ANALYSIS OF PUBLIC SENTIMENT ON GOOGLE PLAY STORE TIJE APPLICATION USERS USING NAÏVE BAYES CLASSIFIER METHOD

Laila Atikah Sari; Nindia Fitri  Ramadhita; Firman Noor Hasan

doi:10.52436/1.jutif.2024.5.1.1648

Laila Atikah Sari Informatics Engineering, Faculty of Industrial Technology and Informatics, Universitas Muhamadiyah Prof. Dr. Hamka, Indonesia
Nindia Fitri Ramadhita International Relations, Faculty of Social Sciences, Sakarya Universitesi, Turkey
Firman Noor Hasan Informatics Engineering, Faculty of Industrial Technology and Informatics, Universitas Muhamadiyah Prof. Dr. Hamka, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.1.1648

Keywords: Google Play Store, Naïve Bayes Classifier, Reviews, Sentiment Analysis, Tije App

Abstract

Advances in information technology have an influence on companies and agencies to innovate. The Tije application is one of the innovations that has been made by PT Tranportasi Jakarta which is used by its users. However, each application has advantages and disadvantages, including the Tije application which has an impact on the disruption of the function of supporting user services as the purpose of making this application. This can certainly trigger a response from users which can be submitted through the review column on the Google Play Store platform. This research was conducted to analyze the sentiment of community reviews of Tije application users on the Google Play Store platform using the Naïve Bayes Classifier method. Tije application review data collection is done by web scrapping techniques on the Google Play Store using Google Colab. Then, the collected data will be processed to eliminate inappropriate elements and get sentiment content on each review, whether the review falls into the category of positive or negative sentiment towards the Tije application. The results of this study conclude that users are dissatisfied and disappointed with the services available on the Tije application. This is evidenced by the number of negative sentiments that are more dominant and in the application of the Naive Bayes algorithm in this study, obtained quite good accuracy results of 85.88%.

Downloads

Download data is not yet available.

References

U. Yudatama et al., Memahami Teknologi Informasi Prinsip: Prinsip, Pengembangan, dan Penerapan, Pertama. Kaizen Media Publishing, 2023.

K. T.B and Syarifuddin, “Perancangan Sistem Aplikasi Pemesanan Makanan dan Minuman pada Cafetaria No Caffe di Tanjunga Balai Karimun Menggunakan Bahasa Pemrograman PHP dan MYSQL,” J. TIKAR, vol. 1, no. 2, pp. 192–206, 2020, doi: https://doi.org/10.51742/teknik_informatika.v1i2.153.

A. I. Tanggraeni and M. N. N. Sitokdana, “Analisis Sentimen Aplikasi E-Government pada Google Play Menggunakan Algoritma Naïve Bayes,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 2, pp. 785–795, 2022, doi: 10.35957/jatisi.v9i2.1835.

N. L. W. Rita Kurniati, “Dampak Ekonomi Pengoperasian Transjakarta Ditinjau dari Persepsi Pengguna,” J. Penelit. Transp. Darat, vol. 22, no. 2, pp. 194–205, 2021, doi: 10.25104/jptd.v22i2.1669.

R. Wahyuni and Y. Irawan, “Aplikasi E-Book Untuk Aturan Kerja Berbasis Web Di Pengadilan Negeri Muara Bulian Kelas Ii Jambi,” J. Ilmu Komput., vol. 9, no. 1, pp. 20–26, 2020, doi: 10.33060/jik/2020/vol9.iss1.152.

Y. W. S. Putra et al., Pengantar Aplikasi Mobile, Pertama. Haura Utama, 2023.

A. P. Giovani, A. Ardiansyah, T. Haryanti, L. Kurniawati, and W. Gata, “Analisis Sentimen Aplikasi Ruang Guru Di Twitter Menggunakan Algoritma Klasifikasi,” J. Teknoinfo, vol. 14, no. 2, p. 115, 2020, doi: 10.33365/jti.v14i2.679.

A. Erfina, E. S. Basryah, A. Saepulrohman, and D. Lestari, “Analisis Setimen Aplikasi Pembelajaran Online di Play Store pada Masa Pandemi Covid-19 Menggunakan Algoritma Support Vector Machine (SVM),” Semasif, pp. 145–152, 2020.

“Google Play,” Google Play Store, 2023. https://play.google.com/store/apps/details?id=com.transjakarta.tijeku&hl=en_US&pli=1

Alfandi Safira and F. N. Hasan, “Analisis Sentimen Masyarakat Terhadap Paylater Menggunakan Metode Naive Bayes Classifier,” Zo. J. Sist. Inf., vol. 5, no. 1, pp. 59–70, 2023, doi: 10.31849/zn.v5i1.12856.

R. Wahyudi and G. Kusumawardana, “Analisis Sentimen pada Aplikasi Grab di Google Play Store Menggunakan Support Vector Machine,” J. Inform., vol. 8, no. 2, pp. 200–207, 2021, doi: 10.31294/ji.v8i2.9681.

A. Syakir and F. N. Hasan, “Analisis Sentimen Masyarakat Terhadap Perilaku Korupsi Pejabat Pemerintah Berdasarkan Tweet Menggunakan Naive Bayes Classifier,” J. Media Inform. Budidarma, vol. 7, no. 4, pp. 1796–1805, 2023, doi: 10.30865/mib.v7i4.6648.

D. Duei Putri, G. F. Nama, and W. E. Sulistiono, “Analisis Sentimen Kinerja Dewan Perwakilan Rakyat (DPR) Pada Twitter Menggunakan Metode Naive Bayes Classifier,” J. Inform. dan Tek. Elektro Terap., vol. 10, no. 1, pp. 34–40, 2022, doi: 10.23960/jitet.v10i1.2262.

A. Wibowo, Firman Noor Hasan, Rika Nurhayati, and Arief Wibowo, “Analisis Sentimen Opini Masyarakat Terhadap Keefektifan Pembelajaran Daring Selama Pandemi COVID-19 Menggunakan Naïve Bayes Classifier,” J. Asiimetrik J. Ilm. Rekayasa Inov., vol. 4, pp. 239–248, 2022, doi: 10.35814/asiimetrik.v4i1.3577.

A. Rozaq, Y. Yunitasari, K. Sussolaikah, E. R. N. Sari, and R. I. Syahputra, “Analisis Sentimen Terhadap Implementasi Program Merdeka Belajar Kampus Merdeka Menggunakan Naïve Bayes, K-Nearest Neighboars Dan Decision Tree,” J. Media Inform. Budidarma, vol. 6, no. 2, p. 746, 2022, doi: 10.30865/mib.v6i2.3554.

N. Agustina, D. H. Citra, W. Purnama, C. Nisa, and A. R. Kurnia, “Implementasi Algoritma Naive Bayes untuk Analisis Sentimen Ulasan Shopee pada Google Play Store,” MALCOM Indones. J. Mach. Learn. Comput. Sci., vol. 2, no. 1, pp. 47–54, 2022, doi: 10.57152/malcom.v2i1.195.

R. AL Anshari, S. Alam, and M. T. Hafid, “Komparasi Payment DIgital untuk Analisis Sentimen Berdasarkan Ulasan di Google Playstore Menggunakan Metode Support Vector Machine,” J. Ilm. Tek. dan Ilmu Komput., vol. 2, no. 3, pp. 118–128, 2023, doi: https://doi.org/10.55123/storage.v2i3.2337.

R. Apriani and D. Gustian, “Analisis Sentimen dengan Naïve Bayes Terhadap Komentar Aplikasi Tokopedia,” J. Rekayasa Teknol. Nusa Putra, vol. 6, no. 1, pp. 54–62, 2019, doi: https://doi.org/10.33395/jmp.v11i2.11640.

J. Winahyu and I. Suharjo, “Aplikasi Web Analisis Sentimen Dengan Algoritma Multinomial Naïve Bayes,” Kumpul. Artik. Mhs. Pendidik. Tek. Inform., vol. 10, no. 2, p. 206, 2021, doi: 10.23887/karmapati.v10i2.36609.

S. Styawati, N. Hendrastuty, and A. R. Isnain, “Analisis Sentimen Masyarakat Terhadap Program Kartu Prakerja Pada Twitter Dengan Metode Support Vector Machine,” J. Inform. J. Pengemb. IT, vol. 6, no. 3, pp. 150–155, 2021, doi: 10.30591/jpit.v6i3.2870.

N. Herlinawati, Y. Yuliani, S. Faizah, W. Gata, and S. Samudi, “Analisis Sentimen Zoom Cloud Meetings di Play Store Menggunakan Naïve Bayes dan Support Vector Machine,” CESS (Journal Comput. Eng. Syst. Sci., vol. 5, no. 2, p. 293, 2020, doi: 10.24114/cess.v5i2.18186.

M. K. Khoirul Insan, U. Hayati, and O. Nurdiawan, “Analisis Sentimen Aplikasi Brimo Pada Ulasan Pengguna Di Google Play Menggunakan Algoritma Naive Bayes,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 1, pp. 478–483, 2023, doi: 10.36040/jati.v7i1.6373.

A. Faisal, Y. Alkhalifi, A. Rifai, and W. Gata, “Analisis Sentimen Dewan Perwakilan Rakyat Dengan Algoritma Klasifikasi Berbasis Particle Swarm Optimization,” JOINTECS (Journal Inf. Technol. Comput. Sci., vol. 5, no. 2, p. 61, 2020, doi: 10.31328/jointecs.v5i2.1362.

I. R. Afandi, F. Noor Hasan, A. A. Rizki, N. Pratiwi, and Z. Halim, “Analisis Sentimen Opini Masyarakat Terkait Pelayanan Jasa Ekspedisi Anteraja Dengan Metode Naive Bayes,” J. Linguist. Komputasional, vol. 5, no. 2, pp. 63–70, 2022, doi: 10.26418/jlk.v6i1.

M. A. Permana, S. Widiastuti, and S. Saepudin, “Analisis Sentimen Pengguna Aplikasi Video Conference pada Ulasan Google Play Store Menggunakan Metode NBC (Naive Bayes Classifier),” Sainsbertek J. Ilm. Sains Teknol., vol. 2, no. 1, pp. 1–9, 2021, doi: 10.33479/sb.v2i1.145.

M. Syarifuddinn, “Analisis Sentimen Opini Publik Mengenai Covid-19 Pada Twitter Menggunakan Metode Naïve Bayes Dan Knn,” INTI Nusa Mandiri, vol. 15, no. 1, pp. 23–28, 2020, doi: 10.33480/inti.v15i1.1347.

B. Z. Ramadhan, R. I. Adam, and I. Maulana, “Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes,” J. Appl. Informatics Comput., vol. 6, no. 2, pp. 220–225, 2022, doi: 10.30871/jaic.v6i2.4725.

T. A. Sari, E. Sinduningrum, and F. Noor Hasan, “Analisis Sentimen Ulasan Pelanggan Pada Aplikasi Fore Coffee Menggunakan Metode Naïve Bayes,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 3, no. 6, pp. 773–779, 2023, doi: 10.30865/klik.v3i6.884.