Extraction of Activity Diagrams Based on Steps Performed in Use Case Description Using Text Mining (Case Study: SRS Myoffice Application)

Octavially, Reynaldi Prama; Priyadi, Yudi; Widowati, Sri

doi:10.1109/ice3is56585.2022.10010003

Cited by 13 publications

(3 citation statements)

References 29 publications

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“…In text mining, the implementation is required to prepare for the irregularity of the text data structure to become structured data. This implementation uses several activities for text preprocessing, including [12,18] a. Case folding for converting to lowercase.…”

Section: Text Miningmentioning

confidence: 99%

“…In text mining for the activities of text preprocessing, the stages of the process can be adjusted depending on the type of text data and the results required. According to Octavially et al [12], there is an extraction process for text preprocessing consisting of tokenization, stopword removal, and stemming. In addition, there is a semantic similarity measurement process through the WordNet similarity for Java applications.…”

Section: Introductionmentioning

confidence: 99%

“…The results of the extraction process, combined with greedy algorithms, constitute an optimal value solution approach. In addition, there is a method for calculating similarities using the Wu Palmer and Levenshtein method [12,18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Priyadi¹,

Kusumahadi²,

Lyanda³

2022

IJFIS

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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.

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Section: Text Miningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%