The purpose of this study is to determine the variables that can explain the prediction of financial distress in manufacturing companies. This research was conducted to test the hypothesis (hypotheses testing) proposed by researchers, where the variables EBITS, ROE, Fixed Assets Turnover, Size and Tax Expense can explain the prediction of financial distress in manufacturing companies. As well as the use of an analytical model to measure prediction accuracy which can explain the prediction of financial distress by the logit model. This research uses secondary data obtained from ICMD Indonesia Stock Exchange (IDX). A total of 11 healthy companies and 11 unhealthy companies were taken using the Z-score method. The samples were companies experiencing financial distress taken during the 2004-2009 period. The data used in this study include financial ratios which include TOAS, CATA, SETA, APNPTA, SCA, SWC, STFA, GPM, LTDTD, WCLTD, CASH, PHASE, ROE, EBITPC, EBITS, OIBOIA. The statistical method used to test the hypothesis is Logistic Regression analysis with the Stepwise method. The results of this study indicate that the CATA, APNPTA, and CASH variable analysis tools are variables that can explain the prediction of financial distress in manufacturing companies listed on the IDX for the 2004-2009 period.
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