House rental management system for student in UiTM Perlis / Nur Nadiah Husna Samsudin and Muhammad Nabil Fikri Jamaluddin

Samsudin, Nur Nadiah Husna and Jamaluddin, Muhammad Nabil Fikri (2023) House rental management system for student in UiTM Perlis / Nur Nadiah Husna Samsudin and Muhammad Nabil Fikri Jamaluddin. In: Research Exhibition in Mathematics and Computer Sciences (REMACS 5.0). College of Computing, Informatics and Media, UiTM Perlis, pp. 45-46. ISBN 978-629-97934-0-3

Abstract

This House Rental Management system is a system created to display rental houses near UiTM Perlis that are available. This house rental management system will also display detailed information about each house and allow you to contact the agent via WhatsApp. The purpose of the House Rental Management System is to help students find available rental houses near campus. While, in this system also can give landlords to upload their house to display in this system. So it can give ease to student to contact them for rent their house. The methodology used for the development process is the waterfall model. The entire project development process is divided into separate phases. It will go through three phases, such as system requirement identification, system design and development, and testing. Besides functional testing, also user acceptance test (UAT) with 30 participants, consisting of students from UiTM Perlis, was conducted to verify the performance of this system prototype.

Metadata

Item Type: Book Section
Creators:
Creators
Email / ID Num.
Samsudin, Nur Nadiah Husna
UNSPECIFIED
Jamaluddin, Muhammad Nabil Fikri
UNSPECIFIED
Subjects: T Technology > T Technology (General) > Information technology. Information systems
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Page Range: pp. 45-46
Keywords: House Rental, students, UiTM Perlis, User Acceptance Testing (UAT)
Date: 2023
URI: https://ir.uitm.edu.my/id/eprint/100275
Edit Item
Edit Item

Download

[thumbnail of 100275.pdf] Text
100275.pdf

Download (1MB)

ID Number

100275

Indexing

Statistic

Statistic details