Researchers in this field are looking at how data mining and HRM are intertwined to manage human resources better. An Ensemble Classifier-Decision Tree (EC-DT) approach may analyse Human Resource Management (HRM) data. C4.5, Random Tree, J48, and Simple Cart are the single decision tree algorithms employed. Based on the algorithm design, algorithms for evaluation and talent recommendation are then assessed in an HRM system. The algorithm under development is put through its last paces in terms of comparisons and testing. The EC-DT method has a classification accuracy of 79.97 %, whereas C4.5 has a classification accuracy of 76.69 %. DMRM's accuracy and recall were 35.2 % and 41.6 % better than CRM's and CFR's combined, proving that data mining may be a powerful tool for recommending products and services (CFRM). Thus, the data mining-based human resources management system may help organisations expand due to quantitative analyses. In this way, the data mining-based HRM system may encourage and direct businesses to grow under the outcomes of quantitative assessments. A starting point for further research on data mining-based HRM systems may be found in the abovementioned findings