scholarly journals ANALISIS KESESUAIAN PREDIKSI KEBANGKRUTAN MODEL ALTMAN Z-SCORE, FULMER DAN SPRINGATE TERHADAP OPINI AUDITOR PADA PERUSAHAAN DELISTINGTAHUN 2015

IKONOMIKA ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 144
Author(s):  
Anissa Agustina Rahmadini
Keyword(s):  
Stock Exchange ◽  
Financial Statements ◽  
Descriptive Study ◽  
Bankruptcy Prediction ◽  
Financial Data ◽  
Z Score ◽  
Gray Area ◽  
Level Of Agreement

Abstract-This research aims at bankruptcy prediction in PT. Bank Ekonomi Raharja which delisted from The Indonesia Stock Exchange and determine the level of suitability of these predictions with the auditor's opinion on the financial statements. This research is a descriptive study with a sample of companies that delisting from the stock exchange in 2015. Based on processing and analysis of financial data year 2011-2015 results obtained from three models of bankruptcy prediction Springate and Fulmer predicted PT. Bank Ekonomi Raharja went bankrupt during that period, while the method of Altman predicts PT. Bank Ekonomi Raharja are in the category of "gray area". In addition the level of agreement between the predictions of bankruptcy by the auditor's opinion is only 20%, this corresponds to the condition that the company is still operating despite at delisted from the stock exchange.

ANALISIS PREDIKSI KEBANGKRUTAN DAN HARGA SAHAM PADA PERUSAHAAN PERTAMBANGAN BATU BARA

2016 ◽  
Vol 12 (2) ◽  
pp. 141
Author(s):  
Augustpaosa Nariman
Keyword(s):  
Coal Mining ◽  
Stock Price ◽  
Stock Exchange ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Mining Company ◽  
Mining Companies ◽  
Gray Area ◽  
Analysis Technique

This study aims to examine and analyze the bankruptcy prediction on coal mining company listed onthe Indonesia Stock Exchange. Bankruptcy prediction on coal mining companies using the Altman ZScore to see how big a bankruptcy prediction coal mining company. The data used in this study arethe financial statements of coal mining companies that are in the period 2012-2014 on the IndonesiaStock Exchange. The analysis technique used is a bankruptcy prediction model Altman Z-Score usingfive variables representing liquidity ratios, profitability ratio, and activity ratio. During theobservation period of 2012-2014 shows that the research data as many as 19 coal mining companiesthere are in a state of bankruptcy. In 2012 and 2013 there were 31.6% of companies experiencingbankruptcy prediction, and 26.32% are in the gray area. 2014 showed an increase where there are42.10% of companies experiencing bankruptcy prediction and 5.26% in the gray area..Keywords: Altman Z-Score, Predicted Bankruptcy, Stock price

scholarly journals ANALISIS PREDIKSI KEPAILITAN PADA BANK UMUM SWASTA NASIONAL DEVISA YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2010 – 2013

2018 ◽  
Vol 4 (1) ◽  
pp. 93
Author(s):  
Sumaniyatun Fadhilah ◽  
Indah Kurniawati
Keyword(s):  
Commercial Bank ◽  
Foreign Exchange ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Working Capital ◽  
Purposive Sampling ◽  
Gray Area ◽  
Private Banks

The purpose of this study is to assess bankruptcy prediction in the National Private Banks Foreign Exchange listed in Indonesian Stock Exchange. This study uses the size of liquidity ratio of working capital to total assets. This study uses the find were the purposive sampling. The population in this study is the National Private Commercial Bank Foreign Exchange listed on the Indonesian Stock Exchange during the period of the study, namely between 2010 until 2013. The sample amounted to 21 banks during the 4 years that have been selected based on specific criteria. Based on the results of the analysis carried out stating that the National Private Commercial Bank Foreign Exchange listed in Indonesian Stock Exchange in 2010 there were 29 % of banks that are insolvent, 71 % of banks that are in the gray area, and no banks that are in not bankruptcy predictions. In 2011 29 % of banks that are insolvent, 67 % of banks that are in the gray area and 5 % are located on the banks not bankruptcy prediction. In 2012 29 % of banks that are insolvent, 67 % of banks that are in the gray area, and 5 % of banks that are in the prediction of the bank is not bankrup. In 2013 29 % of banks that are in bankruptcy prediction, 71 % of banks that are in the gray area, and there are no banks that are in not bankruptcy predictions. There is no difference in Z-score on bankruptcy prediction National Private Banks Foreign Exchange Listed in Indonesian Stock Exchange between 2010, 2011, 2012, and 2013.

scholarly journals BANKRUPTCY PREDICTION OF THE COMPANY USING ALTMAN Z–SCORE METHOD FOR THE CONVENTIONAL BANKS REGISTERED IN THE INDONESIA STOCKS EXCHANGE (BEI)

2017 ◽  
Vol 2 (02) ◽  
pp. 11
Author(s):  
Irwansyah .
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Gray Area ◽  
Analysis Technique ◽  
Score Analysis ◽  
Score Method ◽  
Score Model ◽  
Conventional Banks

This study was conducted to prove the accuracy of bankruptcy prediction of Altman Z-Score model on conventional banks listed on the Indonesia Stock Exchange. The data used in this study is secondary data obtained from the annual financial statements of conventional banks during the period of 2013-2016 mentioned on the official website of the Indonesia Stock Exchange. The data analysis technique used is bankruptcy prediction of Altman Z-Score model, using five variables representing liquidity ratios X1, profitability ratios X2 and X3, and activity ratios X4 and X5. The formula Z-score = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + X5. When Z-Score criteria is Z > 2.90 it is categorized as a healthy company. Z-Score between 1.23 to 2.90 is categorized as a company in area. While Z-Score Z < 1.23 is categorized as a potential bankrupt company. Based on the results of the research, Z-Score analysis that has been done in the period of 2013-2016 indicating that most conventional banks are predicted bankrupt. The lowest score of the Z-Score is 1.23. Only one Bank Jtrust Indonesia Tbk (BCIC bank code) is in a healthy category. Bank Mandiri (Persero) Tbk with BMRI bank code, has been increasing from the prediction of bankruptcy category to the prediction of gray area category.Keywords: Altman Z-Score, Conventional Banks Listed on BEI 2013-2016, Prediction of Bankruptcy.

scholarly journals Application of Altman Modified Z-Score to Predict Financial Distress in the Indonesian Telecommunications Industry

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Rianti Fifriani ◽  
Perdana Wahyu Santosa
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Financial Statements ◽  
Telecommunications Industry ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Purposive Sampling ◽  
Modification Method ◽  
The Future ◽  
The Right

Bankruptcy prediction is needed to assess the prospect of going concern and sustainability of the corporations in the future. This study aims to predict the bankruptcy of corporates with the Altman Z-Score Modification model in the telecommunications industry in Indonesia. The data used are the financial statements of the telecommunications industry that listing on the Indonesia Stock Exchange for the period 2011-2015. Samples for this study uses purposive sampling according to company criteria. The results of the study using the Altman Z-score modification method found two potentially bankrupt companies, namely Bakrie Telecom, Tbk, and Smartfren, Tbk. While Indosat, Tbk, and XL Axiata, Tbk have high financial distress potential due to liquidity and profitability problems that tend to weaken. Meanwhile, Telkom Indonesia, Tbk, and Infracom Inovisi financial concessions are relatively healthy and have the right business expectations

scholarly journals Analisis Potensi Kebangkrutan: Perbandingan Model Altman dengan Zavgren

PERSPEKTIF ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 447-452
Author(s):  
Wardayani Wardayani ◽  
Azhar Maksum
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Identification Problem ◽  
Bankruptcy Prediction ◽  
Logit Analysis ◽  
Z Score ◽  
Gray Area ◽  
Financial Difficulties ◽  
Score Model ◽  
Analysis Models

This study is aimed to compare two methods to determine the potential for bankruptcy of the company. The method used is the Altman (Z Score) and Zavgren (Logit Analysis) models. The Z Score model is a method to predict the financial difficulties, where the score value on the Altman Z Score classifies whether a company being bankrupt or not. Zavgren developed bankruptcy prediction model with Logit Analysis which divide bankruptcy classifications. The identification problem in this research are the decline in profits occurred from the end of 2016 until 2018, and the mismatch of the increase in profits to the increase the number of assets in the Cosmetics Company, through the use of secondary data from the Indonesia Stock Exchange of companies with code MRAT, KINO, TCID, dan MBTO. Thus, the financial state of cosmetics companies listed on the Indonesia Stock Exchange (BEI) during the 2016 to2018, according to the Altman Z Score model can be categorized into 2 criteria, they are: Gray Area; MBTO and Sound Area: MRAT, KINO and TCID. Meanwhile, based on the Zavgren model, MRAT, KINO, TCID and MBTO were declared as Sound.

ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z- SCORE DAN ZMIJEWSKI PADA PERUSAHAAN KOSMETIK YANG TERDAFTAR DI BURSA EFEK INDONESIA

2020 ◽  
Vol 5 (1) ◽  
pp. 24-33
Author(s):  
Dewi Oktary
Keyword(s):  
Quantitative Data ◽  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
The Other ◽  
Z Score ◽  
Gray Area ◽  
Score Method ◽  
Data Source ◽  
Score Model

Increasingly intense competition in the cosmetics industry in Indonesia, one of which is the number of artists opening a cosmetics business and besides the entry of many cosmetics brands from abroad which makes existing cosmetic companies must be careful in running their business. This study aims to predict the bankruptcy of cosmetics companies listed on the Indonesia Stock Exchange with the Altman Z-Score model and the Zmijewski model. The sample in this study was cosmetic companies listed on the Main Board of the Indonesia Stock Exchange as many as 4 companies. The data source used is secondary data taking data from the IDX, the type of data used is quantitative data. The result of this research is bankruptcy prediction using the Altman-Z Score method showing that PT. Martino Berto, Tbk for 2016 is included in the Gray Area category while in 2017-2018 it is predicted to go bankrupt while for PT. Mustika Ratu, in 2016 - 2018 entered the Gray Area category while the other two companies namely PT. Mandom Indonesia, Tbk and PT. Unilever, Tbk from 2016 to 2018 is predicted not to go bankrupt. Meanwhile, using the Zmijewski method in cosmetics companies listed on the Indonesia Stock Exchange in the period 2016-2018 is predicted not to go bankrupt. From the comparison between the Altman Z-Score model and the Zmijewski model, the Zmijewski model has an effectiveness of 100% compared to the Altman Z-Score model which has an effectiveness level of 50%.

scholarly journals ANALISIS PREDIKSI KEBANGKRUTAN BERDASARKAN METODE ALTMAN Z-SCORE (STUDI KASUS PADA BANK BUMN YANG TERDAFTAR DI BEI)

2019 ◽  
pp. 191
Author(s):  
I Komang Try Satriawan Korry ◽  
Made Pratiwi Dewi ◽  
Ni Luh Anik Puspa Ningsih
Keyword(s):  
Financial Distress ◽  
Deposit Insurance ◽  
Stock Exchange ◽  
Descriptive Analysis ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Gray Area ◽  
Analysis Technique ◽  
Score Method

Abstract: Bankruptcy Prediction Analysis Based on the Altman Z-Score Method (Case Study ofState-Owned Banks Registered on the IDX). Bankruptcy phenomena can occur in every company.Based on data from the Deposit Insurance Agency (LPS), there were 90 banks liquidated since 2005 until mid-2018. Based on the phenomenon of bankruptcy that occurred, it was important for banks to be no exception for state-owned banks to recognize the symptoms of financial distress thatled to bankruptcy. The purpose of this study was to determine the prediction of bankruptcy basedon the Altman Z-Score method on state-owned banks listed on the Indonesia Stock Exchange (IDX).The data analysis technique used in this study is descriptive analysis techniques. The sample inthis study used four state-owned banks, namely Bank Negara Indonesia, Bank Rakyat Indonesia,Bank Tabungan Nasional, and Bank Mandiri with the technique of determining saturated samplingsamples and the data used were financial statements for the 2014-2017 period obtained throughofficial IDX sites (www.idx.co.id). The results of the study show that all state-owned banks are inthe gray area for the period of 2014-2017 because the value of the Z-score obtained is between 1.1and 2.6.

PREDIKSI TINGKAT KEBANGKRUTAN PERUSAHAAN PERTAMBANGAN BATU BARA YANG TERDAFTAR Di BURSA EFEK INDONESIA TAHUN 2014-2015

2017 ◽  
Vol 1 (2) ◽  
pp. 156-173
Author(s):  
Erwita Dewi
Keyword(s):  
Coal Mining ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
T Test ◽  
Z Score ◽  
Model Classification ◽  
Gray Area ◽  
The Difference ◽  
A Company ◽  
Altman Model

This study aims to determine the financial statements prior to the bankruptcy can be used to predict the rate of bankruptcy with Altman Model and Foster on coal mining company listed on the Indonesia Stock Exchange. Model classification Altman Z score Z score> 2.90 is classified as a healthy company, while the company has a Z score <1.20 were classified as potentially bankrupt company. Furthermore, scores between 1.20 to 2.90 is classified as a company in the gray area or the gray area. While the Model Z score Foster use the "Cut-off Point" Z = 0.640, so companies that have Z < 0.640 belongs to a group of companies that go bankrupt, while if Z > 0.640 included in the group of companies that are not bankrupt. After that tested the difference between the predicted results using independent samples t test. The results of the analysis of financial ratios and Foster Altman model proved capable of predicting corporate bankruptcies coal mining sector in Indonesia Stock Exchange in 2014-2015. Results Zscore Altman bankruptcy prediction for the year 2014-2015 shows an increase in predictive companies entering bankrupt category. In 2014 by 22% (there are four companies that PT.BUMI Resources Tbk, PT.Darma Henwa Tbk, PT.Delta Dunia Makmur Tbk and PT.Perdana Karya Perkasa Tbk), and in 2015 by 44% (there are eight companies, namely       PT. Adaro Energy Tbk, PT.Atlas Resources Tbk, PT. Bumi Resources Tbk, PT. Darma Henwa Tbk, PT. Delta Dunia Makmur Tbk, PT.Perdana Karya Perkasa Tbk, PT.Petrosea and  PT. Golden Eagle Energy Tbk). Foster Zscore bankruptcy prediction results for the year 2014-2015 shows that there is consistency predictive companies entering bankrupt category. Year 2014-2015 by 28% (there are five companies that PT.Atlas Resources Tbk, PT.Baramulti Sukses sarana Tbk, PT. Bayan Resources Tbk, PT. Darma Henwa Tbk and PT. Perdana Karya Perkasa Tbk). Both models are Zscore Altman bankruptcy prediction and Zscore Foster in this study proved to be no different in corporate bankruptcy prediction results were proved by analysis of independent sample t test.

scholarly journals ANALISIS ALTMAN Z-SCORE, GROVER SCORE, SPRINGATE, DAN ZMIJEWSKI SEBAGAI SIGNALING FINANCIAL DISTRESS (Studi Empiris Industri Barang-Barang Konsumsi di Indonesia)

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Niken Savitri Primasari
Keyword(s):  
Prediction Model ◽  
Financial Distress ◽  
Stock Exchange ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
T Test ◽  
Z Score ◽  
F Test ◽  
Company Sector ◽  
Altman Model

This study purpose to determine whether there are differences among Altman model, Springate model and Zmijewski model to predict financial distress, and to find out which the Financial Distress prediction model has the most excellent implementation in Indonesia manufacture industry. Comparison of those six models were made by analyzing the accuracy of each model, by using the real condition of a company’s net income. The data used in the form of annual financial statements published by the company on the Indonesia Stock Exchange website. The sample in this study consisted of 116 financial data from 29 companies in Consumer Goods Industry. All companies are listed in Indonesia Stock Exchange Market at period 2012 - 2015. The company does not conclude yet, whether there is a prediction model that best suit the measurement. This cause by: (1) every model have its own superiority and weakness, (2) the company sample characteristic differences (company sector, company size) also influence the choice of prediction model being used, (3) the company financial ratio as independent variable used in bankruptcy prediction. Since the financial statements are reflecting the company’s financial ability of the signaling, the researchers limited the industry with the highest value of EPS and PER. This is done to avoid confounders in the proof of the accuracy of the model, Springate model, Ohlson model and Zmijewski model to predict financial distress. The data obtained from the Annual Financial Statements, IDX Fact Book and the Indonesian Capital Market Directory. In this study will be used t test, additional testing is done to see the feasibility of the model by observing the F test results and test the coefficient of determination (R2), R2 value used to examine differences among Altman, Grover, Springate and Zmijewski models in predicting financial distress. The analytical tool used is the One Way ANOVA with level of significance 5 %. The results from this research showed that any prediction model used in this study can be used to predict Financial Distress, particularly the Altman Z-Scores, which have the greater R2 analysis. Only Grover G-Score models have insignificant value t test and F-test is greater than the probability cannot be used to predict corporate Financial Distress. The results also showed that the most accurate model is the model Altman Z-Score. At the end of the study was to try predict 29 firms sample used listed on the Stock Exchange with Altman model. Predicted results showed that five companies are expected to experience Financial Distress in the future.

scholarly journals RISIKO PERBANKAN DENGAN ALTMAN Z SCORE : KAJIAN PADA BANK YANG TERDAFTAR DI BURSA EFEK INDONESIA

2018 ◽  
Vol 13 (1) ◽  
pp. 1-10
Author(s):  
Poppie Indriyanti
Keyword(s):  
Quantitative Research ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Research Approach ◽  
Z Score ◽  
Gray Area ◽  
Banking Risk ◽  
Conventional Banks ◽  
Value Model

Abstract. This research was conducted to find out banking risk with Altman Z Score on conventional banks listed on Indonesia Stock Exchange. The data used in this study is secondary data obtained from the annual financial statements of conventional banks during the period 2003-2016 contained in the official website of the Indonesia Stock Exchange.The focus of research (research focuses) on the topic that has been studied is the risk of banking based on Altman Z Score. Of the four studies examined, the equation is all research using quantitative research approach. It means to assess the Altman Z-Score in observing banking risk, the quantitative approach is the most appropriate approach.Of the four studies, the results show banking risk with Altman Z Score, from 2003-2016 the banks listed on the Indonesia Stock Exchange are generally in the category of bankrupt. However, Ganesha et al (2012) study shows the Z value model in 2003-2006 can not show a good enough accuracy level when measured per year. Irwansyah's research (2017) shows that in the period 2013-2016, only one bank, namely Bank Jtrust Indonesia Tbk (BCIC bank code) entered into the healthy category. In addition, Bank Mandiri (Persero) Tbk with BMRI bank code, has started to increase from the predicted category of bankruptcy to the prediction of gray area category.

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