TY - JOUR
T1 - Determining process model using Time-based Process Mining and control-flow pattern
AU - Sarno, Riyanarto
AU - Wibowo, Widyasari Ayu
AU - Kartini,
AU - Amelia, Yutika
AU - Rossa, Kelly
N1 - Publisher Copyright:
© 2016 Universitas Ahmad Dahlan.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control-flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed-based Process Mining which utilized non-linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed-based Process Mining and control-flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.
AB - Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control-flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed-based Process Mining which utilized non-linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed-based Process Mining and control-flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.
KW - Conditional OR
KW - Control-flow pattern
KW - Incompleteness
KW - Noise
KW - Timed-based Process Mining
UR - http://www.scopus.com/inward/record.url?scp=84964764007&partnerID=8YFLogxK
U2 - 10.12928/TELKOMNIKA.v14i1.3257
DO - 10.12928/TELKOMNIKA.v14i1.3257
M3 - Article
AN - SCOPUS:84964764007
SN - 1693-6930
VL - 14
SP - 349
EP - 359
JO - Telkomnika (Telecommunication Computing Electronics and Control)
JF - Telkomnika (Telecommunication Computing Electronics and Control)
IS - 1
ER -