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Selection of prospective workers using profile matching algorithm on crowdsourcing platform

The use of a crowdsourcing platform is an option to get workers who will help complete the work. Crowdsourcing is the process of gathering work, information, or opinions from a large number of individuals using the internet, social media, or smartphone apps. Whether crowdsourcing is used for program...

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Main Authors: Cucus, Ahmad, Aji, Luhur Bayu, Al Fahim, Mubarak Ali, Aminuddin, Afrig, Farida, Lilis Dwi
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/39339/1/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/39339/2/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39339/
https://doi.org/10.1109/ICOIACT55506.2022.9972155
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spelling my.ump.umpir.393392023-11-21T00:30:19Z http://umpir.ump.edu.my/id/eprint/39339/ Selection of prospective workers using profile matching algorithm on crowdsourcing platform Cucus, Ahmad Aji, Luhur Bayu Al Fahim, Mubarak Ali Aminuddin, Afrig Farida, Lilis Dwi QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) The use of a crowdsourcing platform is an option to get workers who will help complete the work. Crowdsourcing is the process of gathering work, information, or opinions from a large number of individuals using the internet, social media, or smartphone apps. Whether crowdsourcing is used for programming, design, content creation, or any other task, requesters are putting their trust in individuals who are unfamiliar with their knowledge and have unknown histories and skills. Requesters do not have the time or resources to screen all of the crowd's qualities, unlike employing full-time personnel. In this study, we try to minimize the risks faced by requesters when using a crowdsourcing platform to complete their work, namely by increasing the match between the profile of workers and the jobs offered on the crowdsourcing platform. The researcher implemented the profile matching method using a dataset consisting of several fields that became the criteria for finding a match. The criteria used to find a match between workers and the work offered consist of two parts, core factors and secondary factors. Core Factor Criteria as skill, designation, location, and the secondary factor is the number of years of work experience. These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. This algorithm is able to select worker profiles from 10,000 datasets, up to 1148 people who are most suitable for the tasks offered. And the results obtained indicate an increase in the match between workers and the needs of the work offered by the requester. Institute of Electrical and Electronics Engineers Inc. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39339/1/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/39339/2/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm_ABS.pdf Cucus, Ahmad and Aji, Luhur Bayu and Al Fahim, Mubarak Ali and Aminuddin, Afrig and Farida, Lilis Dwi (2022) Selection of prospective workers using profile matching algorithm on crowdsourcing platform. In: ICOIACT 2022 - 5th International Conference on Information and Communications Technology: A New Way to Make AI Useful for Everyone in the New Normal Era, Proceeding; 5th International Conference on Information and Communications Technology, ICOIACT 2022, 24-25 August 2022 , Yogyakarta. pp. 122-126. (185076). ISBN 978-166545140-6 https://doi.org/10.1109/ICOIACT55506.2022.9972155
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Cucus, Ahmad
Aji, Luhur Bayu
Al Fahim, Mubarak Ali
Aminuddin, Afrig
Farida, Lilis Dwi
Selection of prospective workers using profile matching algorithm on crowdsourcing platform
description The use of a crowdsourcing platform is an option to get workers who will help complete the work. Crowdsourcing is the process of gathering work, information, or opinions from a large number of individuals using the internet, social media, or smartphone apps. Whether crowdsourcing is used for programming, design, content creation, or any other task, requesters are putting their trust in individuals who are unfamiliar with their knowledge and have unknown histories and skills. Requesters do not have the time or resources to screen all of the crowd's qualities, unlike employing full-time personnel. In this study, we try to minimize the risks faced by requesters when using a crowdsourcing platform to complete their work, namely by increasing the match between the profile of workers and the jobs offered on the crowdsourcing platform. The researcher implemented the profile matching method using a dataset consisting of several fields that became the criteria for finding a match. The criteria used to find a match between workers and the work offered consist of two parts, core factors and secondary factors. Core Factor Criteria as skill, designation, location, and the secondary factor is the number of years of work experience. These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. This algorithm is able to select worker profiles from 10,000 datasets, up to 1148 people who are most suitable for the tasks offered. And the results obtained indicate an increase in the match between workers and the needs of the work offered by the requester.
format Conference or Workshop Item
author Cucus, Ahmad
Aji, Luhur Bayu
Al Fahim, Mubarak Ali
Aminuddin, Afrig
Farida, Lilis Dwi
author_facet Cucus, Ahmad
Aji, Luhur Bayu
Al Fahim, Mubarak Ali
Aminuddin, Afrig
Farida, Lilis Dwi
author_sort Cucus, Ahmad
title Selection of prospective workers using profile matching algorithm on crowdsourcing platform
title_short Selection of prospective workers using profile matching algorithm on crowdsourcing platform
title_full Selection of prospective workers using profile matching algorithm on crowdsourcing platform
title_fullStr Selection of prospective workers using profile matching algorithm on crowdsourcing platform
title_full_unstemmed Selection of prospective workers using profile matching algorithm on crowdsourcing platform
title_sort selection of prospective workers using profile matching algorithm on crowdsourcing platform
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39339/1/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/39339/2/Selection%20of%20prospective%20workers%20using%20profile%20matching%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39339/
https://doi.org/10.1109/ICOIACT55506.2022.9972155
_version_ 1822923859616071680
score 13.235367

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