Abstract
Apartment rental prices in Kuala Lumpur are influenced by numerous factors. The aim of this study is to conduct a statistical analysis of the impact of a variety of factors on the monthly rental prices of apartments in Kuala Lumpur, such as the size of the house (square feet), the availability of parking space, and the distance from the Kuala Lumpur City Centre. Correlation and multiple linear regression analysis were applied to secondary data from 38 samples. The dataset from the Kaggle.com website, which includes the rental price and distinctive features of houses in the city of Kuala Lumpur, Malaysia. The findings reveal the distance from KLCC, and the availability of parking spaces are the most significant contributors to rental price variations. Larger apartments with more square footage also tend to have higher rental prices, but their impact is less pronounced compared to the other factors. Another purpose of the study is to find out the factors that signify the apartment rental price near KLCC. To estimate the rental prices near KLCC, this study develops a multiple linear regression model based on these key variables. The importance of this research depends on its ability to provide real estate brokers, owners, and potential tenants with insightful information. Stakeholders in the rental market can make better judgements by being aware of the main elements influencing rental rates.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Shah Kirit, Nur Shamilah UNSPECIFIED Tarmizi, Nurin Nazirah UNSPECIFIED Mohd Saamah, Nurul Ain Athirah UNSPECIFIED Yusoff, Sarah UNSPECIFIED Ahmad, Noraini UNSPECIFIED |
Subjects: | H Social Sciences > HB Economic Theory. Demography > Price |
Divisions: | Universiti Teknologi MARA, Perlis > Arau Campus |
Journal or Publication Title: | Jurnal Intelek |
UiTM Journal Collections: | Listed > Jurnal Intelek (JI) |
ISSN: | 2682-9223 |
Volume: | 20 |
Number: | 1 |
Page Range: | pp. 125-135 |
Keywords: | correlation, multiple linear regression, parking spaces, rental prices |
Date: | February 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/111269 |