Rental apartment monitoring system

• Main Author: Kuit, Ying Qian
• Format: Final Year Project / Dissertation / Thesis
• Published: 2024
• Subjects: L Education (General); T Technology (General)
• Online Access: http://eprints.utar.edu.my/6515/1/fyp_IB_2024_KYQ.pdf; http://eprints.utar.edu.my/6515/

There is a lack of a complete monitoring system in the property market in Malaysia, specifically in Kuala Lumpur which is one of the busiest regions to accurately determining apartment values based on several characteristics. This lack of presence leaves users without a reliable tool for making reliable decisions regarding property investments or rents. Moreover, users frequently have difficulties in creating accurate forecasts as a result of insufficient understanding of market dynamics as well as relevant variables that impact flat prices. Therefore, here comes the need of an interactive dashboard to illustrate and provide a comprehensive view for the peoples. The aim of this project is to create a monitoring system that can generate price predictions for apartments in Kuala Lumpur by analyzing their features. This approach seeks to fill the void in the market by offering customers a simpler visual representation of apartment rental rates, taking into account criteria such as the number of bedrooms, number of bathrooms, location, facilities, and amenities. Through the utilization of this technology, individuals can enhance their property search experience and make well-informed choices regarding property purchases. This project applies the CRISP-DM (Cross-Industry Standard Process for Data Mining) technique to provide a path to simplify the processing of project data. This technique comprises six steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation, and Deployment. Every individual stage plays a crucial role in guaranteeing the success of the project and reducing possible risks throughout every phase of its execution. Programming languages like Python is used for tasks such as web scraping, data processing, and visualization. The obtained data is shown using various graphs in order to comprehend the relationships among different variables that impact the apartment rental. After finishing the project, the monitoring system effectively produces price estimates for apartments in Kuala Lumpur based on their existing attributes. Users could access to a simplified visual illustration of apartment rental, enabling them to make wise decisions regarding property investments or rentals. The technology offers useful insights into the elements that impact flat prices, enabling users to enhance their apartment search process and navigate the property market with greater efficiency.