A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Ձևաչափ: | Թեզիս |
| Լեզու: | English |
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Brac University
2022
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| Առցանց հասանելիություն: | http://hdl.handle.net/10361/16947 |
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10361-169472022-06-08T21:01:39Z A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning Anjum, Afra Antara Islam, Sadaath Majumder, Shaikat Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Human resource management Blockchain Recruitment Ensemble learning Decision tree Performance appraisal Random Forest (RF) Recursive feature elimination Permission protocol Smart contracts Hyperledger fabric Business logistics Machine learning Artificial intelligence This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 87-91). Recruitment is a crucial task for Human Resource Management (HRM) and determines the creation of a competent workforce that eventually brings tangible and intangible benefits for companies. Employees are key elements in determining a company’s success and employees perform well when their skill set complements their job requirements. However, the current system fails to provide a single solution that verifies employee records and predicts employee-company compatibility. This paper proposes an recruitment system using a private permissioned blockchain architecture and ensemble learning algorithms. The paper proposes a permissioned blockchain architecture using permission protocol and smart contracts to store employee records in an immutable ledger. Development of Data and processing decentralization is inspired and in accordance with the Hyperledger Fabric system design, thus creating a decentralized data sharing system that is used to hold comprehensive employee performance records in a peer-to-peer system that allows employee data verification and retrieval by organizations in the blockchain consortium. The applicant records and previous performance appraisal records can be retrieved by a company in the consortium following smart contract rules and can be used to predict employee performance ratings based retrieved previous performance appraisal records. To predict the performance score, we used machine learning models namely supervised and ensemble learning. The system also ranks eligible candidates, based on predicted performance scores and other relevant applicant data via Multi-Criteria Decision Making Algorithm (MCDM). Finally, a Streamlit application is created where performance score predicting and ranking are done automatically with a suitable user interface for final result output. Afra Antara Anjum Sadaath Islam Shaikat Majumder B. Computer Science 2022-06-08T06:41:02Z 2022-06-08T06:41:02Z 2022 2022-01 Thesis ID 18101220 ID 18101227 ID 18101630 http://hdl.handle.net/10361/16947 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 91 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Human resource management Blockchain Recruitment Ensemble learning Decision tree Performance appraisal Random Forest (RF) Recursive feature elimination Permission protocol Smart contracts Hyperledger fabric Business logistics Machine learning Artificial intelligence |
| spellingShingle |
Human resource management Blockchain Recruitment Ensemble learning Decision tree Performance appraisal Random Forest (RF) Recursive feature elimination Permission protocol Smart contracts Hyperledger fabric Business logistics Machine learning Artificial intelligence Anjum, Afra Antara Islam, Sadaath Majumder, Shaikat A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Alam, Md. Golam Rabiul |
| author_facet |
Alam, Md. Golam Rabiul Anjum, Afra Antara Islam, Sadaath Majumder, Shaikat |
| format |
Thesis |
| author |
Anjum, Afra Antara Islam, Sadaath Majumder, Shaikat |
| author_sort |
Anjum, Afra Antara |
| title |
A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| title_short |
A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| title_full |
A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| title_fullStr |
A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| title_full_unstemmed |
A decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned Blockchain and ensemble learning |
| title_sort |
decentralized employee performance appraisal framework for recruitment, performance prediction and ranking using permissioned blockchain and ensemble learning |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16947 |
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