Modification of Alpha++ for Discovering Collaboration Business Processes Containing Non-Free Choice

Gusna Ikhsan, R. Sarno, K. R. Sungkono
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Abstract

A business process is a series of activities or work that is structured and interrelated to solve a problem. Business Process Model Notation (BPMN) is a standard that often use to create a series of business processes. There are not only one or two processes in a business process, but many processes which cross each other. Processes which have activities related to one another are called collaborative business processes. Process mining techniques analyze a process model that is generated based on actual processes with a process model as the Standard Operational Procedure (SOP). Existing process mining techniques depict activities of each process without consider the linkages between activities in a process with another process. In addition, there is an issue that should be handled by process mining techniques, i.e. non-fee choice. This paper proposes a Modification of Alpha++ for discovering linkages of activities in collaboration business processes. Alpha++ is chosen because this algorithm can form non-free choice relationship. In the evaluation, the proposed Modification of Alpha++ will be compared with Alpha++, Inductive Miner, and Heuristic Miner. The evaluation shows the proposed Modification Alpha++ algorithm can model event log data correctly based on the proposed business process. Modification Alpha++ can find non-free choice constructs on the event log data. Modification Alpha++ gets the best calculation results for fitness, precision, and f-measure with a value of 1.
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用于发现包含非自由选择的协作业务流程的改进
业务流程是为解决问题而结构化和相互关联的一系列活动或工作。业务流程模型符号(BPMN)是一种经常用于创建一系列业务流程的标准。业务流程中不仅有一个或两个流程,还有许多相互交叉的流程。具有相互关联的活动的流程称为协作业务流程。流程挖掘技术分析基于实际流程生成的流程模型,将流程模型作为标准操作过程(SOP)。现有的流程挖掘技术描述每个流程的活动,而没有考虑流程中活动与另一个流程之间的联系。此外,还有一个问题应该由过程挖掘技术来处理,即无费用选择。本文提出了对Alpha++的改进,用于发现协作业务流程中活动的联系。之所以选择Alpha++,是因为该算法可以形成非自由选择关系。在评估中,提出的修改阿尔法++将与阿尔法++、归纳Miner和启发式Miner进行比较。评估结果表明,所提出的修改阿尔法++算法能够基于所提出的业务流程正确地建模事件日志数据。修改Alpha++可以在事件日志数据上找到非自由选择结构。Alpha++在适应度、精度和f-measure值为1时得到了最好的计算结果。
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