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GOJEK DATA ANALYSIS THROUGH TEXT MINING USING SUPPORT VECTOR MACHINE (SVM) AND K-NEAREST NEIGHBOR (KNN)

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 2 (2025) · hlm. 889–902

DOI
10.30598/barekengvol19iss2pp889-902
ISSN
2615-3017, 1978-7227
Terbit
2025-04-01
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

The main focus of this research is to apply and test the effectiveness of SVM and KNN methods in Gojek data text analysis. This research will examine how the two methods can classify user comments and feedback and identify data sentiment analysis at the same time practically help Gojek understand user needs and improve service quality. The data obtained through scrapping is categorized into positive and negative sentiment. Data is taken from Gojek application user reviews throughout the year 2022 with a total of 1148 sentiment data with a percentage of 80% training data and 20% testing data. Evaluation of model performance using Confusion Matrix and AUC-ROC Curve shows that SVM is more effective than KNN, with accuracy on training data of 92.55% for SVM and 81.71% for KNN, as well as accuracy on testing data of 82.40% for SVM and 77,09% for KNN.

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  • Yogyakarta State University
  • Indonesia Open University
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Madiha Dzakiyyah ChairunnisaAfiliasi tidak diketahui3
Muhammad Rif'anAfiliasi tidak diketahui3
Avelyn Pingkan KomunaAfiliasi tidak diketahui3
Dwi Astuti AprijaniAfiliasi tidak diketahui2
Fitria AmastiniAfiliasi tidak diketahui2
Moh. Rizky Putra Aji UtamaAfiliasi tidak diketahui2
Sri Maulidia PermatasariIndonesia Open University1
Arya YusufYogyakarta State University1
Siswantoyo SiswantoyoYogyakarta State University1
Ria DymyatiYogyakarta State University1
Putu SudiraYogyakarta State University1
Yanuar Agung FadlullahYogyakarta State University1
Yoga SyahriaYogyakarta State University1
Yanuar Agung FadlullahAfiliasi tidak diketahui1
Asma’ Khoirunnisa’Yogyakarta State University1
Yosef BudimanAfiliasi tidak diketahui1
Gilang Adi PrasetyoAfiliasi tidak diketahui1
Hanifah Mar’atush ShalihahAfiliasi tidak diketahui1
Sugiri SugiriAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">GOJEK DATA ANALYSIS THROUGH TEXT MINING USING SUPPORT VECTOR MACHINE (SVM) AND K-NEAREST NEIGHBOR (KNN)</dc:title>
	<dc:creator>Hasanah, Siti Hadijah</dc:creator>
	<dc:creator>Maulana, Muhamad Riyan</dc:creator>
	<dc:creator>Nurdiana, Dian</dc:creator>
	<dc:description xml:lang="en-US">The main focus of this research is to apply and test the effectiveness of SVM and KNN methods in Gojek data text analysis. This research will examine how the two methods can classify user comments and feedback and identify data sentiment analysis at the same time practically help Gojek understand user needs and improve service quality. The data obtained through scrapping is categorized into positive and negative sentiment. Data is taken from Gojek application user reviews throughout the year 2022 with a total of 1148 sentiment data with a percentage of 80% training data and 20% testing data. Evaluation of model performance using Confusion Matrix and AUC-ROC Curve shows that SVM is more effective than KNN, with accuracy on training data of 92.55% for SVM and 81.71% for KNN, as well as accuracy on testing data of 82.40% for SVM and 77,09% for KNN.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-04-01</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14792</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss2pp889-902</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application; 889-902</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss2year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14792/9956</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Siti Hadijah Hasanah, Muhamad Riyan Maulana, Dian Nurdiana</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>