A Semantic Comparison of Feature Requirements Extraction Methods
| Main Authors: | Manek, Patricia Gertrudis; Information Technology Department, Universitas Timor, Kefamenamu, Septiyanto, Abdullah Faqih; Informatics Master Programme, Institut Teknologi Sepuluh Nopember., Nugroho, Adi Setyo; Informatics Master Programme, Institut Teknologi Sepuluh Nopember. |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
IPTEK, LPPM, Institut Teknologi Sepuluh Nopember
, 2021
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| Subjects: | |
| Online Access: |
https://iptek.its.ac.id/index.php/jts/article/view/13003 https://iptek.its.ac.id/index.php/jts/article/view/13003/6884 |
Daftar Isi:
- 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.