Abstarct: Business process management is a structural and systematic procedure to analyze, develop, control and manage the process, aimed to improve the quality of services. The absence of an efficient business system causes to create unnecessary costs and low-quality services, and also discontent for staff and clients in each organization. Business process management is a comprehensive solution for understanding and managing the process in any organization and helps them to make complex relationships work between staff, systems and process, simple in a way that it will be understandable and in this way it helps, to increase efficiency of organizations and clients’ satisfaction. In this research business process management, process mining and process mining’s algorithms will be examined. Then some processes will be explored with the aim of exploring the relationships between them, so it can identify similar activities of a process that can be placed in a class or a group. In this step extract event logs baxsed on, time of starting transaction and when the transaction is complete, and in the next step clustering and finding hidden relations in this event log will be investigated. The results of implementation of the real and simulated processes indicate that clusters which produced by the proposed method was able to maintain the similarity of the clusters which produced by humans in educational simulated processes with an average of 85.5% and also the accuracy of 73.3% in the real processes. Also, as far as the experts in this field are concerned the proposed method is almost 10% accurate than node filtering in the fuzzy mining. In addition, the processing time of the proposed method compared with the trace clustering method is much improved.