IdVar4CL: Causal Loop Variable Identification Method for Systems Thinking Based on Text Mining Approach

Abstract

Systems thinking is a discipline for understanding wholeness and frameworks based on the changing patterns of the interconnectedness of the whole system. The storytelling of a system is a description of the mental model of an individual in describing the state of the environment. There are differences in the interpretation of the system description. This difference occurs because each individual has a different level of systems thinking in terms of experience, learning process, insight, intuition, and assumption in understanding system interactions. This study aims to extract data in the description of the storytelling of a systems thinking case by performing text mining and similarity to identify and find a variable to form causal loop diagrams. Based on the results of this study, there are results in the data extraction from the description of storytelling for the systems thinking case. The conclusions of this study are as follows: First, processing the five documents has successfully identified two documents with the highest similarity value, such as d1 and d3. Second, based on the cosine similarity calculation results and the results of the similarity value, there is a value closest to 1, such as 0.0913166. This value is at the d1 and d3 positions. Third, it produces a variable approach in the form of a group of words used in modeling thinking systems based on a connectedness value greater than 0.50.