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Abstract

This study uses a quantitative approach to analyze the factors that influence the use of QRIS (Quick Response Code Indonesian Standard) in the North Sumatra region. The model used is the Technology Acceptance Model (TAM), which evaluates the influence of Perceived Ease of Use and Perceived Usefulness on Attitude Toward Using and Behavioral Intention to Use QRIS. Data was collected through surveys and analyzed using path analysis to test the relationship between variables. The results showed that Perceived Ease of Use affects Perceived Usefulness and user attitude, which in turn affects behavioral intention to use QRIS. These findings confirm that the TAM model is effective in explaining the adoption of digital payment technology in North Sumatra. However, uneven digital infrastructure and low technological literacy are still the main challenges in increasing widespread adoption of QRIS. This research recommends improving digital access and education as strategic steps.


 

Keywords

QRIS, Technology Acceptance Model, Perceived Usefulness, Perceived Ease of Use, User Attitude, Behavioral Intention, North Sumatra

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Afriza Ulfa Ritonga, A. U. R., Rahmani, N. A. B. ., & Qarni, W. . (2025). Analysis of Determinants of QRIS Analysis of Determinants of QRIS Use in North Sumatra with the TAM Model (Technology Acceptance Model). Amkop Management Accounting Review (AMAR), 5(2), 01–16. https://doi.org/10.37531/amar.v5i2.2702
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References

  1. Aburbeian, A. H. M., Owda, A. Y., & Owda, M. (2022). A Technology Acceptance Model Survey of the Metaverse Prospects. AI (Switzerland), 3(2). https://doi.org/10.3390/ai3020018
  2. Adikoeswanto, D., Eliyana, A., Syamsudin, N., Budiyanto, S., Arief, Z., & Anwar, A. (2022). The mediation role of adoption readiness on perceived anxiety and attitude toward using database management system at correctional institutions. Heliyon, 8(8). https://doi.org/10.1016/j.heliyon.2022.e10027
  3. Agus Sulistyo, & Ismarti. (2022). Urgensi dan Strategi Penguatan Literasi Media dan Digital dalam Pembelajaran Agama Islam. At Turots: Jurnal Pendidikan Islam, 3(2), 5161. https://doi.org/10.51468/jpi.v3i2.75
  4. Akbar, A., Imsar, I., & Silalahi, P. R. (2024). ANALISIS PENERAPAN FINTECH PADA UMKM DI KOTA MEDAN DALAM PERSFEKTIF MAQASHID SYARIAH. Jurnal Manajemen Terapan dan Keuangan, 13(03), 806-820.
  5. Alfiandi, N., Rahma, T. I. F., & Inayah, N. (2024). Pengaruh Pengetahuan dan Kemanfaatan Quick Response Code Indonesian Standart (QRIS) Terhadap Penggunaan E-Wallet dikalangan Mahasiswa FEBI UIN Sumatera Utara. RUBINSTEIN, 2(2), 84-93.
  6. Amel, S. (2024). Transaksi QRIS Melonjak 214,93%, Ekonomi Digital Sumut Makin Dinamis. Mimbarumum. https://mimbarumum.co.id/transaksi-qris-melonjak-21493-ekonomi-digital-sumut-makin-dinamis/
  7. Balatif, M. R., Fachrudin, K. A., Silalahi, A. S., Syahyunan, & Torong, M. Z. B. (2024). The Effect Of Financial Education And Financial Stress On Financial Well-Being With The Use Of Financial Technology. Quality - Access to Success, 25(199). https://doi.org/10.47750/QAS/25.199.12
  8. Firdaus, M., Farohi, A., Saragih, A. N., & Harahap, M. (2023). Optimizing Digital Transactions: Analyzing UserS Adoption Intention of Quick Response Code Indonesian Standard (Qris) in North Sumatera. 134.
  9. Firmansyah, D., Saepuloh, D., & Dede. (2022). Daya Saing : Literasi Digital dan Transformasi Digital. Journal of Finance and Business Digital, 1(3). https://doi.org/10.55927/jfbd.v1i3.1348
  10. Hamidar, P., Mustafa, K. R., & Muhammad, I. H. (2024). Pengaruh Pengetahuan, Kemudahan Penggunaan, dan Kemanfaatan Quick Response Code Indonesian Standart (QRIS) Terhadap Penggunaan Ewallet (Studi Kasus Mahasiswa Fakultas Ekonomi dan Bisnis Islam UIN Sumatera Utara). MENAWAN: Jurnal Riset Dan Publikasi Ilmu Ekonomi.
  11. Hermanto, H., Somayasa, W., & Pimpi, L. (2020). Perbandingan Uji Likelihood Ratio Dan Uji F Asymtotik Pada Regresi Linier. Jurnal Pembelajaran Berpikir Matematika (Journal of Mathematics Thinking Learning), 5(2). https://doi.org/10.33772/jpbm.v5i2.15032
  12. Hrp, G. R., & Tambunan, K. (2023). Analisis Efektivitas Implementasi Sistem Pembayaran Digital QRIS Dalam Meningkatkan Penjualan Usaha Dagang Plastik Intan Baru Sibuhuan. JPEK (Jurnal Pendidikan Ekonomi Dan Kewirausahaan), 7(1), 70-82.
  13. ILORI, O. O., & TANIMOWO, F. O. (2022). Heteroscedasticity Detection in Cross-Sectional Diabetes Pedigree Function: A Comparison of Breusch-Pagan-Godfrey, Harvey and Glejser Tests. International Journal of Scientific and Management Research, 05(12). https://doi.org/10.37502/ijsmr.2022.51211
  14. Jaya, A. D., & Nurifanti, E. D. (2021). Pembaharuan Sistem KUPVA BB Sebagai Upaya Pencegahan dan Pemberantasan Tindak Pidana Pencuci Uang. Ikatan Penulis Mahasiswa Hukum Indonesia Law Journal, 1(2). https://doi.org/10.15294/ipmhi.v1i2.53269
  15. Khairani Lubis, R. (2022). Analisis Minat Penggunaan Quick Responses Code Indonesian Standard (QRIS) Dengan Pendekatan Technology Acceptance Model ( TAM) Yang Telah Dimodifikasi. In Skripsi,jurusan perbankan syariah,Institut Agama Islam Negeri Padangsidimpuan.
  16. Kotian, H., Varghese, A. L., & Rohith, M. (2022). An R Function for Cronbachs Alpha Analysis: A Case-Based Approach. National Journal of Community Medicine, 13(8). https://doi.org/10.55489/njcm.130820221149
  17. Mustafidah, H., Imantoyo, A., & Suwarsito, S. (2020). Pengembangan Aplikasi Uji-t Satu Sampel Berbasis Web. JUITA: Jurnal Informatika, 8(2). https://doi.org/10.30595/juita.v8i2.8786
  18. Nasution, A. S. P., Harahap, I., & Aslami, N. (2025). Pengaruh Kemudahan, Kecepatan dan Keamanan Penggunaan Qris Pada UMKM Halal Kota Medan. Jambura Economic Education Journal, 7(1), 420-435.
  19. Ningri, L. J., Hamidi, M., & Adrianto, F. (2023). Sentiment Analysis Against Digital Payment GoPay, OVO, DANA, and ShopeePay Using Naïve Bayes Classifier Algorithm. Indonesian Journal of Economics and Management, 3(2). https://doi.org/10.35313/ijem.v3i2.4765
  20. Nugraha, D. (2022). Literasi Digital dan Pembelajaran Sastra Berpaut Literasi Digital di Tingkat Sekolah Dasar. Jurnal Basicedu, 6(6). https://doi.org/10.31004/basicedu.v6i6.3318
  21. Park, E. S., & Park, M. S. (2020). Factors of the technology acceptance model for construction IT. Applied Sciences (Switzerland), 10(22). https://doi.org/10.3390/app10228299
  22. Putri, D. A., & Jannah, N. (2025). QRIS as a catalyst for growth: Analyzing its role in Tanjung Balai's MSME sector from an Islamic viewpoint. SERAMBI: Jurnal Ekonomi Manajemen dan Bisnis Islam, 7(1), 61-70.
  23. Quraisy, A. (2022). Normalitas Data Menggunakan Uji Kolmogorov-Smirnov dan Saphiro-Wilk. J-HEST Journal of Health Education Economics Science and Technology, 3(1). https://doi.org/10.36339/jhest.v3i1.42
  24. Santoso, A. (2023). Rumus Slovin : Panacea Masalah Ukuran Sampel ? Suksma: Jurnal Psikologi Universitas Sanata Dharma, 4(2). https://doi.org/10.24071/suksma.v4i2.6434
  25. Saragih, Y. W., & Rikumahu, B. (2022). Analisis Faktor Adopsi E-Wallet Gopay, OVO, dan DANA dengan Model UTAUT2 pada Masyarakat Jawa Barat. Nominal Barometer Riset Akuntansi Dan Manajemen, 11(1). https://doi.org/10.21831/nominal.v11i1.43075
  26. Seputri, W., Soemitra, A., & Rahmani, N. A. B. (2023). Pengaruh Technolgy Acceptance Model terhadap Minat Mahasiswa Menggunakan Quick Response Code Indonesian Standard (QRIS) sebagai Cashless Society. MES Management Journal, 2(1), 116-126.
  27. Setiawan, I. W. A., & Mahyuni, L. P. (2020). QRIS DI MATA UMKM: EKSPLORASI PERSEPSI DAN INTENSI UMKM MENGGUNAKAN QRIS. E-Jurnal Ekonomi Dan Bisnis Universitas Udayana. https://doi.org/10.24843/eeb.2020.v09.i10.p01
  28. Tan, H. (2022). Quantitative research methods in translation and interpreting studies. Poznan Studies in Contemporary Linguistics, 58(1). https://doi.org/10.1515/psicl-2022-0007
  29. Yu, J. (2024). Stabilizing leverage, financial technology innovation, and commercial bank risks: Evidence from China. Economic Modelling, 131. https://doi.org/10.1016/j.econmod.2023.106599