Main Article Content

Abstract

This study explores public sentiment toward Indonesia’s new digital tax administration system, known as Coretax, by analyzing conversation among tax-savvy users in a WhatsApp Group. Public sentiment was analyzed by examining more than 53,000 messages using a lexicon-based approach to classify them into positive, negative or neutral categories. The findings reveal that negative sentiment dominates (39%), indicating frequent technical issues, procedural confusion, and access problems during Coretax’s early implementation phase in 2025. However, neutral (31.5%) and positive (29.5%) messages show that users also shared information and expressed appreciation, especially during successful interactions. Spikes in communication occurred during major events such as webinars and statutory tax filing deadlines. This study provides a novelty using real-time peer-to-peer digital conversations to capture how knowledgeable users experience tax digitalization in its earliest months. The findings suggest that user-oriented design, clearer guidance, and responsive communication are essential for improving user experience in digital tax reforms.

Keywords

Coretax Public Perceptions Sentiment Analysis Taxation System

Article Details

References

  1. Acquah, A. (2025). E-taxing maturity in developing economies: evidence from corporate tax payers in Ghana. Digital Policy, Regulation and Governance, 27(4), 466–485. https://doi.org/10.1108/DPRG-06-2024-0131
  2. Aisah, F. (2025, April 13). Coretax Bikin Wajib Pajak Pusing, Proyek Triliunan Rupiah Sarat Masalah Teknis. BeritaOne. https://beritaone.id/news/detail/12839/coretax-bikin-wajib-pajak-pusing-proyek-triliunan-rupiah-sarat-masalah-teknis?utm
  3. Alm, J. (2023). Tax compliance, technology, trust, and inequality in a post-pandemic world. EJournal of Tax Research, 21(2), 152–172.
  4. Alm, J., & Soled, J. (2017). W(h)ither the tax gap? Washington Law Review, 92(2). https://digitalcommons.law.uw.edu/wlr/vol92/iss2/2
  5. Ardhianto, R. A., Bawono, I. R., & Sudibyo, Y. A. (2022). The role of trust in the voluntary compliance of MSME taxpayers. Jurnal Reviu Akuntansi Dan Keuangan, 12(1), 75–87. https://doi.org/10.22219/jrak.v12i1.18501
  6. Arianty, F. (2023). Modernization of tax administration in djp online service in terms of efficiency principle. In Proceedings of the 6th International Conference on Vocational Education Applied Science and Technology (ICVEAST 2023) (pp. 772–782). Atlantis Press. https://doi.org/10.2991/978-2-38476-132-6_66
  7. Bassey, E., Mulligan, E., & Ojo, A. (2022). A conceptual framework for digital tax administration - A systematic review. Government Information Quarterly, 39(4), 101754. https://doi.org/10.1016/J.GIQ.2022.101754
  8. Chan, S., & Tjandra, T. (2020). elang · PyPI. Elang 0.1.1. https://pypi.org/project/elang/
  9. Chen, Y., Silva, E. A., & Reis, J. P. (2021). Measuring policy debate in a regrowing city by sentiment analysis using online media data: A case study of Leipzig 2030. Regional Science Policy & Practice, 13(3), 675–693. https://doi.org/10.1111/RSP3.12292
  10. Direktorat Jenderal Pajak. (2025). Coretax | Direktorat Jenderal Pajak. https://pajak.go.id/Coretax
  11. Hauptman, L., Žmuk, B., & Pavić, I. (2024). Tax compliance in Slovenia: An empirical assessment of tax knowledge and fairness perception. Journal of Risk and Financial Management 2024, Vol. 17, Page 89, 17(3), 89. https://doi.org/10.3390/JRFM17030089
  12. Kencono, D. S., Djunaedi, A., & Purbokusumo, Y. (2025). Exploring public sentiment toward regional e-government apps: A case study of Sapawarga and Jaki in Indonesia. Journal of Information Systems Engineering and Management, 10(15s), 285–298. https://doi.org/10.52783/jisem.v10i15s.2458
  13. Koto, F., & Rahmaningtyas, G. Y. (2017). Inset lexicon: Evaluation of a word list for Indonesian sentiment analysis in microblogs. 2017 International Conference on Asian Language Processing (IALP), 391–394. https://doi.org/10.1109/IALP.2017.8300625
  14. Mauleny, A. T., Sayekti, N. W., Rivani, E., Satya, V. E., Lisnawati, & Rongiyati, S. (2020). Optimalisasi Dan Penguatan Perpajakan Indonesia (C. M. Firdausy, Ed.). Yayasan Pustaka Obor Indonesia.
  15. Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018). Foundations of Machine Learning (2nd ed.). The MIT Press.
  16. Mpofu, F. Y. (2022a). Taxation of the digital economy and direct digital service taxes: Opportunities, challenges, and implications for African countries. Economies, 10(9), 219. https://doi.org/10.3390/economies10090219
  17. Mpofu, F. Y. (2022b). Taxing the digital economy through consumption taxes (VAT) in African countries: Possibilities, constraints and implications. International Journal of Financial Studies, 10(3), 65. https://doi.org/10.3390/ijfs10030065
  18. Nose, M. (2023). Exploring the adoption of selected digital technologies in tax administration. IMF Notes, 2023(008), 1. https://doi.org/10.5089/9798400258183.068
  19. Nyantakyi, G., Atta Sarpong, F., Asiedu, F., Adjei Bimpeh, D., Kwasi Anenyah Ntoso, J., Ofeibea Nunoo, L., nyantakyi, george, Atta sarpong, F., Kwasi Anenyah Ntoso, J., & Ofeibea Nunoo, Linda. (2024). Unearthing the mediating role of political affiliation in tax compliance determinants: New evidence from Ghana. Cogent Business & Management, 11(1), 2316886. https://doi.org/10.1080/23311975.2024.2316886
  20. OECD. (2023). Tax Administration 2023. OECD. https://doi.org/10.1787/900b6382-en
  21. Peraturan Presiden (Perpres) Nomor 40 Tahun 2018 Tentang Pembaruan Sistem Administrasi Perpajakan, Pub. L. No. 40 (2018).
  22. Puspapertiwi, E. R., & Adhi, I. S. (2025, February 18). Kata Pakar IT soal Penyebab Sistem Coretax Bermasalah dan Ganggu Perpajakan. Kompas.Com. https://www.kompas.com/tren/read/2025/02/18/120000765/kata-pakar-it-soal-penyebab-sistem-coretax-bermasalah-dan-ganggu-perpajakan?page=all
  23. Puspita, M. D., & Estherina, I. (2025, February 25). Sederet Masalah Coretax yang Sering Dikeluhkan Menurut Ditjen Pajak | tempo.co. Tempo.Co. https://www.tempo.co/ekonomi/sederet-masalah-coretax-yang-sering-dikeluhkan-menurut-ditjen-pajak--1211669
  24. Rachman, A. (2025, January 14). Keluhan Soal Coretax Terus Muncul: Sistem Tak Siap, Sosialisasi Kacau! CNBC Indonesia. https://www.cnbcindonesia.com/news/20250114071439-4-602923/keluhan-soal-coretax-terus-muncul-sistem-tak-siap-sosialisasi-kacau
  25. Rahayu, S. K., & Kusdianto, A. (2023). Challenges of Digital Tax Administration Transformation in Indonesia. https://doi.org/10.5772/intechopen.111458
  26. Russell, S. N., Rao-Graham, L., & McNaughton, M. (2024). Mining social media data to inform public health policies: A sentiment analysis case study. Revista Panamericana de Salud Pública, 48, e79. https://doi.org/10.26633/RPSP.2024.79
  27. Shelvi, & Rachmawati, T. (2025). Does public trust encourage voluntary tax compliance? A study of Indonesian taxpayers. Jurnal Ilmu Administrasi Media Pengembangan Ilmu Dan Praktek Administrasi, 22(1). https://doi.org/10.31113/jia.v22i1.1244
  28. Siwi, T. P. U., & Nawawi, Z. (2023). Building citizen satisfaction towards e-government services: A conceptual framework. Jurnal Manajemen Pelayanan Publik, 6(2), 253. https://doi.org/10.24198/jmpp.v6i2.46471
  29. Thu, H. D. T. (2024). Income tax compliance behavior of businesses: The case of Vietnam. Decision Science Letters, 13(1), 135–142. https://doi.org/10.5267/j.dsl.2023.11.002
  30. Twesige, D., Rutungwa, E., Faustin, G., Misago, I. K., & Mutarinda, S. (2024). Gender and the tax compliance puzzle: does gender influence taxpayers’ behaviour towards tax compliance? Evidence from Rwanda. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2316887
  31. van Atteveldt, W., van der Velden, M. A. C. G., & Boukes, M. (2021). The validity of sentiment analysis: Comparing manual annotation, crowd-coding, dictionary approaches, and machine learning algorithms. Communication Methods and Measures, 15(2), 121–140. https://doi.org/10.1080/19312458.2020.1869198
  32. Wahid, D. H., & SN, A. (2016). Peringkasan sentimen esktraktif di twitter menggunakan hybrid tf-idf dan cosine similarity. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 10(2), 207. https://doi.org/10.22146/ijccs.16625
  33. Wildan, M. (2024, May 15). Sistem Informasi DJP Sudah Jadul, Pengembangan Coretax Tak Terelakkan. DDTC News. https://news.ddtc.co.id/berita/nasional/1802622/sistem-informasi-djp-sudah-jadul-pengembangan-coretax-tak-terelakkan
  34. Yaqub, U., Chun, S. A., Atluri, V., & Vaidya, J. (2021). Analyzing social media messages of public sector organizations utilizing sentiment analysis and topic modeling. Information Polity, 26(4), 375–390. https://doi.org/10.3233/IP-210321