@Article{JICS-13-131, author = {Ojokoh Bolanle Adefowoke , Oluwasefunmi Tale Arogundade , Mojisola Grace Asogbon , Babatope Sunday Adeniyi and Oluwarotimi Williams Samuel}, title = {Fuzzy Driven Decision Support System for Enhanced Performance Appraisal}, journal = {Journal of Information and Computing Science}, year = {2018}, volume = {13}, number = {2}, pages = {131--140}, abstract = { Employees’  performance  appraisal  is  often  considered  as  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. }, issn = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22455.html} }