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All Journal IPTEK The Journal for Technology and Science
Adi Setyo Nugroho
Informatics Master Programme, Institut Teknologi Sepuluh Nopember.
Computer Science & IT

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A Semantic Comparison of Feature Requirements Extraction Methods Patricia Gertrudis Manek; Abdullah Faqih Septiyanto; Adi Setyo Nugroho
IPTEK The Journal for Technology and Science Vol 32, No 3 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i3.13003

Abstract

Requirement engineering is an essential part of software development. The initial process in software development is to determine the needs of the stakeholders. To convert stakeholder needs into features of the system to be developed takes a long time, so it is a challenge for researchers to be able to extract features automatically based on the description of the needs of stakeholders. Previous research has also implemented feature extraction using user reviews on applications that public users have used. The feature extraction results will be used for feature development in future updated versions. The extraction process can use several proven methods to provide results that match the needs of the stakeholders in the system. This study compared the automatic feature extraction method using Natural Language Processing (NLP) with Hierarchical Pattern Recognition (HPR) on the dataset requirements and user reviews. Performance evaluation was conducted to test feature extraction results using Accuracy, precision, recall, and F-measure. The study results show that each method has advantages when implemented on both datasets. The NLP method excels in classifying the NL Requirement dataset. The HPR method has its advantages in extracting user review data.
Co-Authors Abdullah Faqih Septiyanto Patricia Gertrudis Manek