Abstract
The problem of measuring the dwelling time of the container logistics process at ports in developing countries is often a major problem. Therefore, process mining as a field of data science that focuses on analyzing event log data is used to perform business process analysis. In process mining, the process is a sequence of events or activities that are carried out to achieve certain goals. Event logs help an organization to find gaps between the designed business processes and the reality of the processes that occur. In this study PM4PY as a python library is used to perform process mining techniques. The results of the fitness calculation in this study indicate that the container logistics business process model is close to 0.99.
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