House Rental Management System (Dream House)

Azizan, Muhammad Aiman Izzat (2024) House Rental Management System (Dream House). Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

The House Rental Management System (DreamHouse) project was developed to streamline the management and operation of rental properties through an integrated software solution. This system provides a comprehensive platform for tenants, guests, landlords, administrators, and agents to manage property listings, contracts, and user interactions efficiently. The primary objective of this project was to enhance the functionality and user experience of property management by leveraging modern web technologies. The system architecture is built on a robust framework that ensures security, reliability, and scalability, addressing the complex needs of property management. Key features of the system include property listing management, search functionality with advanced filters, user role management, and a dynamic contract system. The system was designed with a user-friendly interface to ensure ease of use for individuals with varying levels of technical skills. Extensive testing, including unit testing, integration testing, system testing, and user acceptance testing, was conducted to ensure the system met all functional requirements and performance benchmarks. The testing phases highlighted the system’s capability to handle multiple user requests simultaneously, maintain data integrity, and protect against potential security threats. The implementation of the House Rental Management System (DreamHouse) has demonstrated significant improvements in operational efficiency and user satisfaction. Feedback from user acceptance testing has been overwhelmingly positive, with particular commendation for the system’s intuitive navigation and fast response times. This project not only fulfills the academic requirements of Bachelor of Computer Science at Universiti Teknikal Malaysia Melaka (UTeM) but also provides a scalable solution that can be adapted to different markets within the real estate industry. Future enhancements will focus on incorporating artificial intelligence for predictive analytics and further automating property management processes.

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