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  • 标题:KETEPATAN MODEL ALTMAN, SPRINGATE, ZMIJEWSKI, DAN GROVER DALAM MEMPREDIKSI FINANCIAL DISTRESS
  • 作者:Edi Edi ; May Tania
  • 期刊名称:Jurnal Reviu Akuntansi dan Keuangan
  • 出版年度:2018
  • 卷号:8
  • 期号:1
  • 页码:79-92
  • DOI:10.22219/jrak.v8i1.28
  • 语种:Indonesian
  • 出版社:Jurnal Reviu Akuntansi dan Keuangan
  • 摘要:This study aims to identify and analyze the accuracy models of financial distress between the model results of Altman, Springate, Zmijewski, and Grover. The model used by investors, creditors and the company itself who will invest in the company and evaluate the financial performance. Samples from this study are 1.321 firm-year, collected from Indonesia Stock Exchange for the period 2012-2016 and were selected using purposive sampling method. The data used in this study are financial reports of each company. The data obtained were tested with logistic regression. This study shows that the model of Altman, Springate, Zmijewski, and Grover has a significant impact and can be used for predicting the condition of financial distress. However, the Springate model is the most appropriate model for predicting the condition of financial distress because it has the highest level of coefficient determination compared to other models.
  • 其他摘要:This study aims to identify and analyze the accuracy models of financial distress between the model results of Altman, Springate, Zmijewski, and Grover. The model used by investors, creditors and the company itself who will invest in the company and evaluate the financial performance. Samples from this study are 1.321 firm-year, collected from Indonesia Stock Exchange for the period 2012-2016 and were selected using purposive sampling method. The data used in this study are financial reports of each company. The data obtained were tested with logistic regression. This study shows that the model of Altman, Springate, Zmijewski, and Grover has a significant impact and can be used for predicting the condition of financial distress. However, the Springate model is the most appropriate model for predicting the condition of financial distress because it has the highest level of coefficient determination compared to other models.
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