Melola Discovery

← Melola Discovery

Jurnal

Penggunaan Seleksi Fitur Query Expansion Ranking dan Genetic Algorithm-Support Vector Machine untuk Analisis Sentimen pada Aplikasi Perbankan Jenius

ESTIMASI: Journal of Statistics and Its Application · Vol. 7 No. 1 (2026) · pp. 147–158

DOI
10.20956/ejsa.v7i1.47395
ISSN
2721-379X, 2721-3803
Published
2026-05-05
Publisher
Hasanuddin University
Language
en

Abstract

Jenius is a digital banking product from BTPN launched in 2016. In 2021, various opinions emerged on Twitter regarding cases of lost customer funds, necessitating sentiment analysis to understand public perception. This study used the Support Vector Machine (SVM) method with two feature selection approaches: Query Expansion Ranking (QER) and Genetic Algorithm (GA). The data used were 2,008 manually labeled tweets. The results showed that the QER-SVM method produced an accuracy of 87.81%, while the GA-SVM achieved an accuracy of 88.31% with improvements in precision and F-measure. Thus, the combination of Genetic Algorithm and SVM was more effective in classifying sentiment towards the Jenius application on Twitter.

Keywords

Collaboration network of the authors

40 authors · 121 co-authorship links · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Padjadjaran University
  • Universitas Halu Oleo
  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Raupong RaupongAffiliation unknown3
Anisa KalondengAffiliation unknown3
Andi Kresna JayaAffiliation unknown2
Anna IslamiyatiAffiliation unknown2
Muhammad FadilAffiliation unknown2
Andi Isna YunitaAffiliation unknown2
Budi AyuningsihPadjadjaran University1
Iman HernamanPadjadjaran University1
Tidi DhalikaPadjadjaran University1
Destu Putra RosmawanAffiliation unknown1
Dedi RahmatPadjadjaran University1
Ansharullah AnsharullahUniversitas Halu Oleo1
Abdu Rahman BacoAffiliation unknown1
Alfiana AntohAffiliation unknown1
Yundy HafizriandaAffiliation unknown1
Anisa AnisaSultan Ageng Tirtayasa University1
Bunga ApriliaAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Grace Oktavia YusufAffiliation unknown1
Nurul IkhsaniAffiliation unknown1
Hajratul Ashwad KAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Afifah Mutiah NurdinAffiliation unknown1
Muh. Indirwan ArfanAffiliation unknown1
Wa Ode Sitti Amni AmniAffiliation unknown1
Kevin Ekarinaldo PalunganAffiliation unknown1
Sitti SahrimanAffiliation unknown1
A.Muthiah Nur AngrianyAffiliation unknown1
Rini JamalAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
Andi FebriyantiAffiliation unknown1
Rahmiati RahimAffiliation unknown1
Nurhaliza RaisAffiliation unknown1
Maryana MaharaniAffiliation unknown1
Rahmat HermawanAffiliation unknown1
Fadlan AminAffiliation unknown1
Ahmad Ryan Al AqshaAffiliation unknown1

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://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Penggunaan Seleksi Fitur Query Expansion Ranking dan Genetic Algorithm-Support Vector Machine untuk Analisis Sentimen pada Aplikasi Perbankan Jenius</dc:title>
	<dc:creator xml:lang="en">Haksar, Haksar</dc:creator>
	<dc:creator xml:lang="en">Siswanto, Siswanto</dc:creator>
	<dc:creator xml:lang="en">Ilyas, Nirwan</dc:creator>
	<dc:subject xml:lang="en">Genetic Algorithm</dc:subject>
	<dc:subject xml:lang="en">Jenius</dc:subject>
	<dc:subject xml:lang="en">Query Expansion Ranking</dc:subject>
	<dc:subject xml:lang="en">SVM</dc:subject>
	<dc:subject xml:lang="en">GA-SVM</dc:subject>
	<dc:subject xml:lang="en">QER-SVM</dc:subject>
	<dc:description xml:lang="en">Jenius is a digital banking product from BTPN launched in 2016. In 2021, various opinions emerged on Twitter regarding cases of lost customer funds, necessitating sentiment analysis to understand public perception. This study used the Support Vector Machine (SVM) method with two feature selection approaches: Query Expansion Ranking (QER) and Genetic Algorithm (GA). The data used were 2,008 manually labeled tweets. The results showed that the QER-SVM method produced an accuracy of 87.81%, while the GA-SVM achieved an accuracy of 88.31% with improvements in precision and F-measure. Thus, the combination of Genetic Algorithm and SVM was more effective in classifying sentiment towards the Jenius application on Twitter.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2026-05-05</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/47395</dc:identifier>
	<dc:identifier>10.20956/ejsa.v7i1.47395</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 7, No. 1, Januari, 2026 : Estimasi; 147-158</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/47395/14392</dc:relation>
</oai_dc:dc>