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Predicting Employee Performance using Machine Learning

The goal of this research is to create a machine learning model that uses historical employee data to predict future performance in organisational contexts. The goal is to divide people into three distinct categories—high performers, moderate performers, and low performers—and to use data to improve...

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Bibliographic Details
Main Author: Chol Gakeer Alier, Nathaniel
Format: Final Year Project
Language:English
Published: 2024
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://utpedia.utp.edu.my/id/eprint/26996/1/Nathaniel_fyp2_report.pdf
http://utpedia.utp.edu.my/id/eprint/26996/
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record_format eprints
spelling oai:utpedia.utp.edu.my:269962024-05-29T07:25:19Z http://utpedia.utp.edu.my/id/eprint/26996/ Predicting Employee Performance using Machine Learning Chol Gakeer Alier, Nathaniel QA75 Electronic computers. Computer science The goal of this research is to create a machine learning model that uses historical employee data to predict future performance in organisational contexts. The goal is to divide people into three distinct categories—high performers, moderate performers, and low performers—and to use data to improve talent management and decision-making. The construction of the model entails addressing issues such as data quality, bias, and interpretability. In comparison to present methods, the expected outcomes include increased accuracy, speed, and versatility. However, ethical concerns, such as fairness and openness, remain central to the initiative. As organisations seek more innovative employee management approaches, this project aims to deliver a forward-thinking and adaptable paradigm that matches with changing organisational dynamics. 2024-01 Final Year Project NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/26996/1/Nathaniel_fyp2_report.pdf Chol Gakeer Alier, Nathaniel (2024) Predicting Employee Performance using Machine Learning. [Final Year Project] (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Chol Gakeer Alier, Nathaniel
Predicting Employee Performance using Machine Learning
description The goal of this research is to create a machine learning model that uses historical employee data to predict future performance in organisational contexts. The goal is to divide people into three distinct categories—high performers, moderate performers, and low performers—and to use data to improve talent management and decision-making. The construction of the model entails addressing issues such as data quality, bias, and interpretability. In comparison to present methods, the expected outcomes include increased accuracy, speed, and versatility. However, ethical concerns, such as fairness and openness, remain central to the initiative. As organisations seek more innovative employee management approaches, this project aims to deliver a forward-thinking and adaptable paradigm that matches with changing organisational dynamics.
format Final Year Project
author Chol Gakeer Alier, Nathaniel
author_facet Chol Gakeer Alier, Nathaniel
author_sort Chol Gakeer Alier, Nathaniel
title Predicting Employee Performance using Machine Learning
title_short Predicting Employee Performance using Machine Learning
title_full Predicting Employee Performance using Machine Learning
title_fullStr Predicting Employee Performance using Machine Learning
title_full_unstemmed Predicting Employee Performance using Machine Learning
title_sort predicting employee performance using machine learning
publishDate 2024
url http://utpedia.utp.edu.my/id/eprint/26996/1/Nathaniel_fyp2_report.pdf
http://utpedia.utp.edu.my/id/eprint/26996/
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score 13.211869

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