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The land market price have tendency to increased, but the adjustment of NJOP doesn’t comply with the increasement. The number of land assessor and assessment time were not proportional to the amount of land and building, therefore it’s difficult doing an assessment for NJOP adjustment. The stu...

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Main Author: YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/20129
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:20129
spelling id-itb.:201292017-10-09T10:15:54Z#TITLE_ALTERNATIVE# YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/20129 The land market price have tendency to increased, but the adjustment of NJOP doesn’t comply with the increasement. The number of land assessor and assessment time were not proportional to the amount of land and building, therefore it’s difficult doing an assessment for NJOP adjustment. The study of characteristics of spatial and non-spatial factors using an Artificial Neural Network model (ANN) are expected to identify the most significant factors that influence the NJOP adjustments. Spatial factors consist the location from particular reference. Non-spatial factor consists of economic and social. Economic factors related by measured from per capita income and inflation rate. Social factors related to population density in the area. NJOP adjustments calculating spatial and non spatial factors using ANN results predictions close to real NJOP by 97.52%. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description The land market price have tendency to increased, but the adjustment of NJOP doesn’t comply with the increasement. The number of land assessor and assessment time were not proportional to the amount of land and building, therefore it’s difficult doing an assessment for NJOP adjustment. The study of characteristics of spatial and non-spatial factors using an Artificial Neural Network model (ANN) are expected to identify the most significant factors that influence the NJOP adjustments. Spatial factors consist the location from particular reference. Non-spatial factor consists of economic and social. Economic factors related by measured from per capita income and inflation rate. Social factors related to population density in the area. NJOP adjustments calculating spatial and non spatial factors using ANN results predictions close to real NJOP by 97.52%.
format Theses
author YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE
spellingShingle YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE
#TITLE_ALTERNATIVE#
author_facet YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE
author_sort YATHA PRADIPTA (NIM : 25113021); Pembimbing : Dr. Andri Hernandi, ST.,MT.; Dr. Ir. Asep Yusup , GEDE
title #TITLE_ALTERNATIVE#
title_short #TITLE_ALTERNATIVE#
title_full #TITLE_ALTERNATIVE#
title_fullStr #TITLE_ALTERNATIVE#
title_full_unstemmed #TITLE_ALTERNATIVE#
title_sort #title_alternative#
url https://digilib.itb.ac.id/gdl/view/20129
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