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• W4316076831 abstract "Identification of bottlenecks is a challenge for researchers to detect and deal with as soon as possible so as not to affect the implementation of business processes in the actual situation. The complexity of business processes can make it difficult for analysts to identify bottlenecks in a business process. Process mining is a technique to detect bottlenecks using event logs. However, many studies still use event logs from the system resource activities. Therefore, identification cannot be made before implementation. The researcher proposes bottleneck detection using the Discrete Event Simulation (DES) hierarchical process model. The hierarchical process model is divided into Top-level and Bottom-level process models. DES is used to simulate a hierarchical process model that can generate event logs. The event log was analyzed using ProM with the Inductive Miner method and performance analysis. This research indicates that activities that occur bottlenecks at the Top-level can represent a group of activities that occur bottlenecks at the Bottom-level. Therefore, the bottleneck identification results in the hierarchical process model can provide an overview of bottlenecks in general (Top-level) and specifically (Bottom-level)." @default.
• W4316076831 created "2023-01-14" @default.
• W4316076831 creator A5000266116 @default.
• W4316076831 creator A5011086624 @default.
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• W4316076831 date "2022-07-28" @default.
• W4316076831 modified "2023-09-27" @default.
• W4316076831 title "Identifying Bottlenecks of Hierarchical Process Model by Using Discrete Event Simulation and Process Mining" @default.
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• W4316076831 doi "https://doi.org/10.1109/icced56140.2022.10010450" @default.
• W4316076831 hasPublicationYear "2022" @default.
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