@article{Indriyanti_2019, title={The Accuracy of Financial Distress Prediction Models: Empirical Study on the World’s 25 Biggest Tech Companies in 2015–2016 Forbes’s Version}, volume={3}, url={https://knepublishing.com/index.php/KnE-Social/article/view/4025}, DOI={10.18502/kss.v3i11.4025}, abstractNote={<p>Every company has the possibility to go bankrupt. Bankruptcy begins with a condition of financial distress. Reliable and accurate models prediction are needed as the early warning system to anticipate financial distress. This research aims to find the predictor model of financial distress that are the most accurate in predicting the condition of financial distress at technology companies. The population of this research is the technology companies that were listed on the World’s 25 Biggest Tech Companies in 2015–2016 Forbes’s version. The total sample of this research was 30 tech company. The data in this research is totaled to 60 annual reports. Determination of the accuracy level was based on the calculation of the correct number of prediction divided by the total data and multiplied by 100%. This study compares seven predictors model of financial distress. The result indicate that if Grover is the most accurate model in predicting financial condition after the year predict. Grover model has an accuracy rate of 96.6%.</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>Keywords: financial distress, bankruptcy, model prediction, accuracy</p&gt;}, number={11}, journal={KnE Social Sciences}, author={Indriyanti, M}, year={2019}, month={Mar.}, pages={442–450} }