The purpose of this study is to predict the independent auditor opinion using data mining techniques. Independent auditor's opinion (on this study) has been classified to qualify and unqualify class. Using two data mining classification techniques including decision tree C5.0 and artificial neural networks. In order to predict the independent auditors opinion. using 29 financial and nonfinancial variables in 10 groups of liquidity, performance, financial leverage, capital structure, profitability, bankruptcy risk, earnings management, corporate governance, company size and other variables (including industry and listed date in TSE) to train and test model. We found that the most important variables for predicting auditor opinion are the last year audit opinion, net income to revenue ratio, and debt to assets ratio.
Bagherpour Valashani, M. A., Saie, M. J., Meshkani, A., & Bagheri, M. (2013). Prediction of Independent Auditor Opinion in Iran : Data Mining Approach. Accounting and Auditing Research, 5(19), 134-150. doi: 10.22034/iaar.2013.104540
MLA
Mohammad Ali Bagherpour Valashani; Mohammad Javad Saie; Ali Meshkani; Mostafa Bagheri. "Prediction of Independent Auditor Opinion in Iran : Data Mining Approach". Accounting and Auditing Research, 5, 19, 2013, 134-150. doi: 10.22034/iaar.2013.104540
HARVARD
Bagherpour Valashani, M. A., Saie, M. J., Meshkani, A., Bagheri, M. (2013). 'Prediction of Independent Auditor Opinion in Iran : Data Mining Approach', Accounting and Auditing Research, 5(19), pp. 134-150. doi: 10.22034/iaar.2013.104540
VANCOUVER
Bagherpour Valashani, M. A., Saie, M. J., Meshkani, A., Bagheri, M. Prediction of Independent Auditor Opinion in Iran : Data Mining Approach. Accounting and Auditing Research, 2013; 5(19): 134-150. doi: 10.22034/iaar.2013.104540
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