Analisis Sentimen Aplikasi Tokocrypto Berdasarkan Ulasan Pada Google Play Store Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.30865/klik.v4i4.1707Keywords:
Tokocrypto; Naïve Bayes; Exchange Cryptocurrency; Reviews; DataAbstract
The advancement of increasingly sophisticated technology has brought numerous changes and conveniences for humans in all aspects, including the financial sector. Cryptocurrency has emerged as an innovation in the financial world. A cryptocurrency exchange is an electronic platform that enables sellers and buyers to conduct cryptocurrency trading transactions through a website or mobile application. Currently, many cryptocurrency exchange applications suffer from poor service, unreliable security, lengthy withdrawal processes, high administrative fees, and other issues. As a result, many people in Indonesia rely on reviews on the Google Play Store to check user feedback before deciding to use these cryptocurrency exchange applications. Many Indonesians seek information on cryptocurrency exchange applications that provide the best services for buying and selling cryptocurrency. One such application, according to reviews on the Google Play Store, is Tokocrypto. This study aims to understand the sentiment towards user reviews of the Tokocrypto application using the Naïve Bayes algorithm for data classification. The data obtained consists of 2,000 reviews from the Google Play Store in February 2024, collected using Google Colaboratory. The research stages include data scraping using web scraping techniques, data labeling, preprocessing, TF-IDF weighting, implementing the Naïve Bayes algorithm, and evaluation. The cleaned data resulted in 1,000 reviews, with 396 positive sentiments and 604 negative sentiments. The results of sentiment analysis research using the Naïve Bayes algorithm method show 74.22% for accuracy, 63.25% for precision, and 81.40% for recall.
Downloads
References
S. Sajidin, “LEGALITAS PENGGUNAAN CRYPTOCURRENCY SEBAGAI ALAT PEMBAYARAN DI INDONESIA,” Arena Hukum, vol. 14, no. 2, pp. 245–267, Aug. 2021, doi: 10.21776/ub.arenahukum.2021.01402.3.
Rizaldi Azhar, Adi Surahman, and Christina Juliane, “Analisis Sentimen Terhadap Cryptocurrency Berbasis Python TextBlob Menggunakan Algoritma Naïve Bayes,” Jurnal Sains Komputer & Informatika (J-SAKTI), vol. 6, no. 1, pp. 267–281, Mar. 2022, Accessed: Feb. 24, 2024. [Online]. Available: https://tunasbangsa.ac.id/ejurnal/index.php/jsakti
A. Sentimen et al., “Sentiment Analysis of Cryptocurrency Exchange Application on Twitter Using Naïve Bayes Classifier Method,” Jurnal Informatika dan Teknologi Informasi, vol. 20, no. 1, pp. 15–30, 2023, doi: 10.31515/telematika.v20i1.9044.
P. Aditiya, U. Enri, and I. Maulana, “Analisis Sentimen Ulasan Pengguna Aplikasi Myim3 Pada Situs Google Play Menggunakan Support Vector Machine,” JURIKOM (Jurnal Riset Komputer), vol. 9, no. 4, p. 1020, Aug. 2022, doi: 10.30865/jurikom.v9i4.4673.
Dwi Normawati and Surya Allit 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, Sep. 2021, Accessed: Feb. 24, 2024. [Online]. Available: https://tunasbangsa.ac.id/ejurnal/index.php/jsakti
L. Ardiani, H. Sujaini, and T. Tursina, “Implementasi Sentiment Analysis Tanggapan Masyarakat Terhadap Pembangunan di Kota Pontianak,” Jurnal Sistem dan Teknologi Informasi (Justin), vol. 8, no. 2, p. 183, Apr. 2020, doi: 10.26418/justin.v8i2.36776.
A. Nurian, M. S. Ma’arif, I. N. Amalia, and C. Rozikin, “ANALISIS SENTIMEN PENGGUNA APLIKASI SHOPEE PADA SITUS GOOGLE PLAY MENGGUNAKAN NAIVE BAYES CLASSIFIER,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 12, no. 1, Jan. 2024, doi: 10.23960/jitet.v12i1.3631.
F. Zaini, J. W. Sari, and F. N. Hasan, “ANALYSIS OF PUBLIC SENTIMENT RELATED TO THE FAILURE OF INDONESIA TO HOST U-20 USING MULTINOMIAL NAÏVE BAYES CLASSIFIER,” Jurnal Teknik Informatika (Jutif), vol. 4, no. 6, pp. 1409–1418, Dec. 2023, doi: 10.52436/1.jutif.2023.4.6.1209.
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
Caesar Rio Anggina Toruan, Novanto Yudistra, and Rizal Setya Perdana, “Analisis Sentimen Tokocrypto pada Twitter menggunakan Metode Long Short-Term Memory,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer , vol. 7, no. 2, pp. 719–726, Feb. 2023, Accessed: Feb. 23, 2024. [Online]. Available: http://j-ptiik.ub.ac.id/
D. Rudini, D. Gita Purnama, and A. Achmad Khan, “PENGGUNAAN TEKNIK WEB SCRAPING DALAM APLIKASI PENGAMBILAN DATA DARI GOOGLE MAPS UNTUK MENUNJANG DIGITAL MARKETING,” Lentera: Multidisciplinary Studies, vol. 2, no. 1, pp. 10–19, 2023, [Online]. Available: https://lentera.publikasiku.id/index.php
Ni Putu Gita Naraswati, Delvira Cindy Rosmilda, Dinda Desinta, Fadhilatul Khairi, Riska Damaiyanti, and Rani Nooraeni, “Analisis Sentimen Publik dari Twitter Tentang Kebijakan Penanganan Covid-19 di Indonesia dengan Naive Bayes Classification,” SISTEMASI: Jurnal Sistem Informasi, vol. 10, no. 1, pp. 222–238, Jan. 2021, Accessed: Feb. 24, 2024. [Online]. Available: http://sistemasi.ftik.unisi.ac.id/
H. Parasian Doloksaribu and Y. T. Samuel, “KOMPARASI ALGORITMA DATA MINING UNTUK ANALISIS SENTIMEN APLIKASI PEDULILINDUNGI,” JURNAL TEKNOLOGI INFORMASI(JTI) Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika, vol. 16, no. 1, 2022, doi: 10.47111/JTI.
A. Rhamadanti, A. Rifa’i, F. Dikananda, and K. Anam, “ANALISIS SENTIMEN PADA ULASAN ACCESS BY KERETA API INDONESIA DENGAN K-NEAREST NEIGHBOR,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 12, no. 1, pp. 2830–7062, 2024, doi: 10.23960/jitet.v12i1.3691.
E. Yuniar, D. S. Utsalinah, and D. Wahyuningsih, “Implementasi Scrapping Data Untuk Sentiment Analysis Pengguna Dompet Digital dengan Menggunakan Algoritma Machine Learning,” Jurnal Janitra Informatika dan Sistem Informasi, vol. 2, no. 1, pp. 35–42, Apr. 2022, doi: 10.25008/janitra.v2i1.145.
A. Witanti, B. Yogyakarta Jl Raya Wates-Jogjakarta, K. Sedayu, K. Bantul, and D. Istimewa Yogyakartalamat, “ANALISIS SENTIMEN MASYARAKAT TERHADAP VAKSINASI COVID-19 PADA MEDIA SOSIAL TWITTER MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM),” Jurnal Sistem Informasi dan Informatika (Simika) P-ISSN, vol. 5, pp. 2622–6901, 2022.
Yuyun, Nurul Hidayah, and Supriadi Sahibu, “Algoritma Multinomial Naïve Bayes Untuk Klasifikasi Sentimen Pemerintah Terhadap Penanganan Covid-19 Menggunakan Data Twitter,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 4, pp. 820–826, Aug. 2021, doi: 10.29207/resti.v5i4.3146.
Dicki Nugraha and Dudih Gustian, “Analisis Sentimen Penggunaan Aplikasi Transportasi Online Pada Ulasan Google Play Store dengan Metode Naive Bayes Classifier,” KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen), vol. 5, no. 1, pp. 326–335, Jan. 2024, Accessed: Feb. 24, 2024. [Online]. Available: https://tunasbangsa.ac.id/pkm/index.php/kesatria/index
P. Ayu, W. Purnama, and T. A. Putra, “Klasifikasi Penjualan Produk Menggunakan Algoritma Naive Bayes pada Konter HP Bayu Cell,” Remik: Riset dan E-Jurnal Manajemen Informatika Komputer, vol. 8, no. 1, pp. 286–292, 2024, doi: 10.33395/remik.v8i1.13207.
M. Afriansyah, J. Saputra, V. Yoga Pudya Ardhana, Y. Sa, and U. Qamarul Huda Badaruddin, “ALGORITMA NAIVE BAYES YANG EFISIEN UNTUK KLASIFIKASI BUAH PISANG RAJA BERDASARKAN FITUR WARNA,” Hal. 236 Journal of Information Systems Management and Digital Business (JISMDB), vol. 1, no. 2, pp. 236–248, 2024, Accessed: Feb. 24, 2024. [Online]. Available: https://journal.ppmi.web.id/index.php/jismdb
D. A. Prawinata, U. Pembangunan, N. Veteran, and J. Timur, “Analisis Sentimen Kendaraan Listrik Pada Twitter Menggunakan Metode Long Short Term Memory Ani Dijah Rahajoe I Gede Susrama Mas Diyasa,” vol. 2, no. 1, pp. 300–313, 2024, doi: 10.59841/saber.v2i1.857.
M. N. Hidayat and R. Pramudita, “Analisis Sentimen Terhadap Pembelajaran Secara Daring Pasca Pandemi Covid-19 Menggunakan Metode IndoBERT,” Information Management for Educators and Professionals, vol. 8, no. 2, pp. 161–170, 2023, Accessed: Feb. 24, 2024. [Online]. Available: https://ejournal-binainsani.ac.id/index.php/IMBI
S. Riyadi, “Analisis Sentimen Opini Masyarakat Terhadap Stadion Jakarta Internasional Stadium (JIS) Pada Twitter Dengan Perbandingan Metode Naive Bayes Dan Support Vector Machine,” Jurnal Sains dan Teknologi, vol. 5, no. 3, pp. 801–809, 2024, doi: 10.55338/saintek.v5i1.2790.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Analisis Sentimen Aplikasi Tokocrypto Berdasarkan Ulasan Pada Google Play Store Menggunakan Metode Naïve Bayes
ARTICLE HISTORY
How to Cite
Issue
Section
Copyright (c) 2024 Rizki Adi Saputra, Dion Parisda Ray, Faldy Irwiensyah
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
