takes distance as weight. The NIR bandwidth can be
modeled continuously throughout the East Bandung region. Modeling in this research
resulted in the value of Root Mean Square Error (RMSE) of Rp306,622.4 / m2.
|
|---|