APPLICATION OF THE BERT MODEL IN MEASURING USER PERCEPTION OF THE MAGIC INVESTMENT APPLICATION ON THE GOOGLE PLAY STORE

Authors

  • Tabina Fasya Benedicta
  • Ade Setiawan
  • Luthfi Indriyani
  • Astrid Noviriandini
  • Sandra Dewi Saraswati

Keywords:

Web-Based Point of Sale System, Software Architecture, CV Digital Printing

Abstract

Investment is one of the most effective ways to achieve long-term financial gains. Nowadays, numerous digital platforms offer investment services, including the Ajaib application. The growing public interest in investing has been driven by influencers and online advertisements, yet it has also led to the rise of fraudulent schemes and fake investment platforms. Therefore, evaluating user satisfaction through sentiment analysis of application reviews becomes essential. This study aims to analyze user sentiments toward the Ajaib investment application based on reviews collected from the Google Play Store. The dataset consists of Indonesian-language reviews from the period 2019–2024, processed using Google Colab and the BERT (Bidirectional Encoder Representations from Transformers) algorithm. The classification results yielded 1,393 reviews, comprising 696 positive and 697 negative sentiments, indicating that negative opinions were slightly more dominant. The model achieved an accuracy of 85%, F1-score of 85%, recall of 85%, and precision of 87%, demonstrating that the BERT algorithm performs effectively in sentiment analysis for investment-related applications.

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References

Akhmad, E. P. A. (2023). Analisis Sentimen Ulasan Aplikasi DLU Ferry Pada Google Play Store Menggunakan Bidirectional Encoder Representations from Transformers. Jurnal Aplikasi Pelayaran Dan Kepelabuhanan, 13(2), 104–112. https://doi.org/10.30649/japk.v13i2.94 Atmaja, R. M. R. W. P. K., & Yustanti, W. (2021).

Analisis Sentimen Customer Review Aplikasi RuangGuru dengan Metode BERT (Bidirectional EncoderRepresentations from Transformers). JEISBI (Journal of Emerging Information Systems and Business Intelligence), 02(3), 55–62.

Bey, T., & Ari, I. K. (2023). Implementasi BERT pada Analisis Sentimen Ulasan Destinasi Wisata Bali. Jurnal Elektronik Ilmu Komputer Udayana, 12(2), 409–420.

Braja, A. S. P., & Kodar, A. (2023). Implementasi Fine-Tuning BERT untuk Analisis Sentimen terhadap Review Aplikasi PUBG Mobile di Google Play Store. J I M P – Jurnal Informatika Merdeka Pasuruan, 7(3), 120. https://doi.org/10.51213/jimp.v7i3.779

Cahyani, T. P., & Qoyyimi, D. T. (2023). INTISARI ALGORITMA BIDIRECTIONAL ENCODER REPRESENTATIONS FROM TRANSFORMERS ( BERT ) PADA ANALISIS SENTIMEN Oleh TARISA PUTRI CAHYANI ABSTRACT BIDIRECTIONAL ENCODER REPRESENTATIONS FROM TRANSFORMERS (BERT ) ALGORITHM ON SENTIMENT ANALYSIS By TARISA PUTRI .

Gunawan, B., Pratiwi, H. S., & Pratama, E. E. (2018). Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 4(2), 113. https://doi.org/10.26418/jp.v4i2.27526

Guntara, R. G. (2023). Visualisasi Data Laporan Penjualan Toko Online Melalui Pendekatan Data Science Menggunakan Google Colab. Jurnal Ilmiah Multidisiplin, 2(6), 2091–2100.

Husin, N. (2023). Komparasi Algorit Forest, Naïve Bayes, dan Bert Untuk Multi- Class Classification Pada Artikel Cable News Network (CNN). Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi Dan Sistem Komputer, 7(1), 75–84. https://doi.org/10.55886/infokom.v7i1.608

Kurniawan, B., Ari Aldino, A., & Rahman Isnain, A. (2022). Sentimen Analisis Terhadap Kebijakan Penyelenggara Sistem Elektronik (Pse) Menggunakan Algoritma Bidirectional Encoder Representations From Transformers (Bert). Jurnal Teknologi Dan Sistem Informasi, 3(4), 98–106. http://jim.teknokrat.ac.id/index.php/JTSI

Kusnadi, R., Yusuf, Y., Andriantony, A., Ardian Yaputra, R., & Caintan, M. (2021). Analisis Sentimen Terhadap Game Genshin Impact Menggunakan Bert. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 6(2), 122–129. https://doi.org/10.36341/rabit.v6i2.1765

Mahawardana, P. P. O., Imawati, I. A. P. F., & Dika, I. W. (2022). Analisis Sentimen Berdasarkan Opini dari Media Sosial Twitter terhadap “Figure Pemimpin” Menggunakan Python. Jurnal Manajemen Dan Teknologi Informasi, 12(2), 50–56. https://ojs.mahadewa.ac.id/index.php/jmti/artic le/view/2111

Muflih, H. Z., Abdillah, A. R., & Hasan, F. N. (2023). Analisis Sentimen Ulasan Pengguna Aplikasi Ajaib Menggunakan Metode Naïve Bayes. KLIK: Kajian Ilmiah Informatika Dan Komputer, 4(3), 1613–1621. https://doi.org/10.30865/klik.v4i3.1303 Pradipta, D., Kusrini, K., & Fatta, H. Al. (2023).

Sentiment Analysis Comments Covid-19 Variant Omicron on Social Media Instagram with Bidirectional Encoder from Transformers (BERT). JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem Dan Komputer, 3(1), 51. https://doi.org/10.32503/jtecs.v3i1.3219

Rizaldi, S. A. R., Alam, S., & Kurniawan, I. (2023). Analisis Sentimen Pengguna Aplikasi JMO (Jamsostek Mobile) Pada Google Play Store Menggunakan Metode Naive Bayes. STORAGE: Jurnal Ilmiah Teknik Dan Ilmu Komputer, 2(3), 109–117. https://doi.org/10.55123/storage.v2i3.2334

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Published

2025-11-05

How to Cite

Tabina Fasya Benedicta, Ade Setiawan, Luthfi Indriyani, Astrid Noviriandini, & Sandra Dewi Saraswati. (2025). APPLICATION OF THE BERT MODEL IN MEASURING USER PERCEPTION OF THE MAGIC INVESTMENT APPLICATION ON THE GOOGLE PLAY STORE. Akrab Juara : Jurnal Ilmu-Ilmu Sosial, 10(4), 1164–1177. Retrieved from https://akrabjuara.com/index.php/akrabjuara/article/view/2585

Issue

Vol. 10 No. 4 (2025): November

Section

Articles

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