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Accounting and Management Journal
Article . 2019 . Peer-reviewed
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Accounting and Management Journal
Article
License: CC BY SA
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PREDIKSI FINANCIAL DISTRESS PADA SEKTOR PERTAMBANGAN

Authors: Anita Handayani;

PREDIKSI FINANCIAL DISTRESS PADA SEKTOR PERTAMBANGAN

Abstract

Financial distress shows the condition of the company unable to fulfill its smooth obligations. Financial difficulties if not handled properly will bring the company into bankruptcy. Bankruptcy predictions can use the Altman, Springate, Grover, Zmijewski methods. The results showed that the accuracy of the Springate model predicts financial distress by 73% compared to other models. And sequentially followed by Altman’s model of 54%, and the grover model of 35% and the last is the zmijewski model of 22%.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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