Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid

Finding a suitable career is the most prevalent challenge that students confront following graduation. For students who do not know what they want to be after graduating, career seeking may be a difficult experience. The main aim of this project is to develop a career recommendation system that focu...

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Main Author: Abdul Rashid, Adib Hakimi
Format: Thesis
Language:English
Published: 2022
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/59453/1/59453.pdf
https://ir.uitm.edu.my/id/eprint/59453/
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spelling my.uitm.ir.594532023-06-12T00:16:05Z https://ir.uitm.edu.my/id/eprint/59453/ Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid Abdul Rashid, Adib Hakimi Electronic Computers. Computer Science Algorithms Web databases Finding a suitable career is the most prevalent challenge that students confront following graduation. For students who do not know what they want to be after graduating, career seeking may be a difficult experience. The main aim of this project is to develop a career recommendation system that focuses solely on computer science, specifically for UiTM Tapah's CS230 students. The system's career data was scraped from the Jobstreet website using the web scraping technique. A content-based filtering method is used to make the recommendation, which filters one item to another that is similar to the user's preferences. The Modified Waterfall methodology was used to drive this project, which consists of five (5) phases: planning, analysis, design, development, and testing. Visual Studio Code, Anaconda, Pycharm, and Xampp are among the tools used to create this system. The system is designed with a user-friendly interface and simple procedures for the user to follow in order to make a recommendation. This system was put through its paces with the help of a specialized functionality tester. More career opportunities will be offered to career vacancy websites in the future. The system will be more advanced in terms of screening possible careers for the user to choose from, and it will be linked directly to career page websites to ensure that all open careers are still available for the user to apply for. 2022-01 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/59453/1/59453.pdf Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid. (2022) Degree thesis, thesis, Universiti Teknologi MARA, Perak. <http://terminalib.uitm.edu.my/59453.pdf>
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
Web databases
spellingShingle Electronic Computers. Computer Science
Algorithms
Web databases
Abdul Rashid, Adib Hakimi
Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
description Finding a suitable career is the most prevalent challenge that students confront following graduation. For students who do not know what they want to be after graduating, career seeking may be a difficult experience. The main aim of this project is to develop a career recommendation system that focuses solely on computer science, specifically for UiTM Tapah's CS230 students. The system's career data was scraped from the Jobstreet website using the web scraping technique. A content-based filtering method is used to make the recommendation, which filters one item to another that is similar to the user's preferences. The Modified Waterfall methodology was used to drive this project, which consists of five (5) phases: planning, analysis, design, development, and testing. Visual Studio Code, Anaconda, Pycharm, and Xampp are among the tools used to create this system. The system is designed with a user-friendly interface and simple procedures for the user to follow in order to make a recommendation. This system was put through its paces with the help of a specialized functionality tester. More career opportunities will be offered to career vacancy websites in the future. The system will be more advanced in terms of screening possible careers for the user to choose from, and it will be linked directly to career page websites to ensure that all open careers are still available for the user to apply for.
format Thesis
author Abdul Rashid, Adib Hakimi
author_facet Abdul Rashid, Adib Hakimi
author_sort Abdul Rashid, Adib Hakimi
title Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
title_short Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
title_full Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
title_fullStr Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
title_full_unstemmed Student career recommendation using content-based filtering method / Adib Hakimi Abdul Rashid
title_sort student career recommendation using content-based filtering method / adib hakimi abdul rashid
publishDate 2022
url https://ir.uitm.edu.my/id/eprint/59453/1/59453.pdf
https://ir.uitm.edu.my/id/eprint/59453/
_version_ 1769846463032983552
score 13.209306