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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
De-Ron Liang
National Central University, Zhongli
Computer Science & IT Control & Systems Engineering

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Financial Distress Prediction with Stacking Ensemble Learning Muhammad Fadhlil Hadi; De-Ron Liang; Tri Kuntoro Priyambodo; Azhari SN
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 3 (2022): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.76575

Abstract

Previous studies have used financial ratios extensively to build their predictive model of financial distress. The Altman ratio is the most often used to predict, especially in academic studies. However, the Altman ratio is highly dependent on the validity of the data in financial statements, so other variables are needed to assess the possibility of manipulation of financial statements. None of the previous studies combined the five Altman Ratios with the Beneish M-Score. We use Stacking Ensemble Learning to classify crisis companies and perform a comprehensive analysis. This insight helps the investment public make lending decisions by mixing all the financial indicator information and assessing it carefully based on long-term and short-term conditions and possible manipulation of financial statements.
Co-Authors Azhari SN Muhammad Fadhlil Hadi Tri Kuntoro Priyambodo