Analysis of Financial Distress Prediction at PT Kharisma Dua Putri for 2020–2024

Abstract : This study aims to analyze the prediction of financial distress at PT Kharisma Dua Putri (KDP) for the 2020–2024 period using multiple bankruptcy prediction models, namely Altman Z-Score, Springate, Grover, Zmijewski, Taffler. The purpose of this research is to evaluate the company’s financial condition by comparing the predictive consistency among the models and identifying indicators of potential distress. A quantitative descriptive approach is employed using secondary data obtained from audited financial statements covering 2020 to 2024. The results of each model are compared to assess the firm’s financial health and risk of insolvency. The findings reveal variations in prediction outcomes, with several models indicating early signs of financial vulnerability, particularly during periods of declining profitability and liquidity. Overall, PT KDP experienced fluctuating financial performance that approached distress thresholds in certain years. The study highlights the importance of a multi-model analytical approach to enhance the accuracy of financial distress assessment and to provide early warning signals for managerial decision-making.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-26
DOI
https://doi.org/10.5281/zenodo.17720531
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
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article

Analysis of Financial Distress Prediction at PT Kharisma Dua Putri for 2020–2024

Zenodo (CERN European Organization for Nuclear Research)
Financial Distress and Bankruptcy Prediction
article

Analysis of Financial Distress Prediction at PT Kharisma Dua Putri for 2020–2024

article en

Abstract

Abstract : This study aims to analyze the prediction of financial distress at PT Kharisma Dua Putri (KDP) for the 2020–2024 period using multiple bankruptcy prediction models, namely Altman Z-Score, Springate, Grover, Zmijewski, Taffler. The purpose of this research is to evaluate the company’s financial condition by comparing the predictive consistency among the models and identifying indicators of potential distress. A quantitative descriptive approach is employed using secondary data obtained from audited financial statements covering 2020 to 2024. The results of each model are compared to assess the firm’s financial health and risk of insolvency. The findings reveal variations in prediction outcomes, with several models indicating early signs of financial vulnerability, particularly during periods of declining profitability and liquidity. Overall, PT KDP experienced fluctuating financial performance that approached distress thresholds in certain years. The study highlights the importance of a multi-model analytical approach to enhance the accuracy of financial distress assessment and to provide early warning signals for managerial decision-making.

Zenodo (CERN European Organization for Nuclear Research)
Tarumanagara University (ID)
Peace, Justice and strong institutions
Openalex Percentile: Top 31%
Financial Distress and Bankruptcy Prediction
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