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All Journal IPTEK The Journal for Technology and Science JSAI (Journal Scientific and Applied Informatics)
Brian Rizqi Paradisiaca Darnoto
Universitas Jember
Computer Science & IT

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A Systematic Comparison of Software Requirements Classification Fajar Baskoro; Rasi Aziizah Andrahsmara; Brian Rizqi Paradisiaca Darnoto; Yoga Ari Tofan
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.v32i3.13005

Abstract

Software requirements specification (SRS) is an essential part of software development. SRS has two features: functional requirements (FR) and non-functional requirements (NFR). Functional requirements define the needs that are directly in contact with stakeholders. Non-functional requirements describe how the software provides the means to carry out functional requirements. Non-functional requirements are often mixed with functional requirements. This study compares four primarily used machine learning methods for classifying functional and non-functional requirements. The contribution of our research is to use the PROMISE and SecReq (ePurse) dataset, then classify them by comparing the FastText+SVM, FastText+CNN, SVM, and CNN classification methods. CNN outperformed other methods on both datasets. The accuracy obtained by CNN on the PROMISE dataset is 99% and on the Seqreq dataset is 94%.
Integrasi Metode Pengambilan Keputusan Multi kriteria untuk Penilaian Lahan Tembakau: Studi Kasus Menggunakan SMART, TOPSIS, dan AHP Firmawan, Dony Bahtera; Brian Rizqi Paradisiaca Darnoto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8482

Abstract

The results of decision making play an important role in achieving a goal in solving certain problems. Decision making process requires data or supporting evidence that can be used as a guide for the selection of solutions based on available alternatives, to produce choices that can increase productivity. Multi Criteria Decision Making (MCDM) method for the analysis of research data namely SMART, TOPSIS, and AHP. The three methods are tested, because each MCDM method has a different way of working or algorithm, so it is necessary to experiment with certain cases. This study aims to determine the performance of the SMART, TOPSIS, and AHP methods with a case study of selecting of tobacco land recommendations. The application of three MCDM methods for alternative analysts of prospective tobacco land based on testing to determine the accuracy of comparing the results/output of the system with expert recommendation solutions using a sample of 10 tobacco land that produce priority/ranking for tobacco land recommendations, shows that the performance of the three methods produces priority selection results different, with an accuracy of SMART 80
Co-Authors Baskoro, Fajar Firmawan, Dony Bahtera Rasi Aziizah Andrahsmara Yoga Ari Tofan