SENTIMENT ANALYSIS OF CUSTOMER SATISFACTION IN GOJEK AND GRAB APPLICATION REVIEWS USING THE NAIVE BAYES ALGORITHM

  • Ridha Faiz Ananda Information Technology, Faculty of Industrial Technology and Informatics, Universitas Prof. Dr. HAMKA Muhammadiyah, Indonesia
  • Alfi Syahri Arabic Literature, Faculty of Arabic Language, Al-Azhar University, Egypt.
  • Firman Noor Hasan Information Technology, Faculty of Industrial Technology and Informatics, Universitas Prof. Dr. HAMKA Muhammadiyah, Indonesia
Keywords: Customer satisfaction, Gojek, Grab, Naive Bayes, Online motorcycle taxi, Sentiment analysis

Abstract

Online motorcycle taxis are a widely favored mode of public transportation in Indonesia. There are several companies providing online motorcycle taxi services in Indonesia, with Gojek and Grab dominating the market. In this rapidly digitizing era, social media has become a platform for Indonesian citizens to express their evaluations and opinions. One common platform used by users to express their evaluations is the Google Play Store, where users can provide ratings and opinions on the applications they use, including users of Gojek and Grab applications.This research aims to understand and analyze the sentiments of the public towards the two dominant giants in the online motorcycle taxi market in Indonesia based on review data from the Google Play Store using the Naive Bayes algorithm. The data used consists of user reviews from May 14, 2023, to July 26, 2023, totaling 300 data points for each application. This data will undergo pre-processing to remove irrelevant elements. The Naive Bayes algorithm is used to classify the existing sentiments into two classes: positive and negative.The results of this research conclude that Gojek users give positive reviews at 49% and negative reviews at 51%, which include praises for the drivers and services provided by the company, complaints about the heaviness of the application, and some disruptions in the Gopay payment method. Meanwhile, Grab users give positive reviews at 67% and negative reviews at 33%, which include customer satisfaction with attractive promos, complaints about the heaviness of the application after the latest update, and the high cost of Grabexpress and Grabfood services.

Downloads

Download data is not yet available.

References

O. Halilintarsyah, “Ojek Online, Pekerja atau Mitra?,” Jurnal Persaingan Usaha, vol. 02, pp. 64–74, Dec. 2021, doi: https://doi.org/10.55869/kppu.v2i.24.

Yusuf Wahyu Setiya Putra et al., Pengantar Aplikasi Mobile. 2023.

K. Wongso and W. Purnama Sari, “Analisa UX Writing terhadap User Experience pada Pengguna Aplikasi Grab,” Prologia, vol. 4, pp. 1–9, Feb. 2020, doi: https://doi.org/10.24912/pr.v4i1.6415.

J. C. Jansela Situmorang, F. Akbar Maulana Hutabarat, W. Pong Lan, N. Nugroho, and Lisa, “Kualitas Pelayanan Mitra Gojek Terhadap Kepuasan Pengguna Layanan Go-Ride,” ARBITRASE, vol. 2, pp. 51–54, Nov. 2021, doi: https://doi.org/10.47065/arbitrase.v2i2.285.

D. Darwis, N. Siskawati, and Z. Abidin, “Penerapan Algoritma Naive Bayes untuk Analisis Sentimen Review Data Twitter BMKG Nasional,” TEKNO KOMPAK, vol. 15, no. 1, pp. 131–145, 2021, doi: https://doi.org/10.33365/jtk.v15i1.744.

M. Dwijayanti, F. Noor Hasan, and R. Zein Adam, “Analisis Sentimen Pada Ulasan Pelanggan Menggunakan Metode Naïve Bayes Classifier (Studi Kasus: Grab Indonesia),” Prosiding Seminar Nasional Teknoka, vol. 6, pp. 93–99, Jan. 2022, doi: 10.22236/teknoka.v6i1.441.

A. Wibowo, F. Noor Hasan, L. Akbar Ramadhan, R. Nurhayati, and dan Arief Wibowo, “Analisis Sentimen Opini Masyarakat Terhadap Keefektifan Pembelajaran Daring Selama Pandemi COVID-19 Menggunakan Naïve Bayes Classifier,” Asiimetrik:, vol. 4, pp. 239–248, 2022, doi: https://doi.org/10.35814/asiimetrik.v4i1.3577.

A. Safira and F. N. Hasan, “Analisis Sentimen Masyarakat Terhadap Paylater Menggunakan Metode Naive Bayes Classifier,” Jurnal Sistem Informasi, vol. 5, no. 1, 2023, doi: https://doi.org/10.31849/zn.v5i1.12856.

F. Setya Ananto and F. N. Hasan, “Implementasi Algoritma Naïve Bayes Terhadap Analisis Sentimen Ulasan Aplikasi MyPertamina pada Google Play Store,” Jurnal ICT : Information Communication & Technology, vol. 23, no. 1, pp. 75–80, 2023, [Online]. Available: https://ejournal.ikmi.ac.id/index.php/jict-ikmi

N. Tri Romadloni, I. Santoso, S. Budilaksono, and M. Ilmu Komputer STMIK Nusa Mandiri Jakarta, “Perbandingan Metode Naive Bayes, Knn Dan Decision Tree Terhadap Analisis Sentimen Transportasi Krl Commuter Line,” Jurnal IKRA-ITH Informatika, vol. 3, no. 2, pp. 1–9, 2019.

M. I. Ahmadi, D. Gustian, and F. Sembiring, “Analisis Sentiment Masyarakat terhadap Kasus Covid-19 pada Media Sosial Youtube dengan Metode Naive bayes,” Jurnal Sains Komputer & Informatika (J-SAKTI, vol. 5, no. 2, pp. 807–814, 2021, doi: http://dx.doi.org/10.30645/j-sakti.v5i2.378.

W. Yulita et al., “Analisis Sentimen Terhadap Opini Masyarakat Tentang Vaksin Covid-19 Menggunakan Algoritma Naïve Bayes Classifier,” JDMSI, vol. 2, no. 2, pp. 1–9, 2021, doi: https://doi.org/10.33365/jdmsi.v2i2.1344.

D. Setian and I. Seprina, “Analisis Sentimen Masyarakat Terhadap Data Tweet Lazada Menggunakan Text Mining Dan Algoritma Naive Bayes Classifier,” Bina Darma Conference on Computer Science, vol. 1, no. 4, pp. 998–1004, 2020.

Rahmadhan Adinugroho, “Perbandingan Rasio Split Data Training Dan Data Testing Menggunakan Metode Lstm Dalam Memprediksi Harga Indeks Saham Asia,” 2022.

D. Azzahra Nasution, H. H. Khotimah, and N. Chamidah, “Perbandingan Normalisasi Data Untuk Klasifikasi Wine Menggunakan Algoritma K-NN,” CESS (Journal of Computer Engineering System and Science), vol. 4, no. 1, pp. 2502–7131, 2019.

D. Normawati and S. A. Prayogi, “Implementasi Naïve Bayes Classifier Dan Confusion Matrix Pada Analisis Sentimen Berbasis Teks Pada Twitter,” Jurnal Sains Komputer & Informatika (J-SAKTI, vol. 5, no. 2, pp. 697–711, 2021, doi: http://dx.doi.org/10.30645/j-sakti.v5i2.369.

A. Rahim, K. Kusrini, and E. T. Luthfi, “Convolutional Neural Network untuk Kalasifikasi Penggunaan Masker,” Inspiration: Jurnal Teknologi Informasi dan Komunikasi, vol. 10, no. 2, p. 109, Dec. 2020, doi: 10.35585/inspir.v10i2.2569.

K. Nugroho, F. N. Hasan, P. Korespondensi, : Firman, N. Hasan, and R. Artikel, “Analisis Sentimen Masyarakat Mengenai RUU Perampasan Aset Di Twitter Menggunakan Metode Naïve Bayes Analysis of Public Sentiment Regarding RUU Perampasan Aset on Twitter Using Naïve Bayes Method,” SMATIKA : STIKI Informatika Jurnal, vol. 13, no. 2, p. 13, 2023, doi: 10.32664/smatika.v13i02.899.

A. Saputra and F. Noor Hasan, “Analisis Sentimen Terhadap Aplikasi Coffee Meets Bagel Dengan Algoritma Naïve Bayes Classifier,” SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan, vol. 2, no. 2, pp. 465–474, Jan. 2023, doi: 10.54443/sibatik.v2i2.579.

M. E. Lasulika, “Komparasi Naïve Bayes, Support Vector Machine Dan K-Nearest Neighbor Untuk Mengetahui Akurasi Tertinggi Pada Prediksi Kelancaran Pembayaran Tv Kabel,” ILKOM Jurnal Ilmiah, vol. 11, no. 1, pp. 11–16, May 2019, doi: https://doi.org/10.33096/ilkom.v11i1.408.11-16.

M. A. Rosari, ) Wasino, and ) Tony, “Analisis Sentimen Tanggapan Masyarakat Terhadap Bantuan Sosial Pemerintah Di Masa Pandemi Covid-19 Pada Platform Twitter,” Jurnal Ilmu Komputer dan Sistem Informasi, vol. 10, no. 1, 2022, doi: https://doi.org/10.24912/jiksi.v10i1.17867.

N. L. W. S. R. Ginantra, C. P. Yanti, G. D. Prasetya, I. B. G. Sarasvananda, and I. K. A. G. Wiguna, “Analisis Sentimen Ulasan Villa di Ubud Menggunakan Metode Naive Bayes, Decision Tree, dan K-NN,” Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), vol. 11, no. 3, pp. 205–215, Dec. 2022, doi: 10.23887/janapati.v11i3.49450.

D. Pardede, I. Firmansyah, M. Handayani, M. Riandini, and R. Rosnelly, “Comparison Of Multilayer Perceptron’s Activation And Optimization Functions In Classification Of Covid-19 Patients,” JURTEKSI (Jurnal Teknologi dan Sistem Informasi), vol. 8, no. 3, pp. 271–278, Aug. 2022, doi: 10.33330/jurteksi.v8i3.1482.

A. Halifa and R. Novita, “Application Of Naïve Bayes Classifier Algorithm In Determining The Level Of Customer Satisfaction With Rumbai Post Office Services,” Jurnal Teknik Informatika (JUTIF), vol. 4, no. 6, pp. 1295–1304, 2023, doi: 10.52436/1.jutif.2023.4.6.1054.

M. Siddik, R. Noratama Putri, and Y. Desnelita, “Classification Of Student Satisfaction On Higher Education Services Using Naïve Bayes Algorithm,” Journal of Information Technology and Computer Science (INTECOMS), vol. 3, no. 2, 2020, doi: https://doi.org/10.31539/intecoms.v3i2.1654

Published
2024-02-16
How to Cite
[1]
R. F. Ananda, A. Syahri, and F. N. Hasan, “SENTIMENT ANALYSIS OF CUSTOMER SATISFACTION IN GOJEK AND GRAB APPLICATION REVIEWS USING THE NAIVE BAYES ALGORITHM”, J. Tek. Inform. (JUTIF), vol. 5, no. 1, pp. 233-241, Feb. 2024.