The problem of corruption in government organizations: Empirical evidence from Indonesia

  • Received August 19, 2021;
    Accepted September 22, 2021;
    Published October 7, 2021
  • Author(s)
    Dwi Ratmono
    ORCID , Arini Cholbyah ,
    Nur Cahyonowati
    ORCID , Darsono Darsono
  • DOI
    http://dx.doi.org/10.21511/ppm.19(4).2021.03
  • Article Info
    Volume 19 2021, Issue #4, pp. 29-39
  • TO CITE АНОТАЦІЯ
  • Cited by
    2 articles
  • 921 Views
  • 316 Downloads

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

Corruption in government organizations is an important and relevant topic to study because of its impact on the state in terms of financial losses and a decrease in the quality of human development. This study is also relevant because previous analyses are still limited in their modeling and measuring comprehensive fiscal decentralization variables. This study aims to examine the effect of fiscal decentralization and quality of government on the level of corruption and the impact of corruption on the human development index. The sample of this paper comprises 113 local governments on the island of Java, Indonesia, for the period 2015–2018. Statistical testing was carried out using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The test results show that fiscal decentralization has a positive effect on corruption with a path coefficient of 0.100 and is significant at 5% alpha. Likewise, poor governance (proxied by internal control weaknesses) has a positive effect on the level of corruption with a coefficient of 0.062 and is significant at an alpha of 10%. The results of the PLS-SEM test also show that corruption has a negative impact on the human development index with a coefficient of –0.206 and is significant at 1% alpha. The practical significance of this study is the importance of the internal control system reliability as a complementary variable for fiscal decentralization to prevent corruption.

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    • Figure 1. Results of Partial Least Square (PLS) test
    • Table 1. Descriptive statistics
    • Table 2. Results of the measurement model evaluation
    • Table 3. Model fit indices
    • Table 4. Path coefficients and p-values results
    • Conceptualization
      Dwi Ratmono, Arini Cholbyah
    • Data curation
      Dwi Ratmono, Arini Cholbyah
    • Formal Analysis
      Dwi Ratmono
    • Investigation
      Dwi Ratmono, Nur Cahyonowati, Darsono Darsono
    • Methodology
      Dwi Ratmono, Arini Cholbyah
    • Project administration
      Dwi Ratmono, Arini Cholbyah
    • Software
      Dwi Ratmono
    • Supervision
      Dwi Ratmono, Nur Cahyonowati
    • Validation
      Dwi Ratmono, Darsono Darsono
    • Writing – original draft
      Dwi Ratmono, Nur Cahyonowati
    • Writing – review & editing
      Dwi Ratmono, Nur Cahyonowati, Darsono Darsono
    • Resources
      Darsono Darsono
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