Analisis Pengaruh Pemerintahan Dengan Algoritma Dan Artificial Intelligence (AI) Terhadap Kepatuhan Wajib Pajak Pada Kpp Pratama Jakarta Mampang Prapatan
Keywords:
Government with Algorithms and Artificial Intelligence (Ai) on Taxpayer Compliance, Kpp Pratama Jakarta
Abstract
This study aims to analyze the effect of governance by algorithm and artificial intelligence (AI) on taxpayer compliance at KPP Pratama Jakarta Mampang Prapatan. The results showed that there is a significant influence between government with algorithms and artificial intelligence on taxpayer compliance. In the government variable with the algorithm (X1), the t-count value is 5,491 with a significance level of 0.000, which is smaller than the 5% confidence level. This t-count value (5.491) is greater than the t-table (1.967). This causes the alternative hypothesis (Ha) to be accepted and the null hypothesis (H0) to be rejected, so it can be concluded that there is a significant influence between government and algorithms on taxpayer compliance at KPP Pratama Jakarta Mampang Prapatan. Furthermore, in the artificial intelligence variable (X2), the t-count value is 5.892 with a significance level of 0.001, which is greater than the 5% confidence level. The t-count value (5.463) is also greater than the t-table (1.967). This causes the alternative hypothesis (Ha) to be accepted and the null hypothesis (H0) to be rejected, so it can be concluded that there is a significant influence between artificial intelligence on taxpayer compliance at KPP Pratama Jakarta Mampang Prapatan. The results of the determination test of the Government with Algorithms and Artificial Intelligence can explain the Taxpayer Compliance of KPP Pratama Jakarta Mampang Prapatan by Adjusted R square is 0.774 which means 77.40%, while the remaining 22.60% is influenced by other factors.
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Undang-undang No. 25 tahun 2009 tentang pelayanan publik.
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Bovens, M. and Zouridis, S. (2002) ‘From street-level to system-level bureaucracies: How information and communication tech- nology is transforming administrative discre- tion and constitutional control’, Public Administration Review, 62 (2): 174–84.
Zaid Aljodat, Vishanth Weerakkody, Ramzi El-Haddadeh (2021). The Rise of Algorithm-Driven Government: A Review of the Use of Algorithms in Public Sector Decision-Making. Journal: Government Information Quarterly.
Aji, Bagus Prabowo, ‘Implementasi Big Data Analytics Berbasis Machine Learning Pada Industri Implementasi Big Data Analytics ( BDA ) Berbasis Machine Learning Pada Industri Retail : A Literature Review’, ResearchGate, January, 2019, 2–6.
Ali S. 2020. Revolusi lndustri 4.0 dan Dampaknya terhadap Pendidikan Akuntansi di Indonesia. Yogyakarta Badan Penerbit Fak Ekon.
Bagus Prabowo Aji (2018), Implementasi Big Data Analytics Berbasis Machine Learning pada Industri Ritel: a literature review.
Cahyani, (2022) Pengaruh Modernisasi Sistem Administrasi Perpajakan Terhadap Kepatuhan Wajib Pajak Orang Pribadi Dimoderasi Dengan Teknologi.
Dani, (2018) Pengaruh Sistem Administrasi Perpajakan Modern Dan Sanksi Perpajakan Terhadap Kepatuhan Wajib Pajak (Survey pada 5 KPP di Kanwil DJP Jabar 1.
Diamendia, Tia, and Milla S Setyowati, ‘Analisis Kebijakan Compliance Risk Management Berbasis Machine Learning Pada Direktorat Jenderal Pajak’, Indonesian Treasury Review: Jurnal Perbendaharaan, Keuangan Negara Dan Kebijakan Publik, 6.3 (2021), 289–98
Fathani dan Apollo, (2020). Pengaruh Modernisasi Sistem Administrasi Perpajakan, Sanksi Pajak Terhadap Kepatuhan Wajib Pajak Orang Pribadi Pada KPP Pratama.
Ferdinand, A. (2017). Structural Equation Modelling Dalam Penelitian Manajemen: Aplikasi Model-model Rumit Dalam Penelitian untuk Tesis Magister dan Disertasi Doktor. (Ed. 2). Universitas Dipenogoro.
Ghozali, I., & Latan, H. (2018). Partial Least Squares Konsep, Teknik, dan. Aplikasi Menggunakan Program SmartPLS 3.0. Universitas Dipenogoro.
Gibson, J. L. Dkk. (2015). Organisasi dan Manajemen. Jakarta; Penerbit Erlangga.
Goodman 8, Flaxman S (2017) European union regulations on algorithmic decision making and a ''right to explanation." Al Mag 38:50-57. https://doi.org/10.1609/aimag.v38i3.2741.
Gunadi. 2015. Panduan Komprehensif Pajak Penghasilan. Jakarta: Bee Media. Indonesia.
Hagras, H. K. Almohammadi,D.Alghazzawi, and G. Aldabbagh, (2018) “A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms,” J. Artif. Intell. Soft Comput. Res., vol. 7, no. 1, pp. 47–64, 2017, doi: 10.1515/jaiscr-2017-0004.
Halida An Nabila, Primandita Fitriandi (2018) Implementasi Compliance Risk Management Sebagai Decision Support System Dalam Kegiatan Penagihan Di Direktorat Jenderal Pajak.
Hamonangan Timbul, Simanjuntak dan Imam Mukhlis. 2012. Dimensi Ekonomi. Perpajakan Dalam Pembangunan Ekonomi. Depok.
Jenna Sweeting, Michael Mintrom (2020). "Artificial Intelligence in Government: Benefits and Risks". Journal: Public Administration Review
Kasmir. (2017). Customer Service Excellent Teori dan Praktik. Jakarta: RajaGrafindo Persada.
Keputusan Menteri Keuangan No.483/KMK.03/2020 tentang Pembaruan Sistem Inti Administrasi Perpajakan.
Kurnia, Siti Rahayu, 2017, Perpajakan Konsep dan Aspek Formal,. Bandung: Rekayasa Sains.
Goralski, Margaret A., And Tay Keong Tan. ―Artificial Intelligence And
Sustainable Development.‖ The International Journal Of Management Education 18, No. 1 (March 2020): 100330.
Madya, Faizal. Rulinawaty dan Pasaribu, Daniel. (2022). Government with Algorithm: Strategy to Improve Synchronous Public Service Using Artificial Intelligence (AI) in Indonesia. Budapest International Research and Critics Institute-Journal (BIRCI-Journal). Volume 5, No 2, May 2022, Page: 14089-14100
Muliari, Ni Ketut dan Putu Ery Setiawan. 2016. Pengaruh Persepsi Tentang Sanksi Perpajakan dan Kesadaran Wajib Pajak Pada Kepatuhan Pelaporan Wajib Pajak Orang Pribadi Di Kantor Pelayanan Pajak Pratama Depansar Timur. Jurnal Akuntansi dan Bisnis, Volume 2.
Nabila, Halida An, and Primandita Fitriandi, ‘Implementasi Compliance Risk Management Sebagai Decision Support’, Implementasi Compliance Risk Management Sebagai Decision Support System Dalam Kegiatan Penagihan Di Direktorat Jenderal Pajak, 2021, 67–82.
Nasucha. Chaizi (2014). Reformasi Administrasi Publik: Teori dan Praktek. Jakarta, PT Gramedia Widiasarana Indonesia.
Nasution, S. (2017) ‘Variabel penelitian’, Raudhah.
Nazarov, M. A., O. L. Mikhaleva, and K. S. Chernousova, ‘Digital Transformation of Tax Administration’, Lecture Notes in Networks and Systems, 84 (2020), 144–49
Kaufmana Publishe.
Pangkey, F. M., Furkan, L. M., & Herman, L. E. (2019). Pengaruh Artificial
Intelligence dan Digital Marketing terhadap Minat Beli Konsumen.
Jurnal Magister Manajemen Unram Vol, 8(3)
Prianto Budi Saptono, and Ismail Khozen, ‘Rekonstruksi Pendekatan Compliance Risk Management Di Masa Pandemi Dalam Upaya Penguatan Penerimaan Pajak’, Scientax, 3.1 (2021), 105–29
Rahman. Abdul, 2013. Administrasi Perpajakan. Bandung : Nuansa.
Riduwan, dan Engkos Achmad Kuncoro. 2017. Cara Menggunakan dan Memakai. Path Analysis (Analisis Jalur). Bandung : Alfabeta.
Rosdiana Haula dan Edi Slamet Irianto. 2012. Pengantar Ilmu Pajak: Kebijakan dan Implementasi. Jakarta: Raja Grafindo Persada.
Saefudin dan Rahmawati (2020), Digitalisasi Administrasi Perpajakan: Implementasi di KPP Pratama Semarang Selatan.
Sousa, W. G. de, Melo, E. R. P. de, Bermejo, P. H. D. S., Farias, R. A. S., & Gomes, A. O. (2019). How and where is artificial intelligence in the public sector going? A literature review and research agenda. Government Information Quarterly, 36(4), 101392.
https://doi.org/10.1016/j.giq.2019.07.004.
Sudjana. 2016. Metode Statistika. Bandung: PT. Tarsido Bandung.
Sugiyono (2017). Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung : Alphabet.
Sukada, I Wayan, ‘Implementasi Compliance Risk Management (CRM) Dalam Rangka Esktensifikasi’, Prosiding Simposium Keuangan Negara, 2020, 876–91
Tanzi. 2012. A Retrospective Study on Tax Reform On 14. Industrialization
Developed Countries. Palgrave Macmillan Journals, 25 (3), pp: 417-451.
Tia Diamendia (2019) Analisis Kebijakan Compliance Risk Management Berbasis Machine Learning Pada Direktorat Jenderal Pajak.
Undang-undang No. 25 tahun 2009 tentang pelayanan publik.
Undang-Undang Republik Indonesia Nomor 28 Tahun 2007 tentang Ketentuan Umum dan Tata Cara Perpajakan (UU KUP 2007).
Valin, J. (2018). Humans still needed: An analysis of skills and tools in public relations. Chartered Institute of Public Relations. https://www.cipr.co.uk/sites/default/files/11497_CIPR_AIinPR_A4_v7.pdf.
Vochozka, & V. V. Mantulenko (Eds.), (2020) Digital Age: Chances, Challenges and Future (Vol. 84, pp. 62–70). Springer International
Publishing. https://doi.org/10.1007/978-3-030-27015-5_8.
Wahid Sulaiman. (2014). Analisis Regresi Menggunakan SPSS. Yogyakarta: Penerbit ANDI.
Wharton, S. Amy. (2012). The Sociology Gender.United Kingdom : John. Wiley & Sons Ltd
Wirtz, Lovelock. Christoper dan Muller. Jochen. 2011. Manajemen Pemasaran, Jasa Manusia, Teknologi, Strategi. Edisi 7 Jilid 1 dan 2. Jakarta: Erlangga
Yogaswara, R (2020) Artificial intelligence sebagai penggerak industri 4.0 dan tan- tangannya bagi sektor pemerintah dan swasta,” Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi, vol. 10, 2019.
Coglianese, C. (2021) ‘Algorithmic regulation: Machine learning as a governance tool’, in M. Schuilenburg and R. Peeters (eds), The Algorithmic Society: Technology, Power, and Knowledge. London and New York: Rout- ledge. pp. 35–52.
Lara Saldivar-Tanaka, Jennifer Shkabatur (2019) "Algorithmic Governance: Developing a Research Agenda through the Power of Platforms, Policies, and Procedures" (2019)
Journal: Public Administration Review.
Lorenz, L., Meijer, A. and Schuppan, T. (2020) ‘The Algocracy as a new ideal type for gov- ernment organizations: Predictive policing in Berlin as an empirical case’, Information Polity, pre-press, 1–16.
Bovens, M. and Zouridis, S. (2002) ‘From street-level to system-level bureaucracies: How information and communication tech- nology is transforming administrative discre- tion and constitutional control’, Public Administration Review, 62 (2): 174–84.
Zaid Aljodat, Vishanth Weerakkody, Ramzi El-Haddadeh (2021). The Rise of Algorithm-Driven Government: A Review of the Use of Algorithms in Public Sector Decision-Making. Journal: Government Information Quarterly.
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2024-07-08
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