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Constructing a Broad View of Tax Compliance Intentions Based on Big Data

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Machine Learning Approaches in Financial Analytics

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 254))

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Abstract

Taxpayer compliance is currently one of the problems faced by the government in any country, especially in developing countries. Taxpayer compliance can be assessed from the intention of the taxpayer toward compliance with the tax itself. The Directorate General of Taxes as an extension of the government in tax matters has the obligation to implement policies and technical standardization in the field of taxation, including in providing efforts to provide an understanding of the importance of taxation in developing a country. Therefore, tax compliance is an important thing to be improved by the government through tax compliance intentions. The basis related to compliance intentions is the Theory of Planned Behavior by (Ajzen in Organ Behav Hum Decis Process 50:179–211, 1991 [1]) which in this case is used as the basis for this discussion. To determine the factors driving the intention to comply, it is necessary to search for any variables that influence this. By using big data, the variables obtained are more in line with the current reality, because they are taken directly from the virtual world, which is more specifically sourced from online media. After the data is mined from social media, the raw data will be extracted and analyzed using Discourse Network Analysis (DNA) to be compiled into a variable which will then be modeled using Structural Equation Modeling (SEM).

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Author information

Authors and Affiliations

  1. Directorate of International Tax, Directorate General of Taxes in Indonesia, Jakarta, Indonesia

    Mekar Satria Utama

  2. Department of Statistics, University of Brawijaya, Malang, Indonesia

    Solimun & Adji Achmad Rinaldo Fernandes

Authors
  1. Mekar Satria Utama
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  2. Solimun
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  3. Adji Achmad Rinaldo Fernandes
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Corresponding author

Correspondence to Mekar Satria Utama .

Editor information

Editors and Affiliations

  1. Edinburgh Napier University, Edinburgh, UK

    Leandros A. Maglaras

  2. Department of Business Management, University of Pretoria, Hatfield, South Africa

    Sonali Das

  3. Indian Institute of Management, Shillong, India

    Naliniprava Tripathy

  4. Institute of Management and Technology, Bhubaneswar, Odisha, India

    Srikanta Patnaik

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Utama, M.S., Solimun, Fernandes, A.A.R. (2024). Constructing a Broad View of Tax Compliance Intentions Based on Big Data. In: Maglaras, L.A., Das, S., Tripathy, N., Patnaik, S. (eds) Machine Learning Approaches in Financial Analytics. Intelligent Systems Reference Library, vol 254. Springer, Cham. https://doi.org/10.1007/978-3-031-61037-0_14

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