Application of Fuzzy Data Mining Algorithm in Human Resource Management

The application of fuzzy data mining algorithms in human resource management has completely changed the way organizations acquire and retain talent. This algorithm combines mathematical models and artificial intelligence to analyze large amounts of data, identify patterns, and predict employee behavior. One of the main benefits of this approach is that it allows human resources managers to make more informed decisions in recruitment, training, and performance management. For example, by analyzing employee performance data, the algorithm can identify factors that contribute to success or failure in specific roles. Then, this information can be used to develop targeted training plans or adjust job requirements to better match employees’ individual skills and abilities. Another advantage of fuzzy data mining in human resources is that it can help organizations identify potential risks before they become significant issues. For example, by analyzing employee turnover rate and exit interviews, this algorithm can identify common reasons for employee turnover and propose strategies to reduce turnover. Overall, the application of fuzzy data mining algorithms in human resource management has great potential for improving organizational performance and achieving strategic goals.