Gap analysis process model is a study that can help an institution to determine differences between business process models, such as a model of Standard Operating Procedure and a model of activities in an event log. Gap analysis is used for finding incomplete processes and can be obtained by using structural similarity. Structural similarity measures the similarity of activities and relationships depicting in the models. This research introduces a graph-matching algorithm as the structural similarity algorithm and compares it with dice coefficient algorithms. Graph-matching algorithm notices parallel relationships and invisible tasks, on the contrary dice coefficient algorithms only measure closeness between activities and relationships. The evaluation shows that the graph-matching algorithm produces 76.76 percent similarity between an SOP model and a process model generating from an event log; while, dice coefficient algorithms produces 70 percent similarity. The ability in detecting parallel relationships and invisible tasks causes the graph-matching algorithm produces a higher similarity value than dice coefficient algorithms.

Original languageEnglish
Pages (from-to)124-134
Number of pages11
JournalIndonesian Journal of Electrical Engineering and Computer Science
Issue number1
Publication statusPublished - 2019


  • Business process
  • Dice coefficient similarity
  • Gap analysis
  • Graph database
  • Graph-matching algorithm


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