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Jurnal SINTA 2

NOISE DETECTION IN SOFTWARE REQUIREMENTS SPECIFICATION DOCUMENT USING SPECTRAL CLUSTERING

JUTI: Jurnal Ilmiah Teknologi Informasi · Vol. 17 No. 1 (2019) · pp. 30–37

DOI
10.12962/j24068535.v17i1.a771
ISSN
2406-8535, 1412-6389
Published
2019-03-12
Publisher
Institut Teknologi Sepuluh Nopember
Language
eng

Abstract

Requirements engineering phase in software development resulting in a SRS (Software Requirements Specification) document. The use of natural language approach in generating such document has some drawbacks that caused 7 common mistakes among the engineer which had been formulated by Meyer as "The 7 sins of specifier". One of the 7 common mistakes is noise. This study attempted to detect noise in software requirements with spectral clustering. The clustering algorithm working on fewer dimensions compared to others. The resulting kappa coefficient is 0.4426. The result showed that the consistency between noise prediction and noise assessment made by three annotators is still low.

Collaboration network of the authors

17 authors · 30 co-authorship links

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  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Yasinta Oktaviana Legu RemaAffiliation unknown1
Firman Yosef Rangga NeonbeniAffiliation unknown1
Risald RisaldAffiliation unknown1
Siprianus Septian ManekInstitut Teknologi Sepuluh Nopember1
Reza FauzanInstitut Teknologi Sepuluh Nopember1
Nurul Fajrin AriyaniInstitut Teknologi Sepuluh Nopember1
Utomo PujiantoAffiliation unknown1
Umi Laili YuhanaInstitut Teknologi Sepuluh Nopember1
Diana PurwitasariInstitut Teknologi Sepuluh Nopember1
Dian SaputraAffiliation unknown1
Esti YuniarAffiliation unknown1
Joko PrasetyoInstitut Teknologi Sepuluh Nopember1
Ratih Nur Esti AnggrainiInstitut Teknologi Sepuluh Nopember1
Ainatul MaulidaInstitut Teknologi Sepuluh Nopember1
Depandi EndaInstitut Teknologi Sepuluh Nopember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://juti.if.its.ac.id/index.php/juti/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">NOISE DETECTION IN SOFTWARE REQUIREMENTS SPECIFICATION DOCUMENT USING SPECTRAL CLUSTERING</dc:title>
	<dc:creator xml:lang="en">Manek, Patricia Gertrudis</dc:creator>
	<dc:creator xml:lang="en">Siahaan, Daniel</dc:creator>
	<dc:description xml:lang="en">Requirements engineering phase in software development resulting in a SRS (Software Requirements Specification) document. The use of natural language approach in generating such document has some drawbacks that caused 7 common mistakes among the engineer which had been formulated by Meyer as "The 7 sins of specifier". One of the 7 common mistakes is noise. This study attempted to detect noise in software requirements with spectral clustering. The clustering algorithm working on fewer dimensions compared to others. The resulting kappa coefficient is 0.4426. The result showed that the consistency between noise prediction and noise assessment made by three annotators is still low.</dc:description>
	<dc:publisher xml:lang="en">Institut Teknologi Sepuluh Nopember</dc:publisher>
	<dc:date>2019-03-12</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://juti.if.its.ac.id/index.php/juti/article/view/771</dc:identifier>
	<dc:identifier>10.12962/j24068535.v17i1.a771</dc:identifier>
	<dc:source xml:lang="en">JUTI: Jurnal Ilmiah Teknologi Informasi; Vol 17, No. 1, Januari 2019; 30-37</dc:source>
	<dc:source>2406-8535</dc:source>
	<dc:source>1412-6389</dc:source>
	<dc:source>10.12962/j24068535.v17i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://juti.if.its.ac.id/index.php/juti/article/view/771/380</dc:relation>
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