scholarly journals Analisis Perbandingan Model Kesulitan Keuangan Studi Pada Bank Bukopin Tbk

2021 ◽  
Vol 31 (6) ◽  
pp. 1541
Author(s):  
Hisky Ryan Kawulur
Keyword(s):  
Data Analysis ◽  
Predictive Value ◽  
Financial Distress ◽  
Research Method ◽  
Financial Statements ◽  
Z Score ◽  
Comparison Model ◽  
To Come ◽  
Score Model

The purpose of this study is to analyze and compare the predictive value of the Altman z-score model of financial distress with the Zmijewski model. The research method used is descriptive quantitative in explaining the phenomena that occur. This study uses data from Bukopin's financial statements for 2018, 2019 and 2020. Data analysis is carried out by calculating the ratio of each model from 2018, 2019 and 2020, then the results of the criteria from the altman z-score model and the zmijewski model are compared and analyzed according to the criteria. The results showed that both the Altman z-score model and the Zmijewski model gave the same results, namely in the years to come the company has the potential to face bankruptcy. Keywords: Altman Z-Score; Zmijewski; Banking; Comparison Model.

scholarly journals Analisis Penilaian Financial Distress Dengan Menggunakan Model Altman Z-Score Dan Model Springate Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia Periode Tahun 2015-2019

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Febriana Anindyka ◽  
Makhmud Zulkifli
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Descriptive Statistics ◽  
Z Score ◽  
Financial Condition ◽  
Similarities And Differences ◽  
The Difference ◽  
Score Model ◽  
A Company ◽  
Data Analysis Methods

The aim of this research to analyze financial distress of Manufature Company by using Altman Z-Score and Springate Models. Moreover, this research aimed to know aims to determine the similarities and differences in the results of the analysis of financial distress assessment using the Altman Z-Score model and the Springate Model. This research used Descriptive statistics and data analysis methods used  in this research were Altman Z-Score and Springate Model. To the finding on the research, it showed that (1) ) After evaluating the Altman Z-Score and Springate models, there are fifty companies that fall into different conditions. (2) The similarities and differences in the results of the Atman Z-Score model and the Springate model are the results of the two models that can be seen from having almost the same variable components and the difference is that the results of the financial distress assessment using the Altman Z-score model and the Springate model show that both These models have different criteria in determining the financial condition of a company.

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 Altman Z-Core pada Perusahaan Manufaktur Sub Sektor Otomotif yang Terdaftar di Bursa Efek Indonesia

2012 ◽  
Vol 13 (2) ◽  
pp. 135-148
Author(s):  
Andreas Suhendi ◽  
Keyword(s):  
Financial Distress ◽  
Research Method ◽  
Stock Exchange ◽  
Ratio Method ◽  
Manufacturing Companies ◽  
Z Score ◽  
Financial Ratio ◽  
Analysis Techniques ◽  
Score Model ◽  
Descriptive Method

This research aims to know the financial performance of companies with the Altman Z-Score Model in the Automotive Sub-Sector Manufacturing Companies Listed on the Indonesia Stock Exchange in 2016-2018. The research method used in this study is a descriptive method with data analysis techniques using the financial ratio method. The results showed that PT. Astra International Tbk, PT. Astra Otoparts Tbk, PT. Gajah Tunggal Tbk and PT. Indospring Tbk is safe from the threat of bankruptcy, while the highest average Z-Score is achieved by PT Selamat Sempurna Tbk and the lowest average Z-Score is achieved by PT Indomobil Sukses International Tbk. Thus, the Company is expected to maintain company liquidity, restructure debt, minimize receivables, increase profit levels and maximize marketing in order to increase sales so that the potential for financial distress in the company can be minimized.

scholarly journals Aplikasi Data Mining Pada Analisis Financial Distress Model Altman z-score Untuk Memprediksi Potensi Kebrangkutan Pada Industri Properti Go-Public Di Indonesia

Jurnal INFORM ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Billy Montolalu
Keyword(s):  
Financial Distress ◽  
Financial Management ◽  
Financial Statements ◽  
Gray Zone ◽  
Z Score ◽  
Financial Ratio ◽  
Financial Report ◽  
Industrial Operations ◽  
Report Data ◽  
Score Model

Early thought systems are needed in companies to overcome financial difficulties that can challenge industrial operations. Altman Z Score is one model that can be used to predict financial distress in a company by analyzing the company's financial statements. This research was conducted to analyze financial distress in property companies going public using the Altman Z Score model. In this model there are 5 financial ratio indicators that are used to predict financial distress. The financial report data used is the financial statements for 2015-2016 and there are 23 companies. The results of these calculations are then clustered with Fuzzy C-Means in two, namely safe zone and gray zone. Cluster validation testing uses the Silhouetee Index with a validation value of 0.9541 which indicates that the cluster process is valid. The results of this study indicate that there is one company that is included in the cluster gray zone, namely Intiland Development Tbk. Analysis of financial ratios found that the most influential is the variable X3 where the results of profits before tax are very small can affect payment of obligations. So it's easy to bring up financial distress conditions. And for those companies that have been in the gray zone condition, they are expected to be careful in financial management to anticipate financial distress.

scholarly journals Analisis Kebangkrutan dengan Model Altman Z-Score pada Perusahaan Sektor Industri Dasar dan Kimia di Bei Periode 2013-2014

2017 ◽  
Vol 26 (01) ◽  
pp. 136-163
Author(s):  
Suci Kurniawati
Keyword(s):  
Financial Distress ◽  
Quantitative Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Z Score ◽  
Manufacturing Company ◽  
Score Model ◽  
Score Index

 The purpose of this study is to analyze the company's financial distress on basis industry and chemical sectors as many as 57 companies using the ALTMAN Z-Score model in 2013-2014. The data which used was secondary data, such as Financial Statements of manufacturing company publication issued by Indonesian Stock Exchange (BEI) and obtained by downloading the website: www.idx.com. This study uses descriptive quantitative method. The finding of Z-Score index in basis industry and chemical sector in 2013 is occupied by PT. Intan Wijaya Internasional Tbk on chemical subsector and 2014 is occupied by PT. Alakasa Industrindo Tbk on metal subsector and others, with the first highest rank and healthy condition, whereas the last and lowest rank on wood and processing sector  in 2013-2014 is PT. SLJ Global Tbk, with having financial distress condition. The findings of this study are not consistent or even  in accordance with the reality which shows that the Altman method can not be used as a tool to indicate a tendency towards company’s financial distress.

scholarly journals KETEPATAN MODEL PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN RETAIL DI INDONESIA

2019 ◽  
Vol 4 (2) ◽  
pp. 117-127
Author(s):  
Kartikasari Kartikasari ◽  
Diyah Santi Hariyani
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Inferential Statistics ◽  
Accuracy Rate ◽  
Data Analysis Technique ◽  
Analysis Technique ◽  
Score Model

Abstract This study aims to analyze the condition of Financial Distress in retail companies listed on the Indonesian Stock Exchange in 2015-2017 using the Ohlson Model, Fulmer Model, CA-Score Model and Zavgren Model. The data used in this study was secondary data derived from the financial statements of retail companies found on the Indonesian Stock Exchange. The data analysis technique used was inferential statistics and Kruskal-Wallis test. The results of this study indicated that Ohlson's model is best at predicting Financial Distress in retail companies in Indonesia with an accuracy rate of 83.33%, CA-Score Model with 30% accuracy rate, as well as the Fulmer Model and Zavgren Model with an accuracy rate of 0.00 %    

scholarly journals PREDIKSI KEBANGKRUTAN PADA BANK BUMN YANG TERDAFTAR DI BURSA EFEK INDONESIA

NIAGAWAN ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 130
Author(s):  
Muhammad Salman ◽  
Catur Wulandari
Keyword(s):  
Data Analysis ◽  
Prediction Model ◽  
Financial Distress ◽  
Z Score ◽  
Analysis Method ◽  
Gray Area ◽  
Data Analysis Method ◽  
State Owned Enterprise ◽  
Score Model

The research was conducted with the aim of knowing the prediction of the potential for bankruptcy of the four State-Owned Enterprises (BRI, BNI, Bank Mandiri and BTN) using the Altman Z-Score, Springate and Grover G-Score models. The data analysis method used a prediction model for the occurrence of bankruptcy consisting of the Altman Z-Score, Springate and Grover G-Score. The results showed that the prediction of bankruptcy (financial distress) using the Altman Z Score model was obtained from 2015-2019 for the four State-Owned Enterprise Banks (BRI, BNI, Bank Mandiri and BTN) as a whole obtained Z Score between 1.42-1 88 or at the criteria (cut off) Z <181 has the potential to go bankrupt and 1.81 <Z <2.99 gray area. Meanwhile, based on the Springate model from 2015-2019, the four State-Owned Enterprises (BRI, BNI, Bank Mandiri and BTN) overall obtained a Springate of 1.95 - 44.08 and were in the criteria (cut off) S> 0.862 and can be declared as not potentially bankrupt (healthy). Then based on Grover, it was obtained from 2015-2019 in the four State-Owned Enterprise Banks (BRI, BNI, Bank Mandiri and BTN) as a whole obtained a G Score of 1.71 - 2.15 and were in the criteria of G ≥ 0.01 or no potential bankrupt (healthy). The results showed that the Altman Z Score model has a better value than Springate and Grover because the number of ratios is more so that it can predict bankruptcy better 

scholarly journals BANKRUPTCY ANALYSIS USING ALTMAN Z SCORE MODEL IN MANUFACTURING COMPANY AT INDONESIA STOCK EXCHANGE IN 2013-2014

2017 ◽  
Vol 5 (1) ◽  
pp. 1 ◽  
Author(s):  
Suci Kurniawati
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Secondary Data ◽  
Financial Statements ◽  
Asia Pacific ◽  
Manufacturing Companies ◽  
Z Score ◽  
Score Model ◽  
Score Index

Analysis of financial distress is very important, because it enables to assess an indication of the company's financial distress, how the indication of financial distress using Altman z-score in industry manufacturing sector in 2013-2014, and whether the Altman z-score model can be used as a tool in predicting the tendency of financial distress. The purpose of this study is to analyze the financial distress of 125 manufacturing companies with different sectors and subsectors using Altman Z-Score model in 2013 and 2014. The source of data used was secondary data, such as financial statements of manufacturing companies’ publication issued by BEI and obtained from the internet by downloading through the website: www.idx.com. This study employed descriptive quantitative method. The findings of the Z-Score index on manufacturing companies in 2013 were occupied by PT. Intan Wijaya International Tbk. in chemical subsector, and in 2014 Herbal and Pharmaceutical Industry of PT Sido Muncul Tbk. was the first highest rank and healthy condition.  Whereas the lowest rank was PT. Asia Pacific Fiber Tbk. in textile and garment sub-sector in 2013 and 2014, having financial distress condition. The findings of this study are not consistent or even in accordance with the reality which shows that the Altman method cannot be used as a tool to indicate a tendency towards company’s financial distress.

scholarly journals Analysis of bankruptcy issues at manufacturing companies, sub-sectors of cosmetics and houseappliances registered in Indonesia Stock Exchange (IDX) year 2015-2017 using Altman Z-score

2019 ◽  
Vol 4 (01) ◽  
pp. 27
Author(s):  
Indar Khaerunnisa ◽  
Nur Anisa Rahayu
Keyword(s):  
Financial Performance ◽  
Financial Distress ◽  
Stock Exchange ◽  
Manufacturing Companies ◽  
Z Score ◽  
Marketing Performance ◽  
Grey Area ◽  
Manufacturing Company ◽  
Score Model

This research aims to figure out the level of companies bankruptcy by applying Altman Z-Score at the manufacturing companies registered in the Indonesia Stocks Exchange. The result of the research has indicated that ZScore model is applicable to detect the company’s potential bankruptcy issues, especially manufacturing company subsectors of cosmetics and houseappliances. Altman Z-Score model has classified the companies into three categories; safe, grey area and distress. Based on the result of the research, for the companies which are in the grey area category are suggested to improve their financial performance and to use the benefit of all the assets properly to get the revenue as much as possible. However, for the companies which are in the safe category are suggested to increase their performance, especially marketing performance so that they will receive bigger amount of the revenue, nevertheless, the potential of financial distress can be minimized accordingly. Keywords: manufacturing company, financial distress, Altman Z-Score.

scholarly journals Financial distress prediction of listed companies – empirical evidence on the Vietnamese stock market

2020 ◽  
Vol 17 (2) ◽  
pp. 377-388
Author(s):  
Tran Quoc Thinh ◽  
Dang Anh Tuan ◽  
Nguyen Thanh Huy ◽  
Tran Ngoc Anh Thu
Keyword(s):  
Stock Market ◽  
Financial Distress ◽  
Financial Statements ◽  
Listed Companies ◽  
Research Model ◽  
Z Score ◽  
Economic Decisions ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
High Level

Financial distress is a matter of concern in the recent period as Vietnam gradually enters global markets. This paper aims to examine the factors of Altman Z-score to detect the financial distress of Vietnamese listed companies. The authors use a sample of 30 delisted companies due to financial problems and 30 listed companies on the Vietnamese stock market from 2015 to 2018. They employ Independence Samples T-test to test the research model. It is found that there are significant differences in the factors of Altman Z-score between the group of listed companies and the group of delisted companies. Further analyses using subsamples of delisted companies show that the factors of Altman Z-score are also statistically different between companies with a low level of financial distress and those with a high level of financial distress. Based on the results, there are some suggestions to assist practitioners and the State Securities Commission in detecting, preventing, and strictly controlling financially distressed businesses. These results also enable users of financial statements to make more rational economic decisions accordingly.

Sign in / Sign up

Export Citation Format

Share Document