The development of a performance appraisal system using Decision Tree analysis and Fuzzy Logic

Abstract

The establishment of highly qualified faculty has become the core work of human resource management in State Universities and Colleges. Also, faculty add value to higher education institutions and performance evaluation is the best way to keep track of them. This study presents the development of a performance appraisal system which aims at studying the HR specific to the educational environment and brings out the role of data mining in achieving quality enhanced development in its faculty. The researchers utilized CRISP-DM and Extreme Programming methodologies, focusing on generating models for the Decision Tree algorithm, combined with Fuzzy Logic Controller in predicting faculty performance. J48-generated IF-THEN rules is utilized in conjunction with FLC to predict individual or institutional faculty performance. Also, the generated output of the prototype meets substantial standards. Finally, main users found the system to be Very Acceptable through IS0/IEC 20510:2011 software quality tool.