A Twitter Sentimen Analysis on Islamic Banking Using Drone Emprit Academic (DEA): Evidence from Indonesia
Authors: Nadia Nurul Izza  , Mia Sari  , Mughnii Kahila  , Solahuddin Al-ayubi  
Published: October 2023

ABSTRACT
The research aimed to identify and collect issues discussed regarding Islamic banking from user activity, sentimen, and content on Twitter. This study used a qualitative approach by collecting data on 145,475 conversations from Twitter using the Twitter Crawling technique with the Drone Emprit Academy (DEA) engine from 28 July 2020 – 10 March 2023 in Indonesia. Text data mining is used with the help of the DEA system by analyzing sentimen, Social Network Analysis (SNA), and other Twitter data analysis. The results showed that the highest number of tweets related to Islamic banking came from the number of tweets which were dominated by millennials and millennials with positive sentimens of 66%, then negative sentimens of 28% and neutral sentimens of 5%. From these results, both positive, negative and neutral sentimens are a challenge for various stakeholders in the field, including academics, government and others, in a more massive manner to explain and provide a more solid and stronger understanding of Islamic finance, especially Islamic banking.Keywords: Islamic Banking; Sentimen Analysis; Twitter; Academic Emprit Drone
ABSTRAKPenelitian bertujuan untuk mengindetifikasi dan mengumpulkan isu yang dibahas terkait perbankan syariah dari aktivitas pengguna, sentimen, dan konten di Twitter. Metode ini menggunakan pendekatan kualitatif dengan mengumpulkan data 145.475 percakapan dari Twitter menggunakan teknik Twitter Crawling dengan mesin Drone Emprit Academy (DEA) dari tanggal 28 Juli 2020 – 10 Maret 2023 di Indonesia. Text data mining digunakan dengan bantuan sistem DEA dengan menganalisis sentimen, Social Network Analysis (SNA), dan analisis data Twitter lainnya. Hasil penelitian menunjukkan jumlah tweet tertinggi terkait perbankan syariah berasal dari jumlah tweet yang didominasi oleh kaum millennials dan zillenial dengan sentimen positif sebesar 66%, kemudian sentimen negatif 28% dan sentimen netral sebesar 5%. Dari hasil tersebut, baik sentimen positif, negative, maupun netral menjadi tantangan bagi berbagai pemangku kepentingan di lapangan, termasuk akademisi, pemerintah, dan lainnya, secara lebih massif untuk menjelaskan dan memberikan pemahaman yang lebih kokoh dan kuat tentang keuangan syariah khususnya perbankan syariah. Kata Kunci: Perbankan Syariah, Analisis Sentimen, Twitter, Drone Emprit Akademik
 
REFERENCES
Ahmad, A., Sohail, A., & Hussain, A. (2021). Emergence of financial technology in Islamic banking industry and its influence on bank performance in covid-19 scenario: A case of developing economy. Gomal University Journal of Research, 37(1), 97-109.
Alotaibi,  M. S. (2013). The Impact of Twitter on Saudi banking sectors in the presence of social media: An evaluative study. International Research: Journal of Library & Information Science, 3(4), 618–630.
Anwar, S. A. (2019). Revolusi industri 4.0 Islam dalam merespon tantangan teknologi digitalisasi. At Tuhfah: Jurnal Studi KeIslaman, 8(2), 16-28. doi:10.36840/jurnalstudikeislaman.v8i2.203
Anwar, S., Marlius, D., & Badri, J. (2022). Sharia bank in the middle of the disruptive era. Al-Masraf: Jurnal Lembaga Keuangan dan Perbankan, 7(2), 139-151. doi:10.15548/al-masraf.v7i2.416
Arianto, B. (2021). Media Sosial sebagai Saluran Aspirasi Kewargaan: Studi Pembahasan RUU Cipta Kerja. Jurnal PIKMA : Publikasi Ilmu Komunikasi Media dan Cinema, 3(2), 107–127. doi:10.24076/pikma.v3i2.469
Bank Indonesia. (2021). Laporan Perekonomian Indonesia 2021. Retrieved from https://www.bi.go.id/id/publikasi/laporan/Pages/LPI_2021.aspx
Bappenas. (2018). Masterplan ekonomi syariah Indonesia 2019-2024. Retrieved from https://kneks.go.id/storage/upload/1573459280-Masterplan%20Eksyar_Preview.pdf
Cahyono, E. F., Rani, L. N., & Kassim, S. (2020). Perceptions of the 7P marketing mix of Islamic banks in Indonesia: What Do Twitter Users Say About It? International Journal of Innovation, Creativity and Change, 11(11), 300–319.
Dang-Xuan, L., Stieglitz, S., Wladarsch, J., & Neuberger, C. (2017). An investigation of influentials and the role of sentimen in political communication on Twitter during election periods. Information, Communication and Society, 16(5), 1-31. doi:10.1080/1369118X.2013.783608
Fahmi, D. Y., Hartoyo, & Zulbainarni, N. (2021). Mining Social Media (Twitter) Data for Corporate Image Analysis: A Case Study in the Indonesian Mining Industry. Journal of Physics: Conference Series, 1811, 1-10. doi:10.1088/1742-6596/1811/1/012107
Fahmi, I. (2016). Drone Emprit: Software for media monitoring and analytics. Retrieved from https://pers.droneemprit.id/how-to-cite-drone-emprit/
Fahmi, I. (2018). Drone Emprit Academic: Software for social media monitoring and analytics. Retrieved from Available at http://dea.uii.ac.id.
Fakhrunnas, F., & Anto, M. B. H. (2023). Assessing the Islamic banking contribution to financial stability in Indonesia : A non-linear approach. Banks and Banks System, 18(1), 150-162. doi:10.21511/bbs.18(1).2023.13
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432-448). London: Routledge.
Haidar, A., As-Salafiyah, A., & Herindar, E. (2022). Sentimen analysis of digital sharia banking. Ekonomi Islam Indonesia, 4(1). doi:10.58968/eii.v4i1.72
Kemp, S. (2022). Digital 2022 global overview report. Retrieved from https://datareportal.com/reports/digital-2022-global-overview-report
Izza, N. N. (2022). Scientometric analysis of Islamic bank in Indonesia. Faraid & Wealth Management, 2(1). doi:10.58968/fwm.v2i1.161
Jackson, S. J., Bailey, M., & Welles, B. F. (2018). #GirlsLikeUs: Trans advocacy and community building online. New Media and Society, 20(5), 1868–1888. doi:10.1177/1461444817709276
Liang, F., & Lu, S. (2023). The dynamics of event-based political influencers on Twitter: A longitudinal analysis of influential accounts during Chinese political events. Social Media+ Society, 9(2), doi:20563051231177946.
Liu, B. (2015). Sentimen analysis: Mining opinions, sentimens, and emotions. Cambridge: The Cambridge University Press.
McCombs, M., & Valenzuela, S. (2020). Setting the agenda: Mass media and public opinion (3rd edition). New York: John Wiley & Sons.
Miftahuddin, A., Perdana, Y., & Sandjaya, T. (2023). Persepsi masyarakat terhadap tren perkembangan industri halal di media sosial: Analisis respons di Indonesia. Responsive: Jurnal Pemikiran dan Penelitian Bidang Administrasi, Sosial, Humaniora, dan Kebijakan Publik, 5(4), 233–238. doi: 10.24198/responsive.v5i4.44555
Mosioi, H. B. S. O., & Mailoa, E. (2021). Analisa sentimen publik terkait Otonomi Khusus (OTSUS) di Papua dengan pendekatan sains data. Prosiding Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK), 5(1), 153–156.
Mude, G., & Undale, S. (2023). Social media usage: A comparison between generation Y and generation Z I India. International Journal of E-Business Research, 19(1), 1–20. doi:10.4018/ijebr.317889
OJK. (2020). Indonesia Islamic banking development roadmap. Retrieved from https://ojk.go.id/en/kanal/syariah/berita-dan-kegiatan/publikasi/Pages/Indonesia-Islamic-Banking-Development-Roadmap.aspx
OJK. (2020). Strategi nasional literasi keuangan Indonesia 2021-2025. Retrieved from https://www.ojk.go.id/id/berita-dan-kegiatan/publikasi/Documents/Pages/Strategi-Nasional-Literasi-Keuangan-Indonesia-2021-2025/Strategi%20Nasional%20Literasi%20Keuangan%20Indonesia%202021-2025.pdf
OJK. (2021). Laporan perkembangan keuangan syariah Indonesia 2020. Retrieved from https://ojk.go.id/id/kanal/syariah/data-dan-statistik/laporan-perkembangan-keuangan-syariah-indonesia/Pages/Laporan-Perkembangan-Keuangan-Syariah-Indonesia-2020.aspx
OJK. (2021). Statistik perbankan syariah. Retrieved from https://www.ojk.go.id/id/kanal/perbankan/data-dan-statistik/statistik-perbankan-syariah/Pages/Statistik-Perbankan-Syariah.aspx
OJK. (2022). Siaran pers: Survei nasional literasi dan inklusi keuangan tahun 2022. Retrieved from https://www.ojk.go.id/id/berita-dan-kegiatan/siaran-pers/Pages/Survei-Nasional-Literasi-dan-Inklusi-Keuangan-Tahun-2022.aspx
OJK. (2023). Peningkatan Literasi dan Inklusi Keuangan di Sektor Jasa Keuangan Bagi Konsumen dan Masyarakat. Retrieved from https://www.ojk.go.id/ojk-institute/id/capacitybuilding/upcoming/1340/memperkuat-literasi-dan-inklusi-keuangan-syariah
Rahmanti, A. R., Chien, C. H., Nursetyo, A. A., Husnayain, A., Wiratama, B. S., Fuad, A., Yang, H. C., & Li, Y. C. J. (2022). Social media sentimen analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout. Computer Methods and Programs in Biomedicine, 221. doi:10.1016/j.cmpb.2022.106838
Rahmat, F., & Rantisi, A. A. (2021). Islamic banking on Twitter: An analysis of users and networks. Journal of Islamic Marketing, 12(2), 276-293. doi:10.1108/JIMA-11-2020-0388.
Rahmayati, R. (2021). Competition strategy in the islamic banking industry: An empirical review. International Journal of Business, Economics, aAnd Social Development, 2(2), 65-71.
Rossana, A., & Firmansyah, E. A. (2019). Analisis Rasch pada atribut perbankan syariah: Studi pada generasi milenial. Jurnal Ilmiah Ekonomi Islam, 5(3), 145-156. doi:10.29040/jiei.v5i3.530
Rusydiana, A. S., & As-salafiyah, A. (2022). Shariah Fintech : An Analysis of Twitter Sentimen. Ekonomi Islam Indonesia, 4(2). doi:10.58968/eii.v4i2.98
Scott, J. (2012). What is Social Network Analysis?. London: Bloomsbury Academic
Septiani, E., Mulyadi, M., & Serip, S. (2021). Analisis kepercayaan generasi milenial terhadap lembaga keuangan syariah. Distribusi: Journal of Management and Business, 9(2), 147–160. doi:10.29303/distribusi.v9i2.163
Sotudeh, H., Saber, Z., Aloni, F. G., Mirzabeigi, M., & Khunjush, F. (2022). A longitudinal study of the evolution of opinions about open access and its main features: A twitter sentiment analysis. Scientometrics, 127(10), 5587-5611. doi:10.1007/s11192-022-04502-7
Syafrida, I., Aminah, A., & Awaludin, T. (2020). Keputusan penggunaan jasa perbankan syariah: Perspektif nasabah milenial. BISNIS : Jurnal Bisnis dan Manajemen Islam, 8(1), 49. doi:10.21043/bisnis.v8i1.6691
Zhang, L., Wang, S., & Liu, B. (2018). Deep learning for sentimen analysis: A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(4), 1–25. doi:10.1002/widm.1253