Natural Language Processing For Requirement Elicitation In University Using Kmeans And Meanshift Algorithm

Authors

Devi Yurisca Bernanda, Department of Computer Science, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia | Department of Information System, Faculty of Technology and Design, Universitas Bunda Mulia, Jakarta, Indonesia.Follow
Dayang N.A. Jawawi, Department of Computer Science, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.Follow
Shahliza Abd Halim, Department of Computer Science, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.Follow
Fransiskus Adikara, Department of Informatics, Faculty of Technology and Design, Universitas Bunda Mulia, Jakarta, Indonesia.Follow

Abstract

Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the needs of stakeholders and the goals of the organization. The research objectives in this research to the process collected and integrating data from multiple sources and ensuring interoperability. Conclusion in this research is determining is the clustering algorithm help the collection data and elicitation process has a somewhat greater impact on the ratings provided by professionals for pairs that belong to the same cluster. However, the influence of POS tagging on the ratings given by professionals is relatively consistent for pairs within the same cluster and pairs in different clusters.

Keywords

DDRE, Data Source, Requirement Engineering, System Software, Elicitation Process

Article Type

Special Issue Article

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite this Article

Bernanda, Devi Yurisca; Jawawi, Dayang N.A.; Abd Halim, Shahliza; and Adikara, Fransiskus (2024) "Natural Language Processing For Requirement Elicitation In University Using Kmeans And Meanshift Algorithm," Baghdad Science Journal: Vol. 21: Iss. 2, Article 29.
DOI: https://doi.org/10.21123/bsj.2024.9675