Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis
This study explores the implementation of text mining in audit risk assessment. We use the latent Dirichlet allocation (LDA) algorithm to reveal hidden topics representing risks in the management of the Indonesian School Operational Assistance Fund (BOS Fund). Using 1,460 news data points from a le...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Badan Pemeriksa Keuangan Republik Indonesia
2024-12-01
|
| Series: | Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara |
| Subjects: | |
| Online Access: | https://jurnal.bpk.go.id/TAKEN/article/view/1803 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846106593776631808 |
|---|---|
| author | Iis Istianah Nia Pramita Sari Afrialdi Syahputra Butar Butar Bonar Cornellius Pasaribu |
| author_facet | Iis Istianah Nia Pramita Sari Afrialdi Syahputra Butar Butar Bonar Cornellius Pasaribu |
| author_sort | Iis Istianah |
| collection | DOAJ |
| description |
This study explores the implementation of text mining in audit risk assessment. We use the latent Dirichlet allocation (LDA) algorithm to reveal hidden topics representing risks in the management of the Indonesian School Operational Assistance Fund (BOS Fund). Using 1,460 news data points from a leading Indonesian news portal, this study proves that using text mining with the LDA algorithm effectively identifies the risks of an audit object. This study makes two important contributions to the information systems and audit literature. First, it provides evidence from online news archives to facilitate a more reliable, current, and comprehensive selection of potential audit areas by encompassing evolving social realities and facts. In the contemporary era, the accelerated and precise dissemination of information via the Internet renders the LDA approach feasible and prudent. Second, it provides a practical and applicable framework for audit risk assessment using nonfinancial sources from independent parties, which can be used as a guide for the development of audit models in the public and private sectors.
|
| format | Article |
| id | doaj-art-c9c87f0e4ef545d78f80cc2560f63adc |
| institution | Kabale University |
| issn | 2460-3937 2549-452X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Badan Pemeriksa Keuangan Republik Indonesia |
| record_format | Article |
| series | Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara |
| spelling | doaj-art-c9c87f0e4ef545d78f80cc2560f63adc2024-12-27T12:49:31ZengBadan Pemeriksa Keuangan Republik IndonesiaJurnal Tata Kelola dan Akuntabilitas Keuangan Negara2460-39372549-452X2024-12-0110210.28986/jtaken.v10i2.1803Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysisIis Istianah0Nia Pramita Sari1https://orcid.org/0009-0008-7597-0550Afrialdi Syahputra Butar Butar2Bonar Cornellius Pasaribu3Faculty of Economics and Business, Gadjah Mada University, YogyakartaFaculty of Economics and Business, Gadjah Mada University, YogyakartaThe Audit Board of the Republic of Indonesia, JakartaMaster of Public Policy and Management, University of Melbourne, Melbourne This study explores the implementation of text mining in audit risk assessment. We use the latent Dirichlet allocation (LDA) algorithm to reveal hidden topics representing risks in the management of the Indonesian School Operational Assistance Fund (BOS Fund). Using 1,460 news data points from a leading Indonesian news portal, this study proves that using text mining with the LDA algorithm effectively identifies the risks of an audit object. This study makes two important contributions to the information systems and audit literature. First, it provides evidence from online news archives to facilitate a more reliable, current, and comprehensive selection of potential audit areas by encompassing evolving social realities and facts. In the contemporary era, the accelerated and precise dissemination of information via the Internet renders the LDA approach feasible and prudent. Second, it provides a practical and applicable framework for audit risk assessment using nonfinancial sources from independent parties, which can be used as a guide for the development of audit models in the public and private sectors. https://jurnal.bpk.go.id/TAKEN/article/view/1803risk-based audittext miningtopic modelingLDABOS Fund |
| spellingShingle | Iis Istianah Nia Pramita Sari Afrialdi Syahputra Butar Butar Bonar Cornellius Pasaribu Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara risk-based audit text mining topic modeling LDA BOS Fund |
| title | Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis |
| title_full | Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis |
| title_fullStr | Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis |
| title_full_unstemmed | Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis |
| title_short | Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis |
| title_sort | using lda for audit risk assessment of the indonesian bos fund insights from news analysis |
| topic | risk-based audit text mining topic modeling LDA BOS Fund |
| url | https://jurnal.bpk.go.id/TAKEN/article/view/1803 |
| work_keys_str_mv | AT iisistianah usingldaforauditriskassessmentoftheindonesianbosfundinsightsfromnewsanalysis AT niapramitasari usingldaforauditriskassessmentoftheindonesianbosfundinsightsfromnewsanalysis AT afrialdisyahputrabutarbutar usingldaforauditriskassessmentoftheindonesianbosfundinsightsfromnewsanalysis AT bonarcornelliuspasaribu usingldaforauditriskassessmentoftheindonesianbosfundinsightsfromnewsanalysis |