Indonesia Conference Directory

Abstract This study aims to determine the financial distress prediction model that is most suitable for its application to property and real estate companies in Indonesia. This study compares three financial distress prediction models, namely the Grover, and Ohlson models. Comparison is done by analyzing the accuracy of each model. The data used is in the form of annual financial reports that have been published by the company on the Indonesia Stock Exchange website. The sample used is a property and real estate company that was listed on the IDX during 2013- 2017. The sampling technique was purposive sampling with a total sample of 7 companies. The results of the study show that the Grover model is a prediction model with a high level of accuracy of 100%. Furthermore, Ohlson has the lowest accuracy level of 49% and has an error type of 51%. Therefore an accurate prediction model for property and real estate companies in Indonesia is the Grover model for the period 2013-2017. It is hoped that this research can be a reference to expand the population coverage and research samples on Property and Real Estate companies. Add variables and observation periods for further research.