Sentiment Analysis of the Tiktok Application from Reviews on Google Playstore Using the Naïve Bayes Method
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Abstract
In this research, we use reviews from the Google Play Store platform to conduct sentiment analysis on the TikTok application. Reviews can be categorized into positive, negative, or neutral sentiment groups using a Naïve Bayes approach. The distribution of user sentiment towards TikTok is displayed in the sentiment analysis results. Exposing model performance allows you to observe the level of understanding, accuracy, and precision of emotion classification. Our findings provide marketers and app developers with in-depth information about how users view TikTok. The accuracy level, precision level, and recall level of the Naive Bayes algorithm used for sentiment analysis for evaluating users of the TikTok application on the Google Play Store are 83.66%, 82.97%, and 91.97%, respectively. From the accuracy figures, it is clear that the Naive Bayes method provides reliable results so it is suitable for use in data categorization.
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References
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[3] S. atik Hikmawati and L. Farida, “Pemanfaatan Media Tik Tok Sebagai Media Dakwah Bagi Dosen Iai Sunan Kalijogo Malang,” Al-Ittishol : Jurnal Komunikasi dan Penyiaran Islam, vol. 2, no. 1, pp. 1–11, 2021.
[4] B. G. Parameswara, L. N. Liyah, N. Sania, and A. Ibrahim, “Pemanfaatan Aplikasi TIK-TOK di Masa Pandemi Covid-19,” Cebong Journal, vol. 1, no. 1, pp. 10–14, 2021, doi: 10.35335/cebong.v1i1.4.
[5] R. T. Aldisa and P. Maulana, “Analisis Sentimen Opini Masyarakat Terhadap Vaksinasi Booster COVID-19 Dengan Perbandingan Metode Naive Bayes, Decision Tree dan SVM,” Building of Informatics, Technology and Science (BITS), vol. 4, no. 1, pp. 106–109, 2022, doi: 10.47065/bits.v4i1.1581.
[6] E. Laia and M. Yamin, “Penerapan Algoritma Naïve Bayes dalam Menganalisis Sentimen pada Review Pengguna E-Commerce,” Media Online), vol. 4, no. 1, pp. 305–316, 2023, doi: 10.30865/klik.v4i1.1186.
[7] S. A. R. Rizaldi, S. Alam, and I. Kurniawan, “Analisis Sentimen Pengguna Aplikasi JMO (Jamsostek Mobile) Pada Google Play Store Menggunakan Metode Naive Bayes,” STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer, vol. 2, no. 3, pp. 109–117, 2023, doi: 10.55123/storage.v2i3.2334.
[8] Gilbert, Syariful Alam, and M. Imam Sulistyo, “Analisis Sentimen Berdasarkan Ulasan Pengguna Aplikasi Mypertamina Pada Google Playstore Menggunakan Metode Naïve Bayes,” STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer, vol. 2, no. 3, pp. 100–108, 2023, doi: 10.55123/storage.v2i3.2333.
[9] N. Q. Rizkina and F. N. Hasan, “Analisis Sentimen Komentar Netizen Terhadap Pembubaran Konser NCT 127 Menggunakan Metode Naive Bayes,” Journal of Information System Research, vol. 4, no. 4, pp. 1136–1144, 2023, doi: 10.47065/josh.v4i4.3803.
[10] Ernianti Hasibuan and Elmo Allistair Heriyanto, “Analisis Sentimen Pada Ulasan Aplikasi Amazon Shopping Di Google Play Store Menggunakan Naive Bayes Classifier,” Jurnal Teknik dan Science, vol. 1, no. 3, pp. 13–24, 2022, doi: 10.56127/jts.v1i3.434.
[11] M. Yunus, M. Husni, and M. M. Mufadhdhal, “Klasifikasi Sentimen Terhadap Badan Penyelenggara Jaminan Sosial (BPJS) Pada Media Sosial Twitter Menggunakan Naive Bayes,” Smatika Jurnal, vol. 11, no. 02, pp. 81–91, 2021, doi: 10.32664/smatika.v11i02.577.
[12] 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.
[13] A. T. Susilawati, “Analisis Sentimen Publik Pada Twitter Terhadap Boikot Produk Israel Menggunakan Metode Naïve Bayes,” vol. 2, no. 1, 2024.
[14] A. Harun and D. Putri Ananda, “Analisa Sentimen Opini Publik Tentang Vaksinasi Covid-19 di Indonesia Menggunakan Naïve bayes dan Decission Tree,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 1, no. 1, pp. 58–64, 2021, doi: 10.57152/malcom.v1i1.63.
[15] W. Wahyuni, “Analisis Sentimen terhadap Opini Feminisme Menggunakan Metode Naive Bayes,” Jurnal Informatika Ekonomi Bisnis, vol. 4, pp. 148–153, 2022, doi: 10.37034/infeb.v4i4.162.
[16] Merinda Lestandy, Abdurrahim Abdurrahim, and Lailis Syafa’ah, “Analisis Sentimen Tweet Vaksin COVID-19 Menggunakan Recurrent Neural Network dan Naïve Bayes,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 4, pp. 802–808, 2021, doi: 10.29207/resti.v5i4.3308.
[17] J. Florensius Sianipar, Y. R. Ramadhan, and I. Jaelani, “Analisis Sentimen Pembangunan Kereta Cepat Jakarta-Bandung di Media Sosial Twitter Menggunakan Metode Naive Bayes,” Media Online), vol. 4, no. 1, pp. 360–367, 2023, doi: 10.30865/klik.v4i1.1033.
[18] D. Oktavia, Y. R. Ramadahan, and M. Minarto, “Analisis Sentimen Terhadap Penerapan Sistem E-Tilang Pada Media Sosial Twitter Menggunakan Algoritma Support Vector Machine (SVM),” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 4, no. 1, pp. 407–417, 2023, doi: 10.30865/klik.v4i1.1040.
[19] A. Nurian, “Analisis Sentimen Ulasan Pengguna Aplikasi Google Play Menggunakan Naïve Bayes,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 11, no. 3s1, pp. 1613–1621, 2023, doi: 10.23960/jitet.v11i3s1.3348.
[20] K. Anwar, “Analisa sentimen Pengguna Instagram Di Indonesia Pada Review Smartphone Menggunakan Naive Bayes,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 2, no. 4, pp. 148–155, 2022, doi: 10.30865/klik.v2i4.315.