Structural similarity analysis of business process model using selective reduce based on Petri Net

Abstract

It is exceedingly possible for an organization to have similarities, differences, and varieties among its business processes. To coordinate and make those processes effective and efficient, similarity and difference analysis among existing processes becomes necessary. Business Process Similarity (BPS) is an activity to identify the similarity of two different business processes. In this research, we analysed the similarity of structure of business processes using selective reduce method as a part of graph reduction method, which reduces graph variant over query. The modeling of business process in this research implements Petri Net notation to identify similar activities among different business processes. The result of this study asserts that the degree of similarity depends on nodes of query and variant, and the flow of business processes. A variant with more complete nodes than a query will be reduced and simplified. The degree of similarity of a variant with less complete nodes than a query is below 100%. A variant with the same or more complete nodes than a query does not guarantee the degree of similarity 100%, depending on its flow direction. By means of selective reduce method, the degree of structural similarity will depend on a query (subject of comparison) and a variant (object of comparison) relative to intended purposes for simplification, adjustment, or inspection of sections between two business processes.