Optimasi Metode Certainty Factor Menggunakan Rank Order Centroid Pada Sistem Pakar Pendeteksi Turnover Intention Berbasis WEB

Abstract

Turnover intention, or the tendency of employees to resign, poses a significant challenge for companies—especially when dealing with Generation Z, who tend to have lower job commitment and are more likely to switch jobs. This study aims to develop a web-based expert system to detect the level of employee turnover intention by integrating the Certainty Factor (CF) and Rank Order Centroid (ROC) methods. The CF method is used to handle uncertainty in questionnaire assessments, while ROC is implemented to optimize the weights among aspects, namely Thinking of Quitting, Intention to Search for Alternatives, and Intention to Quit. The system is built based on 36 questionnaire statements and tested on 34 respondents. The results show that the system provides more proportional and realistic interpretations compared to the non-optimized approach. Accuracy testing indicates that 27 out of 34 system results match manual assessments, yielding an accuracy rate of 79.41%. These findings suggest that the system performs reliably and can serve as a practical tool for the early detection of turnover intention in the workplace.