Using LDA for audit risk assessment of the Indonesian BOS fund: Insights from news analysis

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...

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Bibliographic Details
Main Authors: Iis Istianah, Nia Pramita Sari, Afrialdi Syahputra Butar Butar, Bonar Cornellius Pasaribu
Format: Article
Language:English
Published: Badan Pemeriksa Keuangan Republik Indonesia 2024-12-01
Series:Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara
Subjects:
risk-based audit
text mining
topic modeling
LDA
BOS Fund
Online Access:https://jurnal.bpk.go.id/TAKEN/article/view/1803
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