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Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal

Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal

Oluwasefunmi 'Tale Arogundade, Bolanle Ojokoh, Mojisola Grace Asogbon, Oluwarotimi Williams Samuel, Babatope Sunday Adeniyi
Copyright: © 2020 |Volume: 11 |Issue: 1 |Pages: 14
ISSN: 1947-3478|EISSN: 1947-3486|EISBN13: 9781799802303|DOI: 10.4018/IJHCITP.2020010102
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MLA

Arogundade, Oluwasefunmi 'Tale, et al. "Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal." IJHCITP vol.11, no.1 2020: pp.17-30. http://doi.org/10.4018/IJHCITP.2020010102

APA

Arogundade, O. '., Ojokoh, B., Asogbon, M. G., Samuel, O. W., & Babatope Sunday Adeniyi. (2020). Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal. International Journal of Human Capital and Information Technology Professionals (IJHCITP), 11(1), 17-30. http://doi.org/10.4018/IJHCITP.2020010102

Chicago

Arogundade, Oluwasefunmi 'Tale, et al. "Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal," International Journal of Human Capital and Information Technology Professionals (IJHCITP) 11, no.1: 17-30. http://doi.org/10.4018/IJHCITP.2020010102

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Abstract

Employee performance appraisal is often considered a core management task in most standard organizations because it could potentially inspire an employee towards the pursuit of organizational goals and objectives. Meanwhile, issues such as delay in appraisal processes, inevitable human error, and emotional status of the appraiser, are common with the traditional appraisal methods. Hence, this research proposes a fuzzy decision-support system based on Henri Fayol's 14 principles of management for the appraisal of employees' performance. A questionnaire consisting of 44 structured questions was designed based on these principles and administered to the employees of Babcock University, Ilisan-Remo, Ogun State, Nigeria. Fuzzy inference system that incorporates Mamdani computational technique was built based on the feedback extracted from the questionnaires, and used for appraising the employee performance. Experimental results show that the proposed system could predict the appraisal status of an employee with 75% accuracy in comparison to the conventional appraisal method.

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