Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail

Marketplace mobile application is an application that help employer or entrepreneur to sell their item online. Nowadays, many product already appear and available online sometime user of the marketplace application facing problems in choosing the best product in their category. Recommender Systems a...

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Bibliographic Details
Main Author:	Ismail, Muhammad Alif Fauzan
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Electronic Computers Computer Science Programming languages (Electronic computers) PHP Computer software Application software Operating systems (Computers) Android Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/55180/1/55180.pdf
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id	my-uitm-ir.55180
record_format	uketd_dc
spelling	my-uitm-ir.551802022-01-23T06:44:14Z Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail 2021-02 Ismail, Muhammad Alif Fauzan Electronic Computers. Computer Science Programming languages (Electronic computers) PHP Computer software Application software Operating systems (Computers) Android Algorithms Marketplace mobile application is an application that help employer or entrepreneur to sell their item online. Nowadays, many product already appear and available online sometime user of the marketplace application facing problems in choosing the best product in their category. Recommender Systems are software tools and techniques for suggesting items to users by considering their preferences. Objective of the project are to study Collaborative Filter Algorithm of product recommendation system for marketplace, to develop a prototype of Marketplace Product Recommendation System using Collaborative Filter Algorithm and to test the accuracy of Collaborative Filtering algorithm in the proposed work. The algorithm used to develop a product recommendation engine is collaborative filtering algorithm and this algorithm is written in python. For the development of the marketplace mobile application prototype this project use flutter this application is the platform to implement the recommendation system. Mean Absolute Error (MAE) is used to test the accuracy of the product recommendation system. The MAE is calculate using build in function in python and use two different value which is actual product rating and prediction product rating. The result show that the MAE value is 0.96 which is good because the good MAE value is the value closest to 1. In conclusion this paper is to develop a product recommender in marketplace mobile application using Collaborative Filter and the accuracy of the algorithm is measured using Mean Absolute Error 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/55180/ https://ir.uitm.edu.my/id/eprint/55180/1/55180.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Abdul Latif, Mohd Hanapi
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abdul Latif, Mohd Hanapi
topic	Electronic Computers Computer Science Programming languages (Electronic computers) PHP Computer software Application software Operating systems (Computers) Android Algorithms
spellingShingle	Electronic Computers Computer Science Programming languages (Electronic computers) PHP Computer software Application software Operating systems (Computers) Android Algorithms Ismail, Muhammad Alif Fauzan Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
description	Marketplace mobile application is an application that help employer or entrepreneur to sell their item online. Nowadays, many product already appear and available online sometime user of the marketplace application facing problems in choosing the best product in their category. Recommender Systems are software tools and techniques for suggesting items to users by considering their preferences. Objective of the project are to study Collaborative Filter Algorithm of product recommendation system for marketplace, to develop a prototype of Marketplace Product Recommendation System using Collaborative Filter Algorithm and to test the accuracy of Collaborative Filtering algorithm in the proposed work. The algorithm used to develop a product recommendation engine is collaborative filtering algorithm and this algorithm is written in python. For the development of the marketplace mobile application prototype this project use flutter this application is the platform to implement the recommendation system. Mean Absolute Error (MAE) is used to test the accuracy of the product recommendation system. The MAE is calculate using build in function in python and use two different value which is actual product rating and prediction product rating. The result show that the MAE value is 0.96 which is good because the good MAE value is the value closest to 1. In conclusion this paper is to develop a product recommender in marketplace mobile application using Collaborative Filter and the accuracy of the algorithm is measured using Mean Absolute Error
format	Thesis
qualification_level	Bachelor degree
author	Ismail, Muhammad Alif Fauzan
author_facet	Ismail, Muhammad Alif Fauzan
author_sort	Ismail, Muhammad Alif Fauzan
title	Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
title_short	Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
title_full	Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
title_fullStr	Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
title_full_unstemmed	Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
title_sort	marketplace product recommendation using collaborative filter / muhammad alif fauzan ismail
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/55180/1/55180.pdf
_version_	1783734906599243776

Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail

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