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 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

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 Laporan Keuangan dan Prediksi Kebangkrutan Perusahaan

2020 ◽  
Vol 5 (1) ◽  
pp. 196
Author(s):  
Putu Riesty Masdiantini ◽  
Ni Made Sindy Warasniasih
Keyword(s):  
Data Analysis ◽  
Prediction Model ◽  
Prediction Models ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Analysis Techniques ◽  
Accuracy Level ◽  
Altman Model

This study aims to determine differences in bankruptcy predictions at company’s sub-sector of cosmetics and household listed on the Indonesia Stock Exchange (IDX) using the Altman model, Springate model, Zmijewski model, Taffler model, and Fulmer model, and to determine the bankruptcy prediction model that is the most accurate of the five bankruptcy prediction models. This study uses secondary data in the form of company financial statements for the period 2014-2018. Data analysis techniques in this study used the Kruskal-Wallis test. The results showed there were differences in bankruptcy predictions using the Altman model, Springate model, Zmijewski model, Taffler model, and Fulmer model. The Zmijewski, Taffler, and Fulmer models have the same accuracy level of 100% so that the three prediction models are the most accurate prediction models for predicting the potential bankruptcy at companies sub-sector of cosmetics and household listed on the IDX.

scholarly journals Analysis of The Bankruptcy of Companies with Altman Model and Ohlson Model

2020 ◽  
Vol 9 (3) ◽  
pp. 243-251
Author(s):  
Andi Septian Najib ◽  
Dwi Cahyaningdyah
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Sampling Method ◽  
Prediction Models ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Processing Application ◽  
Ohlson Model ◽  
Altman Model

Often companies that have been operating for a certain period forced to disperse because of increased financial distress that caused bankruptcy. There are two models that can be used to predict bankruptcy of companies, that is Altman model (Z-score) and Ohlson model. This study aims to determine the accuracy of the Altman model (Z-Score) and Ohlson's model in predicting bankruptcy of delisting companies in Indonesia Stock Exchange for 2015-2019 period.The population in this study were all of delisting companies in Indonesia Stock Exchange for 2015-2019 period, totaled 17 companies. The number of samples used in this study were 8 companies, by using purposive sampling method. Data analysis used data processing application SPSS version 25. The results showed that accuracy of the Altman model is 58.3%, while the Ohlson model is 79.2%. The conclusion of this research Ohlson model has the highest accuracy that compared to Altman model in predicting bankruptcy at delisting companies in Indonesia Stock Exchange for 2015-2019 period, with accuracy values of Ohlson model is 79.2% and 58.3% for the Altman model. For further researchers, it is expected to increase the number of samples of companies studied and extend the research periods in order to provides more accurate results, and combining the Altman and Ohlson models with other bankruptcy prediction models that can be applied in companies in Indonesia.

scholarly journals ANALISIS FINANCIAL DISTRESS DENGAN MENGGUNAKAN BANKRUPTCY PREDICTION MODELS PADA EMITEN ROKOK PERIODE 2014-2018

2021 ◽  
Vol 4 (1) ◽  
pp. 16-27
Author(s):  
Ani Wahyuningsih ◽  
Hartono Hartono ◽  
Rini Armin
Keyword(s):  
Early Warning ◽  
Financial Distress ◽  
Prediction Models ◽  
Stock Exchange ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Correct Prediction ◽  
Financial Health ◽  
Z Score ◽  
Financial Difficulties

ABSTRACT Financial Distress is a condition of financial difficulties where if this happens to the company foa along period of time, the company is in the initial stages before bankruptcy. Bankruptcy is a state of being or a situation in which company failed to or not able to meet obligations because firm experienced lack of. If the company goes bankrupt there will be many parties who are harmed. Therefore it is necessary to conduct financial distress analysis for early warning. The research aims to determine the financial health of the cigarette sub-sector companies by analyzing financial distress using three bankruptcy prediction models with Altman Z-Score, Springate, Grover and to determine which of these three models has the highest level of accuracy. The data used in this research is the company’s financial statements published on the Indonesia Stock Exchange website. The population in this research is the cigarette sub-sector companies listed on the Indonesia Stock Exchange in the 2014-2018 period. Based on the result of research shows that in the calculation Altman and Springate models, PT. Bentoel International Investama in the category of the company experiencing symptoms of bankruptcy. While in the Grover model calculation, all companies fall into category healthy companies. Of the three models that have the highest level of accuracy are Altman and Springate models by one hundred percent. This shows that Altman and Springate models have the correct prediction of the company correctly.

scholarly journals Analisis Perbandingan Model Prediksi Kebangkrutan Altman Z-Score dan Zmijewski di BEI Periode 2011 - 2015

2019 ◽  
Vol 6 (2) ◽  
pp. 171
Author(s):  
Nindya Ayu Damayanti ◽  
N. Nurhayati ◽  
Susanti Prasetyaningtyas
Keyword(s):  
Data Analysis ◽  
Prediction Model ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Financial Ratios ◽  
Z Score ◽  
Study Population ◽  
A Company

This study aimed to compare the use of bankruptcy prediction model Altman Z-Score and Zmijewski on delisting companies on the Stock Exchange the period 2011 - 2015. The study population is a company delisting from the Stock Exchange in the period 2011-2015. The sample consists of 7 companies using method. purposive sampling Secondary data used in the form of financial statements of companies that issued from stock for bankruptcy in the period 2011-2015. The data analysis in this research is to perform the calculation of financial ratios in each sample, according to the variables of bankruptcy prediction model were compared to the model of Altman Z-Score and Zmijewski. Furthermore, the company classifies conditions appropriate point cut-off of each model and did calculations the accuracy of each model. Keywords: Altman Z-Score, Delisting, Bankruptcy, Zmijewski.

FINANCIAL DISTRESS PREDICTION AND SEEING THE INFLUENCE OF THE ALTMAN RATIO ON COMPANY FINANCIAL DISTRESS

2018 ◽  
Vol 23 (3) ◽  
pp. 236-243
Author(s):  
Hadhi Dharmaputra Juliyan ◽  
Bertilia Lina Kusrina
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Large Role ◽  
Corporate Bankruptcy ◽  
Mining Companies ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Score Model

This research aims to determine the level of the bankruptcy of the company and to see if the Altman ratio can predict the condition of corporate bankruptcy in mining companies on the Indonesia Stock Exchange because mining companies have a large role in the Indonesian economy. This study uses the Altman Z-Score model analysis to see how much the company's bankruptcy prediction and uses logistic regression to see how much the influence of the Altman ratio in predicting corporate bankruptcy. Keywords: financial distress, the Altman z–score, bankruptcy prediction

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.

scholarly journals Using Beneish M-Score and Altman Z-Score models to detect financial fraud and company failure

2021 ◽  
Vol 69 (4) ◽  
pp. 20-29
Author(s):  
Snežana Knežević ◽  
Marko Špiler ◽  
Marko Milašinović ◽  
Aleksandra Mitrović ◽  
Stefan Milojević ◽  
...  
Keyword(s):  
Financial Reporting ◽  
Financial Distress ◽  
Stock Exchange ◽  
Financial Statements ◽  
Z Score ◽  
Fraudulent Financial Reporting ◽  
Financial Decisions ◽  
Score Model ◽  
A Company

Bankruptcy is a risk that any company can face, regardless of its size. The importance of predicting a company's bankruptcy for years before its development is enormous, and it is important for financial sustainability. Financial reporting is an important platform for making financial decisions of investors and creditors. In recent years, the frequency of false financial reporting by firms has increased and there are concerns about investors' confidence in capital market. Academics and industry experts adopt a variety of risk management techniques to detect fraudulent financial reporting. A case study was applied in this paper. Based on publicly available financial data (disclosed financial statements) of a domestic textile company for the period 2017-2020, whose shares are listed on the stock exchange, a survey was conducted based on the application of Altman's Z-Score model and Beneish M-Score model. Financial distress is an important criterion to monitor when assessing the likelihood of fraud reporting. When a company is operating poorly, there is a greater motivation to engage in fraudulent financial reporting. The findings show that the results differ according to the applied method in terms of identifying the possibility of bankruptcy and the possibility of fraud in the financial statements of the observed company. The results of the study can be important to investors, auditors, regulators, bankers, tax and other government bodies.

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.

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