Sentiment Analysis of MyPertamina Application Reviews on Twitter Using the Naïve Bayes Classifier Method
Abstract
Downstream and Natural Gas Regulatory Agency (BPH Migas) Pertamina launched the mypertamina application for subsidized fuel oil (BBM) such as pertalite and diesel which will then be used as a digital financial service that integrates with the link aja application to ensure the subsidised fuel distribution process is truly on target. The problem after the launch of the mypertamina application harvested many pros and cons, one of which was that the application was difficult to use, complicated to use as evidenced in the comments on Twitter. From this problem it can be used as a sentiment analysis research to find out positive comments and negative comments in the mypertamina application review. The naive Bayes classifier method was used in this study for the classification process. In this study using as many as 1001 tweet data from the data collection process sourced from Twitter consisting of 494 positive and 507 negative, in the naive Bayes classifier classification process the accuracy value is 71% with 90% training data and 10% test data
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References
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[16] M. Christianto, J. Andjarwirawan, and A. Tjondrowiguno, “Aplikasi analisa sentimen pada komentar berbahasa Indonesia dalam objek video di website YouTube menggunakan metode Naïve Bayes classifier,” Jurnal Infra, vol. 8.1, pp. 255–259, 2020.
[17] L. A. Andika, P. A. N. Azizah, and R. Respatiwulan, “Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier,” Indonesian Journal of Applied Statistics, vol. 2, no. 1, p. 34, 2019, doi: 10.13057/ijas.v2i1.29998.
[18] S. Khairunnisa, A. Adiwijaya, and S. Al Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),” Jurnal Media Informatika Budidarma, vol. 5, no. 2, p. 406, 2021, doi: 10.30865/mib.v5i2.2835.
[2] M. A. Rizaty, “Indonesia menjadi salah satu negara dengan pengguna Twitter terbesar di dunia. Berdasarkan laporan We Are Social, jumlah pengguna Twitter di Indonesia mencapai 18,45 juta pada 2022.,” dataindonesia.id, 2022. https://dataindonesia.id/digital/detail/pengguna-twitter-di-indonesia-capai-1845-juta-pada-2022 (accessed Mar. 11, 2023).
[3] Zulfikar and Hardiansyah, “Apa Itu MyPertamina yang Bakal Dipakai buat Beli Pertalite dan Solar?,” KOMPAS.com, 2022. https://tekno.kompas.com/read/2022/06/06/12150027/apa-itu-mypertamina-yang-bakal-dipakai-buat-beli-pertalite-dan-solar?page=all (accessed Nov. 19, 2022).
[4] T. Yulianita, T. W. Utami, and M. Al Haris, “Analisis Sentimen Dalam Penanganan Covid-19 di Indonesia Menggunakan Naive Bayes Classifier,” Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika), pp. 235–243, 2020.
[5] D. Aryanti, “Analisis Sentimen Ibukota Negara Baru Menggunakan Metode Naïve Bayes Classifier,” Journal of Information System Research, vol. 3, no. 4, pp. 524–531, 2022, doi: 10.47065/josh.v3i4.1944.
[6] F. N. Hasan and M. Dwijayanti, “Analisis Sentimen Ulasan Pelanggan Terhadap Layanan Grab Indonesia Menggunakan Multinominal Naïve Bayes Classifier,” Jurnal Linguistik Komputasional, vol. 4, no. 2, pp. 52–58, 2021, doi: https://doi.org/10.26418/jlk.v4i2.61.
[7] E. B. Susanto, Paminto Agung Christianto, Mohammad Reza Maulana, and Sattriedi Wahyu Binabar, “Analisis Kinerja Algoritma Naïve Bayes Pada Dataset Sentimen Masyarakat Aplikasi NEWSAKPOLE Samsat Jawa Tengah,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 3, no. 3, pp. 234–241, Dec. 2022, doi: 10.37859/coscitech.v3i3.4343.
[8] A. Q. Surbakti, R. Hayami, and J. Al Amien, “Analisa Tanggapan Terhadap Psbb Di Indonesia Dengan Algoritma Decision Tree Pada Twitter,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 2, no. 2, pp. 91–97, 2021, doi: 10.37859/coscitech.v2i2.2851.
[9] E. Salehudin Basryah, A. Erfina, and C. Warman, “Analisis Sentimen Aplikasi Dompet Digital Di Era 4.0 Pada Masa Pendemi Covid-19 Di Play Store Menggunakan Algoritma Naive Bayes Classifier,” SISMATIK (Seminar Nasional Sistem Informasi dan Manajemen Informatika), pp. 189–196, 2021.
[10] I. Novitasari, T. B. Kurniawan, and D. A. Dewi, “Analisis Sentimen Masyarakat Terhadap Tweet Ruang Guru Menggunakan Algoritma Naive Bayes Classifier ( NBC ),” Institute of Computer Science (IOCS), vol. 6, no. 3, 2022.
[11] E. B. Susanto, P. A. Christianto, M. R. Maulana, and S. W. Binabar, “Analisis Kinerja Algoritma Naïve Bayes Pada Dataset Sentimen Masyarakat Aplikasi NEWSAKPOLE Samsat Jawa Tengah,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 3, no. 3, pp. 234–241, 2022, doi: 10.37859/coscitech.v3i3.4343.
[12] W. Dwitiayasa, “Klasifikasi Jenis Gangguan pada Base Transceiver Station (BTS) menggunakan Algoritma K-Nearest Neighbor, Naïve Bayes, dan Genetic Algorithm,” 2018.
[13] A. A. Permana et al., Machine Learning. Global Eksekutif Teknologi, 2023.
[14] A. Shiddicky and S. Agustian, “Analisis Sentimen Masyarakat Terhadap Kebijakan Vaksinasi Covid-19 pada Media Sosial Twitter menggunakan Metode Logistic Regression,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 3, no. 2, pp. 99–106, 2022, doi: 10.37859/coscitech.v3i2.3836.
[15] M. N. Rusardi, B. Rahayudi, and P. P. Adikara, “Analisis Sentimen Masyarakat terhadap Isu New Normal Scenario berdasarkan Opini dari Twitter menggunakan Algoritma Naive Bayes Classifier,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 6, no. 3, pp. 1434–1440, 2022.
[16] M. Christianto, J. Andjarwirawan, and A. Tjondrowiguno, “Aplikasi analisa sentimen pada komentar berbahasa Indonesia dalam objek video di website YouTube menggunakan metode Naïve Bayes classifier,” Jurnal Infra, vol. 8.1, pp. 255–259, 2020.
[17] L. A. Andika, P. A. N. Azizah, and R. Respatiwulan, “Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier,” Indonesian Journal of Applied Statistics, vol. 2, no. 1, p. 34, 2019, doi: 10.13057/ijas.v2i1.29998.
[18] S. Khairunnisa, A. Adiwijaya, and S. Al Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),” Jurnal Media Informatika Budidarma, vol. 5, no. 2, p. 406, 2021, doi: 10.30865/mib.v5i2.2835.
Published
2023-05-01
How to Cite
Nabilla Saumi Putri. (2023). Sentiment Analysis of MyPertamina Application Reviews on Twitter Using the Naïve Bayes Classifier Method. Jurnal CoSciTech (Computer Science and Information Technology), 4(1), 235-243. https://doi.org/10.37859/coscitech.v4i1.4789
Section
Articles
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