Analysis of Financial Distress with Springate and Method of Grover in Coal In BEI 2012-2016

Info Articles ____________________ History Articles: Received 1 January 2018 Accepted 15 March 2018 Published 8 July 2018 ____________________


INTRODUCTION
Boom commodity era of the 2000s resulted in a significant advantage for companies engaged in the export of coal. The increase in commodity prices mostly fueled by economic growth in developing countries. Nevertheless, the favorable situation changed when the global financial crisis in 2008 when commodity prices decline so quickly. Indonesia affected by these external factors for export commodities (especially for coal and palm oil) are responsible for about 50% of Indonesia's total exports, thus limiting the growth of GDP in 2009 to 4.6% (that can be said is still quite good, mainly supported by domestic consumption). In the 2nd half of 2009 until early 2011, global coal prices rebounded sharply. Although like that, the decline in global economic activity has reduced demand for coal, thus causing a decrease in coal prices that start from the beginning of 2011. Global economy crysis that occurred in 2015 give the greatest impact on the company in the field of mining and plantation companies. Even the world's largest private coal PT. Peabody Energy filed for bankruptcy protection in 2014 due to falling prices and demand for coal, which began in 2011. In Indonesia as many as approximately 125 coal mines in Kalimantan is not operating as of August 2015. As a result, 5,000 people affected by layoffs (PHK). Some of coal companies that listed on the Stock Exchange also experienced the same thing seen from minus profit by the company. As for the coal industry is one of the biggest contributors to the state budget are about more than 40 billion each year, so the decline of the coal industry and conditions of each coal company in Indonesia is of particular concern for the government. Therefore it is necessary analysis on the condition of the company -a coal company in Indonesia whether the company in good health condition or in a state of distress.
Previous research in predicting financial distress is Ni Made and Maria (2013) in his research "Predicted bankruptcy with Model Grover, Altman Zscore, Springate, and Zmijewski in Food and Beverage in Indonesia Stock Exchange", the research results are Model Grover is a predictor of bankruptcy most suitable applied to the Food & Beverage companies listed on the Stock Exchange. Evi, Prihanthini and Sari (2013) in his study "Comparing Prediction Method Method Financial Distrees The Variable", the results of research is there is a difference between the models grover denan Altman Z-Score model with springate and models grover grover with Zmijewski models. Grover and the model is the most suitable prediction model is applied to thecompany Food and Beverage because this model has the highest level of accuracy than other models in the amount of 100%, 80% Altman model, the model springate 90%, and by 90% Zmijewski models. Vahdat and Mohammad (2012) in his study "The Creation Of Bankruptcy Prediction Model Using Springate and SAF Models", his research is Springate with MDA provides bankruptcy prediction with accuracy rate of 90% within 1 year prior to bankruptcy, and 82% in the period 2 years. While the SAF models by logistic regression analysis predicting bankruptcy with the accuracy of 88.5% off for a period of 1 year prior to bankruptcy and 79% for a period of 2 yrs before bankruptcy.
There are a variety of analysis tools bankruptcy that have been found, but the bankruptcy analysis tool that is widely used is the analysis of Springate models, and models Grover. The second reason is that analysis tools are widely used for the analysis of both devices have a fairly high level of accuracy in predicting the potential bankruptcy of a company.

METHODS
The population in this study are companies in the coal industry listed on the Stock Exchange in 2012 -2016. The data selection method is purposive sampling and the number of samples contained in this study as many as 18 companies. The data used in this research is secondary data obtained from the official website of the Stock Exchange in the form of annual financial statements (audited) by accessing the website www.idx.co.id.The variables used in this study is a variable in the analysis method Springate and methods Grover, namely: a. Method Springate 1) Working Capital to Total Assets Ratio 2) Earning Power Of Total Investment Ratio 3) Net Profit Before Tax To Current Liabilities Ratio 4) Total Asset Turn Over b. Method Grover 1) Working Capital to Total asset Ratio

2) Earning Power of Total Investment
Ratio 3) Return on assets Secondary data analysis methods were used to analyze the report -compiled financial statements related to the company -the studied company will use the formula for calculating eacheach method

Springate Model
Description: A = working capital / total assets B = net profit before interest and taxes / total assets C = net profit before taxes / current liabilities S = sales / total assets

Grover Model
Description: X 1 = working capital / total assets X 3 = earnings before interest and taxes / total assets ROA = net income / total assets

Analysis Springate method
Model Springate using four financial ratios to predict their potential in a company's financial difficulties. Springate models can be used to predict bankruptcy with keakurat value of 92.5%. If he scores S> 0,862 classified the company is healthy and if the score S <0,862, the company classified as potentially bankrupt. Springate analysis calculation shown in the following Table 3. Springate method was able to predict in 2012 there were 3 companies classified as financial distress and 15 companies classified health. In 2013 there were four companies classified as financial distress and 14 companies classified health. In 2014 there were five companies classified as financial distress and 13 companies classified health. In 2015, there were 7 companies classified as financial distress and 11 companies classified health. In 2016 there were six companies classified as financial distress and 12 companies classified health.
Over the past 5 years in a row -there are two companies that participated row -has declared financial distress from 2012 till 2016, namely Atlas Resources and Bumi Resources. In this method, the smaller the value S score the worse the condition of the company, both companies are experiencing financial distress respectively -helped by the condition has a value of working capital and net profit before tax certainly has a negative value. A ratio of working capital to total assets and C net profit before tax to current liabilities ratio also has a negative value. This shows that at the time the company had working capital and a small profit before tax would cause the company to experience financial distress based on the calculation formula Springate.

Analysis Grover Model
Grover Model categorizes companies into insolvency if it obtained a score of less than or equal to -0.02 (-0.02 Z) and the company is said to have the potential bankrupt if obtained a score greater than or equal to 0.01 (Z 0, 01). Grover analysis calculations are shown in the following Table 4. Over the past 5 years in a row -succession there are companies that respectively -has declared financial distress from years 2012 to 2016. In this method, the smaller the value of X score the worse the condition of the company, from several companies experiencing financial distress in each year have conditions definitely worth the value of negative net income. The ratio of return on assets also have a negative value. This shows that when the company has a return on assets of small value will cause the company to experience financial distress based on the calculation formula grover.

Springate Model
From the comparison between the methods of prediction with the status of the sample companies using Springate, the results are as follows: Based on the analysis performed on eighteen company Springate method has an accuracy rate of 67%. From table 4.9, the accuracy of prediction methods springate can be seen from the 12 companies that precise predictions, predictions springate account for 12 companies predict healthy and in fact did not experience delisting. For the results of error rates, springate method has an error rate of 33%, this figure can be seen from the 6 companies that predictions are not precise. Springate prediction takes into account 6 companies predicted distress or bankruptcy, and there is in fact the company is not experiencing delisting.

Grover Model
From the comparison between the methods of prediction with the status of the sample companies using Grover in Table 7. based on analysis done at eighteen companies Grover method has an accuracy rate of 78%. From table 4.12 Grover accuracy of prediction methods can be seen from the 14 companies that prediction is right, Grover prediction takes into account 14 companies predict healthy and in fact did not experience delisting. For the results of error rates, methods Grover had an error rate of 22%, this figure can be seen from the four companies that predictions are not precise. Grover predictions take into account the four companies predicted distress or bankruptcy, and there is in fact the company is not experiencing delisting. The table can be seen comparing the results of the analysis using method Springate and Grover on coal company in Indonesia Stock Exchange. The highest accuracy grades are occupied by Grover method to value accuracy rate of 78% and an error rate of 22%, and the second position is occupied by Springate method to value accuracy rate of 67% and an error rate of 33%. This shows that the method of Grover is the most accurate method for analyzing financial distress. This is consistent with research Ni Made and Maria (2013) in his research "Predicted bankruptcy with Model Grover, Altman Zscore, Springate, and Zmijewski in Food and Beverage in Indonesia Stock Exchange", the research results are Model Grover is a predictor of bankruptcy that best suits applied to the Food & Beverage companies listed on the Stock Exchange. Evi, Prihanthini and Sari (2013) in his study "Comparing Prediction Method Method Financial Distrees The Variable", the results of research is there is a difference between the models grover denan Altman Z-Score model with springate and models grover grover with Zmijewski models. Grover and the model is the most suitable prediction model is applied to thecompany Food and Beverage because this model has the highest level of accuracy than other models in the amount of 100%, 80% Altman model, the model springate 90%, and by 90% Zmijewski models.

CONCLUSIONS
Springate method was able to predict in 2012 there were 3 companies classified as financial distress and 15 companies classified health. In 2013 there were four companies classified as financial distress and 14 companies classified health. In 2014 there were five companies classified as financial distress and 13 companies classified health. In 2015, there were 7 companies classified as financial distress and 11 companies classified health. In 2016 there were six companies classified as financial distress and 12 companies classified health.
Grover method was able to predict in 2012 there were four companies classified as financial distress and 14 companies classified health. In 2013 there were 3 companies classified as financial distress and 15 companies classified health. In 2014 there were 3 companies classified as financial distress and 15 companies classified health. In 2015 there were four companies classified as financial distress and 14 companies classified health. In 2016 there were two companies classified as financial distress and 16 companies classified health.
Grover method is the most accurate method for predicting financial distress in the coal company with a value of 78% accuracy rate and an error rate of 22%, in the second position is occupied by Springate method to value accuracy rate of 67% and an error rate of 33%.
For management, may consider the results of the calculation method of Grover to minimize or avoid the risk of financial distress and forced the company delisted from the Indonesian Stock Exchange. For investors, may consider the use of calculations and financial ratios in Grover method to predict the likelihood of listed coal companies would have forced delisting, so that investors can make informed decisions in investing through the Indonesia Stock Exchange.