Cover Image

SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam

The technology of smartphones has greatly influenced every facet of society. This invention of the smartphone has extended the way humans entertained, improved interaction, and also influenced social progress in human communities. The consequence of this event has made the demand for smartphones gro...

Full description

Saved in:
Bibliographic Details
Main Author: Affendy Azam, Nursalsabiela
Format: Thesis
Language:English
Published: 2020
Subjects:
Electronic Computers. Computer Science
Algorithms
Cell phones
Online Access:http://ir.uitm.edu.my/id/eprint/35614/1/35614.pdf
http://ir.uitm.edu.my/id/eprint/35614/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.35614
record_format eprints
spelling my.uitm.ir.356142020-11-26T07:16:53Z http://ir.uitm.edu.my/id/eprint/35614/ SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam Affendy Azam, Nursalsabiela Electronic Computers. Computer Science Algorithms Cell phones The technology of smartphones has greatly influenced every facet of society. This invention of the smartphone has extended the way humans entertained, improved interaction, and also influenced social progress in human communities. The consequence of this event has made the demand for smartphones growing rapidly day by day. Different smartphones come with different specifications to make broader choices for the user to choose from. Due to the midst of thousands of smartphone advertisements from numerous brands have caused the buyer to have a hard time when deciding which smartphone matches their desire. Usually, smartphone buyers will consider budget, brand, camera, storage, and many more. Nevertheless, since all these specifications need to take into consideration, smartphone buyers may not be able to express their preferences accurately and will face some difficulties when comparing the preferences of the smartphone features. Subsequently, this action may be the cause of time-consuming when making a decision as it requires cognitive effort to make a manual survey. Thus, the objective of the system is to design and develop a progressive web application (PWA) recommendation system for purchasing a smartphone by using genetic algorithm and test the system functionality. The technique used is Genetic Algorithm where the user input will be the smartphone specification preferences and budget so these inputs will be processed through Genetic Algorithm and a list of optimum results will be obtained. The functionality testing of this project shows that the system successfully recommending three smartphones above 85% of accuracy from user preferences and achieve the project objective. For future recommendation, this system can make the user straight away deals with the seller to buy the smartphone and displays the picture of the smartphone. 2020 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/35614/1/35614.pdf Affendy Azam, Nursalsabiela (2020) SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam. Degree thesis, Universiti Teknologi MARA, Cawangan Melaka.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Electronic Computers. Computer Science
Algorithms
Cell phones
spellingShingle Electronic Computers. Computer Science
Algorithms
Cell phones
Affendy Azam, Nursalsabiela
SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
description The technology of smartphones has greatly influenced every facet of society. This invention of the smartphone has extended the way humans entertained, improved interaction, and also influenced social progress in human communities. The consequence of this event has made the demand for smartphones growing rapidly day by day. Different smartphones come with different specifications to make broader choices for the user to choose from. Due to the midst of thousands of smartphone advertisements from numerous brands have caused the buyer to have a hard time when deciding which smartphone matches their desire. Usually, smartphone buyers will consider budget, brand, camera, storage, and many more. Nevertheless, since all these specifications need to take into consideration, smartphone buyers may not be able to express their preferences accurately and will face some difficulties when comparing the preferences of the smartphone features. Subsequently, this action may be the cause of time-consuming when making a decision as it requires cognitive effort to make a manual survey. Thus, the objective of the system is to design and develop a progressive web application (PWA) recommendation system for purchasing a smartphone by using genetic algorithm and test the system functionality. The technique used is Genetic Algorithm where the user input will be the smartphone specification preferences and budget so these inputs will be processed through Genetic Algorithm and a list of optimum results will be obtained. The functionality testing of this project shows that the system successfully recommending three smartphones above 85% of accuracy from user preferences and achieve the project objective. For future recommendation, this system can make the user straight away deals with the seller to buy the smartphone and displays the picture of the smartphone.
format Thesis
author Affendy Azam, Nursalsabiela
author_facet Affendy Azam, Nursalsabiela
author_sort Affendy Azam, Nursalsabiela
title SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
title_short SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
title_full SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
title_fullStr SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
title_full_unstemmed SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam
title_sort srcs: smartphone recommendation system using genetic algorithm / nursalsabiela affendy azam
publishDate 2020
url http://ir.uitm.edu.my/id/eprint/35614/1/35614.pdf
http://ir.uitm.edu.my/id/eprint/35614/
_version_ 1685651315088162816
score 13.211869

Similar Items