e aim of this study is to present and evaluate a computational framework based on the Case-Based Reasoning (CBR) approach for analyzing and assessing the performance of employees in governmental organizations of Bushehr Province. In this study, an attempt has been made to model human behavior in solving new problems by relying on past experiences and to provide a systematic model for predicting and evaluating human resource performance.

The statistical population includes all employees of governmental organizations in Bushehr Province, from which 14 individuals were selected through random sampling. The required data were collected using a questionnaire designed based on a decision matrix, and its validity and reliability were evaluated. The analysis process consisted of four main stages: retrieval, reuse, revision, and retention of cases.

To determine the degree of similarity among samples, the K-Means clustering algorithm was applied, and subsequently, the average information of similar cases was used to predict the performance of the target case. The results indicated that factors such as commitment and responsibility, teamwork and collaboration, respect for colleagues, punctuality, and appearance had the greatest impact on overall employee performance.

Accuracy assessment of the model using the MAEE index showed that all error values were below ten percent, confirming the validity of the findings. Overall, the study concludes that the use of the Case-Based Reasoning method can serve as an innovative, efficient, and explainable approach for evaluating employee performance in governmental organizations.


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