Analysis of Factors Influencing the Intention of Whistleblowing Action in the Social Services of The Special Region of Yogyakarta
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ACFE (2019) shows the proportion of Corruption with the highest percentage, namely 64.4%. Followed by Misuse of State and Company Assets or Wealth at 28.9% and Financial Statement Fraud with a percentage of 6.7%. Survey results show that government and administration are the industries that have the second highest level of fraud cases in the ACFE world (2019) with corruption occupying the highest percentage at 57% (ACFE, 2022). Fraud in the Asia-Pacific region, Indonesia ranks fourth out of 18 countries, 23 cases occurred in Indonesia out of a total of 194 cases, ACFE (2022). The rice social assistance (bansos) corruption case occurred which continued with a search at the Directorate General of Social Empowerment, and the determination of a number of suspects in the corruption case by the Corruption Eradication Committee (Rastika, 2023). The government has the duty and responsibility to provide services to the community, especially in relation to meeting needs to achieve community welfare. However, not all government officials or employees are aware of the importance of these duties and responsibilities. This is reinforced by the existence of 53 cases of misappropriation of Covid-19 social assistance funds in the Special Region of Yogyakarta. As a countermeasure, the Government facilitates a whistleblowing system accompanied by laws that guarantee the safety of whistleblowers, however this does not guarantee that all parties are willing to report. This prompted this research to analyze the factors that influence the intention of whistleblowing at the Yogyakarta Special Region Provincial Social Service with the variables Attitude, Personal Cost of Reporting, Organizational Commitment, Seriousness of Fraud, and Religiousness. The population and sample for this research are all employees at the Main Office of Social Services of Yogyakarta Special Region Province. Data source using questionnaires given offline. And the analysis tool used is SmartPLS 4.0.
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