Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad
Real estate is complex and its value is influenced by many characteristics. However, the current practice in Malaysia shows that historical characteristics have not been given primary consideration in determining the value of heritage property. Thus, the accuracy of the values produced is questionab...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/74427/1/74427.pdf https://ir.uitm.edu.my/id/eprint/74427/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uitm.ir.74427 |
---|---|
record_format |
eprints |
spelling |
my.uitm.ir.744272023-03-27T01:37:05Z https://ir.uitm.edu.my/id/eprint/74427/ Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad Ja’afar, Nur Shahirah Mohamad, Junainah Special classes of buildings Shophouses Real estate is complex and its value is influenced by many characteristics. However, the current practice in Malaysia shows that historical characteristics have not been given primary consideration in determining the value of heritage property. Thus, the accuracy of the values produced is questionable. This paper aims to see whether the historical characteristics give significance values toward shophouses at North-East of Penang Island, Malaysia. Several Machine Learning algorithms have been developed, namely Random Forest Regressor, Decision Tree Regressor, Lasso Regressor, Ridge Regressor and Linear Regressor. The result shows that the Random Forest Regressor with historical characteristics is the best fitting model with higher values of adjusted R-Squared (R²) and lowest value of Root Mean Square Error. This indicates the historical characteristics contribute to the significance value of heritage property. By considering historical characteristics, it can contribute to the accuracy of the value predicted. 2021 Conference or Workshop Item NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/74427/1/74427.pdf Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad. (2021) In: Virtual Go-Green: Conference and Publication (V-GoGreen 2020), 29-30 September 2020, Universiti Teknologi MARA, Cawangan Perak Kampus Seri Iskandar. |
institution |
Universiti Teknologi Mara |
building |
Tun Abdul Razak Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Mara |
content_source |
UiTM Institutional Repository |
url_provider |
http://ir.uitm.edu.my/ |
language |
English |
topic |
Special classes of buildings Shophouses |
spellingShingle |
Special classes of buildings Shophouses Ja’afar, Nur Shahirah Mohamad, Junainah Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
description |
Real estate is complex and its value is influenced by many characteristics. However, the current practice in Malaysia shows that historical characteristics have not been given primary consideration in determining the value of heritage property. Thus, the accuracy of the values produced is questionable. This paper aims to see whether the historical characteristics give significance values toward shophouses at North-East of Penang Island, Malaysia. Several Machine Learning algorithms have been developed, namely Random Forest Regressor, Decision Tree Regressor, Lasso Regressor, Ridge Regressor and Linear Regressor. The result shows that the Random Forest Regressor with historical characteristics is the best fitting model with higher values of adjusted R-Squared (R²) and lowest value of Root Mean Square Error. This indicates the historical characteristics contribute to the significance value of heritage property. By considering historical characteristics, it can contribute to the accuracy of the value predicted. |
format |
Conference or Workshop Item |
author |
Ja’afar, Nur Shahirah Mohamad, Junainah |
author_facet |
Ja’afar, Nur Shahirah Mohamad, Junainah |
author_sort |
Ja’afar, Nur Shahirah |
title |
Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
title_short |
Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
title_full |
Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
title_fullStr |
Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
title_full_unstemmed |
Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad |
title_sort |
application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / nur shahirah ja’afar and junainah mohamad |
publishDate |
2021 |
url |
https://ir.uitm.edu.my/id/eprint/74427/1/74427.pdf https://ir.uitm.edu.my/id/eprint/74427/ |
_version_ |
1761622487227957248 |
score |
13.18916 |