Text Mining Untuk Analisis Sentimen Pelanggan Terhadap Layanan Uang Elektronik Menggunakan Algoritma Support Vector Machine

Authors

  • Fajar Romadoni Universitas Singaperbangsa Karawang
  • Yuyun Umaidah Universitas Singaperbangsa Karawang
  • Betha Nurina Sari Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.32736/sisfokom.v9i2.903

Keywords:

Classification, Electronic Money, Kernel, Sentiment Analysis, Support Vector Machine

Abstract

Electronic money is a cashless payment instrument whose money is stored in media server or chip that can be moved for the benefit of payment transactions or fund transfers. In Indonesia, there are already many electronic money products, one of which is OVO. OVO is very popular with the people of Indonesia because it offers many promos such as discounts and cashback. But over time, that much promotion is detrimental to OVO shareholders, so the portion of promo given by OVO to its customers is finally reduced. That incident caused many pros and cons opinions about OVO, one of them is on social media Twitter. Sentiment analysis can be used as a solution to process the opinions of OVO customers on Twitter. This study aims to classify the customer opinions on OVO services into positive and negative classes. This study uses the Support Vector Machine algorithm with 3852 data taken from Twitter with keyword @ovo_id using web scraping techniques. The dataset divided into two classes, 2034 positive and 1818 negative sentiment data. The classification process is carried out with four splitting data scenarios, with 60:40, 70:30, 80:20, 90:10 data ratio and with four kernel such as linear, rbf, sigomid, and polynomial. The final results show that the greatest accuracy value obtained by linear kernel with 90:10 data ratio which gets an accuracy value of 98.7%.

References

Suharni, "Uang Elektronik (E-Money) ditinjau dari Perspektif Hukum dan Perubahan Sosial," Jurnal Spektrum Hukum, pp. 15-43, 2018.

"Kata Data," 25 September 2019. [Online]. Available: https://katadata.co.id/berita/2019/09/25/ovo-jadi-dompet-digital-terbesar-di-indonesia-berkat-ekosistem-grab.

"CNN Indonesia," 29 November 2019. [Online]. Available: https://www.cnnindonesia.com/ekonomi/20191129080739-92-452526/bendera-putih-lippo-bakar-uang-untuk-ovo.

E. M. Sipayung, H. Maharani and I. Zefanya, "Perancangan Sistem Analisis Sentimen Komentar Pelanggan Menggunakan Metode Naive Bayes Classifier," Jurnal Sistem Informasi (JSI), Vol. 8, NO.1, pp. 958-965, 2016.

I. A. Muis and M. Affandes, "Penerapan Metode Support Vector Machine (SVM) Menggunakan Kernel Radial Basis Function (RBF) Pada Klasifikasi Tweet," Journal of Science Technology and Industry, vol. 12, no. 2, pp. 189-197, 2015.

Neneng, K. Adi and R. R. Isnanto, "Support Vector Machine Untuk Klasifikasi Citra Jenis Daging Berdasarkan Tekstur Menggunakan Ekstraksi Ciri Gray Level Co-Occurance Matrices (GLCM)," Jurnal Sistem Informasi Bisnis, pp. 1-10, 2016.

M. Awad and R. Khanna, Efficient Learning Machines : Theories, Concepts, Applications for Engineers and System Designers, New York City: Apress, 2015.

R. Munawarah, O. Soesanto and M. R. Faisal, "Penerapan Metode Support Vector Machine Pada Diagnosa Hepatitis," Kumpulan JurnaL Ilmu Komputer (KLIK), vol. 04, no. 01, pp. 103-113, 2016.

Y. Mardi, "Data Mining : Klasifikasi Menggunakan Algoritma C4.5," Jurnal Edik Informatik, pp. 213-219, 2017.

M. F. Fibrianda and A. Bhawiyuga, "Analisis Perbandingan Akurasi Deteksi Serangan Pada Jaringan Komputer Dengan Metode Naïve Bayes Dan Support Vector Machine (SVM)," Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, pp. 3112-3123, 2018.

F. R. Wibowo, D. S. Rusdianto and A. Arwan, "Pengembangan Sistem Pengumpulan Promo E-Commerce Berbasis Website Dengan Menerapkan Teknik Web Scraping Dalam Proses Pengambilan Data Promo," Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, pp. 2887-2893, 2019.

D. Haryalesmana, "Github," 24 March 2017. [Online]. Available: https://github.com/masdevid/ID-OpinionWords.

R. Mahendrajaya, G. A. Buntoro and M. B. Setyawan, "Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based dan Support Vector Machine," KOMPUTEK : Jurnal Teknik Universitas Muhammadiyah Ponorogo, pp. 52-63, 2019.

M. W. Sardjono, M. Cahyanti, M. Mujahidin and R. Arianty, "Pendeteksi Kesamaan Kata Untuk Judul Penulisan Berbahasa Indonesia Menggunakan Algoritma Stemming Nazief-Ardiani," SEBATIK, pp. 138-146, 2018.

R. Diani, U. N. Wisesty and A. Aditsania, "Analisis Pengaruh Kernel Support Vector Machine (SVM) pada Klasifikasi Data Microarray untuk Deteksi Kanker," Ind. Journal On Computing Volume 2, pp. 109-117, 2017.

Downloads

Additional Files

Published

2020-07-22

Issue

Vol. 9 No. 2 (2020): JULI

Section

Articles

License

The copyright of the article that accepted for publication shall be assigned to Jurnal Sisfokom (Sistem Informasi dan Komputer) and LPPM ISB Atma Luhur as the publisher of the journal. Copyright includes the right to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.

Jurnal Sisfokom (Sistem Informasi dan Komputer), LPPM ISB Atma Luhur, and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Jurnal Sisfokom (Sistem Informasi dan Komputer) are the sole and exclusive responsibility of their respective authors.

Jurnal Sisfokom (Sistem Informasi dan Komputer) has full publishing rights to the published articles. Authors are allowed to distribute articles that have been published by sharing the link or DOI of the article. Authors are allowed to use their articles for legal purposes deemed necessary without the written permission of the journal with the initial publication notification from the Jurnal Sisfokom (Sistem Informasi dan Komputer).

The Copyright Transfer Form can be downloaded [Copyright Transfer Form Jurnal Sisfokom (Sistem Informasi dan Komputer).

This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s). After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted. The copyright form should be signed originally, and send it to the Editorial in the form of scanned document to sisfokom@atmaluhur.ac.id.