Sains Data Perpajakan di Indonesia: Implementasi Praktis, Pembelajaran, dan Agenda Kajiannya

Agung Darono

Abstract


As a relatively recently developed discipline, Tax data science requires a study that focuses on important themes related to how the discipline is applied by both taxpayers and tax authorities (central or regional). This research using an action research strategy is an attempt to present a map of the practical implementation of data science and then relate it to the learning needs for the development of human resource capacity of related tax practitioners as well as the necessary research agenda so that this practice works in line with the needs of the organization. This study, from the aspect of tax research methodology, contributes by providing a result that can be an additional reference regarding how action research strategies can produce practical knowledge of taxation data science from both the perspective of taxpayers and tax authorities.

Full Text:

PDF

References


Aasheim, C.L., S. Williams, Paige Rutner, and A. Gardiner. 2015. “Data Analytics vs. Data Science: A Study of Similarities and Differences in Undergraduate Programs Based on Course Descriptions.” Journal of Information Systems Education 26 (January): 103–15.

Altrichter, Herbert, Stephen Kemmis, Robin Mctaggart, and Ortrun Zuber-Skerritt. 2002. “The Concept of Action Research.” Learning Organization, The 9 (August): 125–31. https://doi.org/10.1108/09696470210428840.

Ayres, Lioness. 2008. “Thematic Coding and Analysis.” In Encyclopedia of Qualitative Research Methods, 867–68.

Baskerville, Richard, and Trevor Wood-Harper. 1996. “A Critical Perspective on Action Research as a Method for Information Systems Research.” Journal of Information Technology 11 (September): 235–46. https://doi.org/10.1080/026839696345289.

Booch, Grady, James Rumbaugh, and Ivar Jacobson. 1998. Unified Modeling Language User Guide. Reading, Massachusetts: Addison Wesley.

Carina, Federico, and Travis Thompson. 2019. “Do IRS Computers Dream About Tax Cheats? Artificial Intelligence and Big Data in Tax Enforcement and Compliance.” Journal of Tax Practice & Procedure, no. Feb-Mar: 43–47. https://www.crowell.com/files/2019-Feb-March-Do-IRS-Computers-Dream-About-Tax-Cheats-Federico.pdf.

Chapman, Peter, Janet Clinton, Randy Kerber, Tom Khabaza, Thomas P. Reinartz, Colin Shearer, and Richard Wirth. 2000. “CRISP-DM 1.0: Step-by-Step Data Mining Guide.” In .

Creswell, John W. 2013. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Thousand Oaks, California: SAGE Publications.

Cuadrado-Gallego, Juan J., and Yuri Demchenko. 2020. “Introduction to the Data Science Framework.” In , 1–7. Springer.

Das, Sibanjan. 2016. Data Science Using Oracle Data Miner and Oracle R Enterprise. New York: Apress Media.

Davenport, Thomas H., and D.J. Patil. 2012. “Data Scientist: The Sexiest Job of the 21st Century” 2012 (October).

Donoho, David. 2017. “50 Years of Data Science.” Journal of Computational and Graphical Statistics 26: 745–66. https://doi.org/10.1080/10618600.2017.1384734.

French, Steven. 2009. “Action Research for Practising Managers.” Journal of Management Development 28 (March): 187–204. https://doi.org/10.1108/02621710910939596.

Hardyana, Yan. 2020. “Best Practice for A Data Analytics Tax Strategy.” Presented at the Seminar Nasional Perpajakan, FIA UB.

Heller, Frank. 2004. “Action Research and Research Action: A Family of Methods.” In Essential Guide to Qualitative Methods in Organizational Research, edited by Catherine Cassell and Gillian Symon, 349–60. London: SAGE Publications Ltd.

Houser, Kimberly A., and Debra Sanders. 2017. “The Use of Big Data Analytics by the IRS: Efficient Solutions or the End of Privacy as We Know It?” Vanderbilt Journal of Entertainment & Technology Law 19 (4): 871–72.

IOTA. 2016. “Applying Data and Analytics in Tax Administration.” IOTA Good Practice Guide. Intra-European Organisation of Tax Administrations (IOTA). https://www.iota-tax.org/good-practice-guide-applying-data-and-analytics-tax-administrations.

Kurtz, Jennifer. 2018. “Understanding Data’s Impact on the Future of Tax Functions.” Vertex. https://www.europeanceo.com/finance/understanding-datas-impact-on-the-future-of-tax-functions/.

Lapadat, Judith C. 2010. “Thematic Analysis.” In Encyclopedia of Case Study Research, edited by Albert J. Mills, Gabrielle Durepos, and Elden Wiebe, 925–27. Thousand Oaks, California: SAGE Publications, Inc.

Martinez, Iñigo, Elisabeth Viles, and Igor Olaizola. 2021. “Data Science Methodologies: Current Challenges and Future Approaches.” Big Data Research 24 (January): 100183. https://doi.org/10.1016/j.bdr.2020.100183.

Microsoft, and PwC. 2018. “The Data Intelligent Tax Administration - Meeting the Challenges of Big Tax Data and Analytics.” Netherland: Microsoft and PricewaterhouseCoopers Belastingadviseurs N.V. https://www.pwc.nl/nl/assets/documents/the-data-intelligent-tax-administration-whitepaper.pdf.

Pierson, Lillian. 2015. Data Science For Dummies. John Wiley & Sons, Inc.

Pijnenburg, Mark Gerardus Franciscus. 2020. “Data Science for Tax Administration.” Ph.D. thesis, Netherland: Leiden University.

Prastuti, Gitarani, and Lasmin. 2021. “Assessing Analytics Maturity Level in The Indonesian Tax Administration: The Case of Compliance Risk Management” 2 (2): 199–217. https://doi.org/10.52869/st.v2i2.157.

Press, Gil. 2013. “A Very Short History Of Big Data,” 2013. https://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/#2135d2fe65a1.

Provost, Foster, and Tom Fawcett. 2013. Data Science for Business. Sebastopol, CA: O’Reilly Media, Inc.

Rollins, John B. 2015. “Foundational Methodology for Data Science.” Route 100 Somers, NY 10589: IBM Analytics.

Shan, JingJing. 2019. “Optimization Strategy of Tax Planning System in the Context of Artificial Intelligence and Big Data.” Journal of Physics: Conference Series 1345 (November): 052006. https://doi.org/10.1088/1742-6596/1345/5/052006.

Somekh, Bridget. 2006. Action Research: A Methodology for Change and Development. Open University Press McGraw-Hill Education.

Worsley, Rob. 2017. “Data Science for Business.” IBM Corporation. https://www.ibm.com/downloads/cas/YLORK8WL.

Zhu, Yangyong, and Yun Xiong. 2015. “Defining Data Science.” CoRR abs/1501.05039. http://arxiv.org/abs/1501.05039.


Refbacks

  • There are currently no refbacks.