Loading…

Utilization of Artificial Neural Network and GIS for property market valuation

The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGI...

Full description

Saved in:
Bibliographic Details
Main Authors: Samad, A M, Zain, M A M, Maarof, I, Hashim, K A, Adnan, R
Format: Conference Proceeding
Language:eng ; jpn
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 331
container_issue
container_start_page 325
container_title
container_volume
creator Samad, A M
Zain, M A M
Maarof, I
Hashim, K A
Adnan, R
description The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGIS 9.3 software. It purpose is to facilities the access and searching the information. Before this, information about property using old files and Microsoft Excel but using GIS spatial and attribute data will be shown. To display property market valuations in Google Earth of each category like residential that have divided into two; double storey house and bungalow, commercial and industrial areas, data that are needed such as property data from JPPH, land parcel from JUPEM, and land use from MBSA. From the property market valuation, can determine high or low market value based on attribute data. In visualization, can analysis the factors of highest and lowest market value based on geographic that have been produced using ArcGIS ang Google Earth. After that, the detail analysis also can determine using ArcGIS 9.3 software such as using overlay and proximity analysis tools. From that data, changes of the market value can be determined the increase market value for each categories of property. Analysis of the property market valuation is performed using mathematical software like Microsoft Excel, SPSS and Artificial Neural Networks (ANN) software. Microsoft Excel produces analysis in graph and bar chart of highest and lowest market valuation for each category of property. After that, the changes of the market valuation also can determine. SPSS shows the relationship of property market value with an area. Lastly, using ANN software can predict property market valuation based on algorithms. For prediction property market valuation just not in qualitative factors but can variable in quantitative to make a good analysis for each property categories; residential, commercial and industry.
doi_str_mv 10.1109/CSPA.2011.5759897
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5759897</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5759897</ieee_id><sourcerecordid>5759897</sourcerecordid><originalsourceid>FETCH-LOGICAL-i156t-26f5b5eff324d22113900b3ffc0d66881c16663c5a7212c624c06ccebfd9ae833</originalsourceid><addsrcrecordid>eNo1kNFKwzAYhSMiqLMPIN7kBVrzJ83f5LIUnYMxhbnrkaYJxNW1ZJkyn94x57n5ODcfh0PIPbACgOnHZvlWF5wBFLKSWunqgmS6UoDAVVkCh0ty-19KvCbZbvfBjkHUiusbslil0Icfk8KwpYOndUzBBxtMTxduH09I30PcULPt6HS2pH6IdIzD6GI60E8TNy7RL9PvT4o7cuVNv3PZmROyen56b17y-et01tTzPIDElHP0spXOe8HLjnMAoRlrhfeWdYhKgQVEFFaaigO3yEvL0FrX-k4bp4SYkIc_b3DOrccYjkMO6_MF4herj0-c</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Utilization of Artificial Neural Network and GIS for property market valuation</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Samad, A M ; Zain, M A M ; Maarof, I ; Hashim, K A ; Adnan, R</creator><creatorcontrib>Samad, A M ; Zain, M A M ; Maarof, I ; Hashim, K A ; Adnan, R</creatorcontrib><description>The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGIS 9.3 software. It purpose is to facilities the access and searching the information. Before this, information about property using old files and Microsoft Excel but using GIS spatial and attribute data will be shown. To display property market valuations in Google Earth of each category like residential that have divided into two; double storey house and bungalow, commercial and industrial areas, data that are needed such as property data from JPPH, land parcel from JUPEM, and land use from MBSA. From the property market valuation, can determine high or low market value based on attribute data. In visualization, can analysis the factors of highest and lowest market value based on geographic that have been produced using ArcGIS ang Google Earth. After that, the detail analysis also can determine using ArcGIS 9.3 software such as using overlay and proximity analysis tools. From that data, changes of the market value can be determined the increase market value for each categories of property. Analysis of the property market valuation is performed using mathematical software like Microsoft Excel, SPSS and Artificial Neural Networks (ANN) software. Microsoft Excel produces analysis in graph and bar chart of highest and lowest market valuation for each category of property. After that, the changes of the market valuation also can determine. SPSS shows the relationship of property market value with an area. Lastly, using ANN software can predict property market valuation based on algorithms. For prediction property market valuation just not in qualitative factors but can variable in quantitative to make a good analysis for each property categories; residential, commercial and industry.</description><identifier>ISBN: 1612844146</identifier><identifier>ISBN: 9781612844145</identifier><identifier>EISBN: 9781612844121</identifier><identifier>EISBN: 161284412X</identifier><identifier>EISBN: 1612844138</identifier><identifier>EISBN: 9781612844138</identifier><identifier>DOI: 10.1109/CSPA.2011.5759897</identifier><language>eng ; jpn</language><publisher>IEEE</publisher><subject>Artificial Neural Network ; Artificial neural networks ; Cities and towns ; Cost accounting ; Earth ; Geographic Information Systems ; GIS ; Google ; Property Valuation ; Software</subject><ispartof>2011 IEEE 7th International Colloquium on Signal Processing and its Applications, 2011, p.325-331</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5759897$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5759897$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Samad, A M</creatorcontrib><creatorcontrib>Zain, M A M</creatorcontrib><creatorcontrib>Maarof, I</creatorcontrib><creatorcontrib>Hashim, K A</creatorcontrib><creatorcontrib>Adnan, R</creatorcontrib><title>Utilization of Artificial Neural Network and GIS for property market valuation</title><title>2011 IEEE 7th International Colloquium on Signal Processing and its Applications</title><addtitle>CSPA</addtitle><description>The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGIS 9.3 software. It purpose is to facilities the access and searching the information. Before this, information about property using old files and Microsoft Excel but using GIS spatial and attribute data will be shown. To display property market valuations in Google Earth of each category like residential that have divided into two; double storey house and bungalow, commercial and industrial areas, data that are needed such as property data from JPPH, land parcel from JUPEM, and land use from MBSA. From the property market valuation, can determine high or low market value based on attribute data. In visualization, can analysis the factors of highest and lowest market value based on geographic that have been produced using ArcGIS ang Google Earth. After that, the detail analysis also can determine using ArcGIS 9.3 software such as using overlay and proximity analysis tools. From that data, changes of the market value can be determined the increase market value for each categories of property. Analysis of the property market valuation is performed using mathematical software like Microsoft Excel, SPSS and Artificial Neural Networks (ANN) software. Microsoft Excel produces analysis in graph and bar chart of highest and lowest market valuation for each category of property. After that, the changes of the market valuation also can determine. SPSS shows the relationship of property market value with an area. Lastly, using ANN software can predict property market valuation based on algorithms. For prediction property market valuation just not in qualitative factors but can variable in quantitative to make a good analysis for each property categories; residential, commercial and industry.</description><subject>Artificial Neural Network</subject><subject>Artificial neural networks</subject><subject>Cities and towns</subject><subject>Cost accounting</subject><subject>Earth</subject><subject>Geographic Information Systems</subject><subject>GIS</subject><subject>Google</subject><subject>Property Valuation</subject><subject>Software</subject><isbn>1612844146</isbn><isbn>9781612844145</isbn><isbn>9781612844121</isbn><isbn>161284412X</isbn><isbn>1612844138</isbn><isbn>9781612844138</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kNFKwzAYhSMiqLMPIN7kBVrzJ83f5LIUnYMxhbnrkaYJxNW1ZJkyn94x57n5ODcfh0PIPbACgOnHZvlWF5wBFLKSWunqgmS6UoDAVVkCh0ty-19KvCbZbvfBjkHUiusbslil0Icfk8KwpYOndUzBBxtMTxduH09I30PcULPt6HS2pH6IdIzD6GI60E8TNy7RL9PvT4o7cuVNv3PZmROyen56b17y-et01tTzPIDElHP0spXOe8HLjnMAoRlrhfeWdYhKgQVEFFaaigO3yEvL0FrX-k4bp4SYkIc_b3DOrccYjkMO6_MF4herj0-c</recordid><startdate>201103</startdate><enddate>201103</enddate><creator>Samad, A M</creator><creator>Zain, M A M</creator><creator>Maarof, I</creator><creator>Hashim, K A</creator><creator>Adnan, R</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201103</creationdate><title>Utilization of Artificial Neural Network and GIS for property market valuation</title><author>Samad, A M ; Zain, M A M ; Maarof, I ; Hashim, K A ; Adnan, R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i156t-26f5b5eff324d22113900b3ffc0d66881c16663c5a7212c624c06ccebfd9ae833</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng ; jpn</language><creationdate>2011</creationdate><topic>Artificial Neural Network</topic><topic>Artificial neural networks</topic><topic>Cities and towns</topic><topic>Cost accounting</topic><topic>Earth</topic><topic>Geographic Information Systems</topic><topic>GIS</topic><topic>Google</topic><topic>Property Valuation</topic><topic>Software</topic><toplevel>online_resources</toplevel><creatorcontrib>Samad, A M</creatorcontrib><creatorcontrib>Zain, M A M</creatorcontrib><creatorcontrib>Maarof, I</creatorcontrib><creatorcontrib>Hashim, K A</creatorcontrib><creatorcontrib>Adnan, R</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Samad, A M</au><au>Zain, M A M</au><au>Maarof, I</au><au>Hashim, K A</au><au>Adnan, R</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Utilization of Artificial Neural Network and GIS for property market valuation</atitle><btitle>2011 IEEE 7th International Colloquium on Signal Processing and its Applications</btitle><stitle>CSPA</stitle><date>2011-03</date><risdate>2011</risdate><spage>325</spage><epage>331</epage><pages>325-331</pages><isbn>1612844146</isbn><isbn>9781612844145</isbn><eisbn>9781612844121</eisbn><eisbn>161284412X</eisbn><eisbn>1612844138</eisbn><eisbn>9781612844138</eisbn><abstract>The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGIS 9.3 software. It purpose is to facilities the access and searching the information. Before this, information about property using old files and Microsoft Excel but using GIS spatial and attribute data will be shown. To display property market valuations in Google Earth of each category like residential that have divided into two; double storey house and bungalow, commercial and industrial areas, data that are needed such as property data from JPPH, land parcel from JUPEM, and land use from MBSA. From the property market valuation, can determine high or low market value based on attribute data. In visualization, can analysis the factors of highest and lowest market value based on geographic that have been produced using ArcGIS ang Google Earth. After that, the detail analysis also can determine using ArcGIS 9.3 software such as using overlay and proximity analysis tools. From that data, changes of the market value can be determined the increase market value for each categories of property. Analysis of the property market valuation is performed using mathematical software like Microsoft Excel, SPSS and Artificial Neural Networks (ANN) software. Microsoft Excel produces analysis in graph and bar chart of highest and lowest market valuation for each category of property. After that, the changes of the market valuation also can determine. SPSS shows the relationship of property market value with an area. Lastly, using ANN software can predict property market valuation based on algorithms. For prediction property market valuation just not in qualitative factors but can variable in quantitative to make a good analysis for each property categories; residential, commercial and industry.</abstract><pub>IEEE</pub><doi>10.1109/CSPA.2011.5759897</doi><tpages>7</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1612844146
ispartof 2011 IEEE 7th International Colloquium on Signal Processing and its Applications, 2011, p.325-331
issn
language eng ; jpn
recordid cdi_ieee_primary_5759897
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Artificial Neural Network
Artificial neural networks
Cities and towns
Cost accounting
Earth
Geographic Information Systems
GIS
Google
Property Valuation
Software
title Utilization of Artificial Neural Network and GIS for property market valuation
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-14T23%3A28%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Utilization%20of%20Artificial%20Neural%20Network%20and%20GIS%20for%20property%20market%20valuation&rft.btitle=2011%20IEEE%207th%20International%20Colloquium%20on%20Signal%20Processing%20and%20its%20Applications&rft.au=Samad,%20A%20M&rft.date=2011-03&rft.spage=325&rft.epage=331&rft.pages=325-331&rft.isbn=1612844146&rft.isbn_list=9781612844145&rft_id=info:doi/10.1109/CSPA.2011.5759897&rft.eisbn=9781612844121&rft.eisbn_list=161284412X&rft.eisbn_list=1612844138&rft.eisbn_list=9781612844138&rft_dat=%3Cieee_6IE%3E5759897%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i156t-26f5b5eff324d22113900b3ffc0d66881c16663c5a7212c624c06ccebfd9ae833%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5759897&rfr_iscdi=true