Implementation of Genetic Process Mining to Support Information System Audit

Authors

  • Yora Radityohutomo School of Computing, Telkom University Bandung
  • Gede Agung Ary Wisudiawan School of Computing, Telkom University Bandung
  • Andry Alamsyah School of Economics and Business, Telkom University Bandung
  • Anisa Herdiani School of Computing, Telkom University Bandung

Abstract

One of the frameworks that can be used to audit information systems is COBIT 5 which offers process assessment
model (PAM). The process assessment model usually done by collecting and validating random factual data
samples, so that the results of this assessment cannot be representative of the overall ongoing process. This
research uses process mining by using event log to replace data collection and data validation stage in process
assessment model. Process mining aims to describe the ongoing process model of the event log data
automatically so that it can be compared with the standard flow process in real time. Process mining is applied
using a genetic algorithm that can recognize less frequent behavior in event log as noise data. This assessment
process delivers the rating point level as a result for comparison of the standard process flow with the process
model of the process mining and business flow analysis of the event log data. The results of this study show
genetic process mining able to support corporate information system audit activities.

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Published

2018-02-05

Issue

2017: SCBTII Proceeding

Section

Articles