Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks

Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks

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Bibliographic Details
Main Author: Sarip, Abdul Ghani
Format: Thesis
Published: 2004
Subjects:
HD Industries
Land use
Labor
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id my-utm-ep.42454
record_format uketd_dc
spelling my-utm-ep.424542017-07-25T04:39:13Z Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks 2004 Sarip, Abdul Ghani HD Industries. Land use. Labor 2004 Thesis http://eprints.utm.my/id/eprint/42454/ http://libraryopac.utm.my/client/en_AU/main/search/results?qu=Pembangunan+sistem+automasi+penilaian+harta+tanah+berasaskan+GIS+dan+artificial+neural+networks&te= masters Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate Faculty of Geoinformation and Real Estate
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic HD Industries
Land use
Labor
spellingShingle HD Industries
Land use
Labor
Sarip, Abdul Ghani
Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
description
format Thesis
qualification_level Master's degree
author Sarip, Abdul Ghani
author_facet Sarip, Abdul Ghani
author_sort Sarip, Abdul Ghani
title Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
title_short Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
title_full Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
title_fullStr Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
title_full_unstemmed Pembangunan sistem automasi penilaian harta tanah berasaskan GIS dan artificial neural networks
title_sort pembangunan sistem automasi penilaian harta tanah berasaskan gis dan artificial neural networks
granting_institution Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate
granting_department Faculty of Geoinformation and Real Estate
publishDate 2004
_version_ 1747816773876449280

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