ST750: Decision Making System For Property Buying

Chang Gia Soon Southern University College

The property-buying process can often be overwhelming and complex, requiring potential 
buyers to analyze factors such as affordability, location, and property features. To address these 
challenges, this report presents the Decision-Making System for Property Buying, a web-based 
platform designed to simplify and enhance the property-buying experience for users in 
Malaysia. The system offers key features tailored to address common challenges faced by 
property buyers. It includes an Affordability Calculator Module, which employs both the Debt 
Service Ratio (DSR) method and Household Income-Based Loan Calculator to help users 
evaluate their financial capacity for property purchases. The Property Comparison Tool enables 
users to compare multiple properties side-by-side, analyzing key features such as price, area, 
and amenities. The AI Property Assistant (Chatbot) provides real-time support by answering 
queries, offering property insights, and performing accurate loan calculations. Additionally, 
the Properties You Might Like feature uses a recommendation engine to suggest properties 
based on user preferences, simplifying the discovery of suitable options. RENs can submit new 
property listings for admin approval, while the admin dashboard facilitates property 
management and oversight, ensuring system reliability and operational efficiency. The 
development of this system followed the Waterfall Methodology, ensuring a structured 
approach to system design, implementation, and testing. Functional testing was conducted to 
verify the accuracy of core features, while user acceptance testing (UAT) gathered feedback 
on usability and effectiveness. UAT results, based on a 5-point Likert scale, highlighted high 
user satisfaction and strong system performance. The system targets property buyers, RENs, 
and administrators, aiming to simplify decision-making, enhance property browsing 
experiences, and provide robust financial tools. The expected outcomes include increased user 
satisfaction, a more informed buying process, and improved efficiency in property management. 
In conclusion, the Decision-Making System for Property Buying bridges the gap between 
complex property decisions and user-friendly digital solutions, supporting all stakeholders in 
achieving their goals efficiently.