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dc.contributor.authorWITONO, DONNY SUSANTO
dc.date.accessioned2015-08-24T11:48:47Z
dc.date.available2015-08-24T11:48:47Z
dc.date.issued2012-05-29
dc.identifier.urihttp://hdl.handle.net/123456789/723
dc.description.abstractFinancial distress sometimes could lead to bankruptcy. The objective of this paper is making a financial distress prediction model in Indonesia using recent financial data from 2008 until 2011. The model tested using 24 financial ratios, which are: cash flow ratio, cash flow to total debt, current liabilities to total asset, EBIT to fixed asset, EBIT to total liabilities, equity to long term debt, market value of equity to book value of debt, net income to fixed asset, net income to total debt, total debt to total asset, current asset to current liabilities, liquid asset to current liabilities, net liquid asset to current liabilities, working capital to total asset, EBIT to current liabilities, EBIT to sales, EBIT to total asset, net income to sales, net income to total asset, retained earning to total asset, expenses to sales, sales to fixed asset , sales to total asset and working capital to sales. From the data analysis, this paper observes 28 distress companies and the pair 28 non distress companies. Logistic regression is the research methodology of this paper. The result of this paper shows that there are 12 ratios that compose the new prediction model. Those ratios are current liabilities to total asset, EBIT to fixed asset, net income to fixed asset, current asset to current liabilities, liquid asset to current liabilities, working capital to total asset, EBIT to sales, EBIT to total asset, net income to sales, net income to total asset, and retained earning to total asset. The accuracy of the model is 76.8%.en_US
dc.language.isoenen_US
dc.publisherUniversitas Pelita Harapan Surabaya - Department Of Business School - Master Of Managementen_US
dc.subjectFinancial Distressen_US
dc.subjectFinancial Ratioen_US
dc.subjectLogistic Regressionen_US
dc.titlePREDICTING FINANCIAL DISTRESS IN INDONESIA COMPANIESen_US
dc.typeThesisen_US


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