Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences

HU-Model Effectiveness in Corruption Detection Haryono Umar; Siti Safaria; Welda Mudiar; Rahima Br Purba; Harsono Harsono; Karyaningsih Karyaningsih
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3102

Abstract

This study aims to test the effectiveness of the HU-Model used in corruption detection efforts. The increasing number of corruption cases shows that the tools to detect corruption are not yet available. With the mode of corruption that is increasingly developing and complex, the existence of a corruption detection tool is a must. The focus of this research is on the causes of fraud star corruption which shows that the cause is due to abuse of power or the authority being exercised is not by the mandate. The characteristics of corruption in Indonesia are very complex, involving various elements from the government / private sector, State / Regional Owned Enterprises (BUMN / D) as well as public officials from the center to the regions. This article discusses the corruption detection model as one of the contributions to fight corruption in Indonesia. As one of the efforts to make Indonesia free from corruption outbreaks, the HU model consists of the variable lack of integrity (lack of integrity), opportunity (opportunity), pressure (pressure), rationalization (rationalization), and the ability (capability) to provide hope and answers. The HU-Model proves that despite the amount of pressure, the number of opportunities, the ease of justification, and the high position and authority will not encourage acts of corruption if there is still strong integrity. The results show that the indications of corruption are divided into three clusters, namely those with indications of corruption (red), gray (gray), and no indications of corruption (green).
The Role of an Accountant in Detecting Corruption Haryono Umar; Rahima Br Purba; Siti Safaria; Welda Mudiar
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 5, No 3 (2022): Budapest International Research and Critics Institute August
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i3.6555

Abstract

The increasing corruption has made Indonesia one of the countries in the red category (corrupt) globally. Corruption is an act to enrich oneself, other people, or corporations by violating the law or abusing authority the focus of this research is on the causes of fraud star corruption. The characteristics of corruption in Indonesia are very complex, abuse of power or authority, and not carried out with trust. Involving various elements from the government/private sector is the cause of fraud star corruption, this occurs in State/Regional Owned Enterprises (BUMN/D) and public officials from the center to the regions. This study discusses one of the contributions in fighting corruption in Indonesia, using a corruption detection model. To be free from the corruption epidemic in Indonesia, the introduction of the HU model consists of the variables lack of integrity (lack of integrity), opportunity (opportunity), pressure (pressure), rationalization (rationalization), and capability (capability) to give hope and get answers. The HU model proves that even the amount of pressure, the number of opportunities, the ease of justification, as well as a high position and authority will not encourage corruption if there is strong integrity. The result shows that the loss of integrity is the most dominant cause of people committing corruption. This study is also able to categorize agencies that are indicated as being corrupt (red), between indicated and not indicated (grey), and not indicated (green).