Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin

The Klang Valley region provides a diverse range of living and employment options, resulting in an increasing demand for residential accommodation. However, due to the immense scope of the area, it is difficult for home buyers to analyze all available residence options. The Residence in Klang Valley...

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Main Author:	Faizal Azrin, Nuha Batrisyia
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Capability maturity model (Computer software) Software engineering
Online Access:	https://ir.uitm.edu.my/id/eprint/96389/1/96389.pdf
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id	my-uitm-ir.96389
record_format	uketd_dc
spelling	my-uitm-ir.963892024-06-05T03:58:12Z Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin 2024 Faizal Azrin, Nuha Batrisyia Capability maturity model (Computer software). Software engineering The Klang Valley region provides a diverse range of living and employment options, resulting in an increasing demand for residential accommodation. However, due to the immense scope of the area, it is difficult for home buyers to analyze all available residence options. The Residence in Klang Valley Recommendation System Using Collaborative Filtering project addresses the difficulties individuals face when looking for suitable residential properties in Malaysia's developing Klang Valley region. By assessing the similarity between individuals or things based on their rating data, collaborative filtering has shown great accuracy in recommender systems. Collaborative filtering identifies user trends and similarities by assessing user preferences, historical data, and property information, and then provides customized residence options that fit with individual tastes and requirements. This system aims to simplify the property search process, improve the overall user experience, and help individuals in discovering residential homes that meet their needs across the Klang Valley's different districts. The project will be separated into five phases to ensure the project will be done smoothly which are preliminary study, design, system development, evaluation, and documentation. The system architecture, flowchart, and GUI prototype will be useful references during the development phase. The system's accuracy is assessed through evaluation. The algorithm's recommendation accuracy is evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), assuring accurate choices for users. Finally, the "Residence in Klang Valley Recommendation System Using Collaborative Filtering" intends to provide a helpful tool for home seekers while also contributing to the progress of the real estate domain in the Klang Valley region. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96389/ https://ir.uitm.edu.my/id/eprint/96389/1/96389.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Ali, Fatimah Zaharah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Ali, Fatimah Zaharah
topic	Capability maturity model (Computer software) Software engineering
spellingShingle	Capability maturity model (Computer software) Software engineering Faizal Azrin, Nuha Batrisyia Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
description	The Klang Valley region provides a diverse range of living and employment options, resulting in an increasing demand for residential accommodation. However, due to the immense scope of the area, it is difficult for home buyers to analyze all available residence options. The Residence in Klang Valley Recommendation System Using Collaborative Filtering project addresses the difficulties individuals face when looking for suitable residential properties in Malaysia's developing Klang Valley region. By assessing the similarity between individuals or things based on their rating data, collaborative filtering has shown great accuracy in recommender systems. Collaborative filtering identifies user trends and similarities by assessing user preferences, historical data, and property information, and then provides customized residence options that fit with individual tastes and requirements. This system aims to simplify the property search process, improve the overall user experience, and help individuals in discovering residential homes that meet their needs across the Klang Valley's different districts. The project will be separated into five phases to ensure the project will be done smoothly which are preliminary study, design, system development, evaluation, and documentation. The system architecture, flowchart, and GUI prototype will be useful references during the development phase. The system's accuracy is assessed through evaluation. The algorithm's recommendation accuracy is evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), assuring accurate choices for users. Finally, the "Residence in Klang Valley Recommendation System Using Collaborative Filtering" intends to provide a helpful tool for home seekers while also contributing to the progress of the real estate domain in the Klang Valley region.
format	Thesis
qualification_level	Bachelor degree
author	Faizal Azrin, Nuha Batrisyia
author_facet	Faizal Azrin, Nuha Batrisyia
author_sort	Faizal Azrin, Nuha Batrisyia
title	Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
title_short	Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
title_full	Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
title_fullStr	Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
title_full_unstemmed	Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin
title_sort	residence in klang valley recommendation system using collaborative filtering / nuha batrisyia faizal azrin
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96389/1/96389.pdf
_version_	1804889987506765824

Residence in Klang Valley recommendation system using collaborative filtering / Nuha Batrisyia Faizal Azrin

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