Time-based α+ miner for modelling business processes using temporal pattern

Yutika Amelia Effendi, Riyanarto Sarno

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Business processes are implemented in an organization. When a business process is run, it generates event log. One type of event log is double timestamp event log. Double timestamp has the start and complete time of each activity executed in the business process and has a close relationship with temporal pattern. In this paper, seven types of temporal pattern between activities were presented as extended version of relations used in the double timestamp event log. Since the event log was not always executed in sequential way, therefore using temporal pattern, event log was divided into several small groups to mine the business process both sequential and parallel. Both temporal pattern and Time-based α+ Miner algorithm were used to mine process model, determined sequential and parallel relations and then evaluated the process model using fitness value. This paper was focused on the advantages of temporal pattern implemented in Time-based α+ Miner algorithm to mine business process. The results also clearly stated that the proposed method could present better result rather than that of original α+ Miner algorithm.

Original languageEnglish
Pages (from-to)114-123
Number of pages10
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Volume18
Issue number1
DOIs
Publication statusPublished - 1 Feb 2020

Keywords

  • Alpha+ miner
  • Business process model
  • Process discovery
  • Process mining
  • Temporal pattern

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