scholarly journals The Prediction of Bankruptcy using Altman Z-Score Model (Case Study in BRI Bank, BNI Bank, Mandiri Bank, BTN Bank)

2018 ◽  
Vol 2 (1) ◽  
pp. 12
Author(s):  
Mrs Herlin
Keyword(s):  
Z Score ◽  
Model Case ◽  
Gray Area ◽  
Score Model ◽  
Altman Model

Based on the calculation of the Altman model in predicting bankrupt at PT. Bank Rakyat Indonesia (Persero) Tbk in 2014, 2015, 2016, PT. Bank Mandiri (Persero) Tbk in 2014 and 2015 and is PT.Bank Tabungan Negara (Persero) Tbk in 2014 with a score of Z-score above 2.99 indicates that included in the company healthy or not potential to go bankrupt. Companies included in the category of unhealthy or potential companies to go bankrupt with a Z-score of less than 1.81 ie PT. Bank Tabungan Negara (Persero) Tbk in 2014 with a Z-score of 1.405 (<1.81). Companies included in the Gray Area (unpredictable) are PT. Bank Negara Indonesia (Persero) Tbk 2015 with Z-score of 2, 753 and year 2016 with Z-score 2,858. PT Bank Tabungan Negara in 2015 and 2016 with Z-score of 2,138 and 1,906 and PT. Bank Mandiri (Persero) Tbk in 2016 which shows the value of Z-score of 2,168.

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 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.

scholarly journals Metode Altman Z-Skor Dalam Memprediksi Kepailitan Di Semua Koperasi Kredit Di Kabupaten Maumere

2020 ◽  
Vol 21 (01) ◽  
Author(s):  
Yoseph Darius Purnama Rangga ◽  
Henrikus Herdi ◽  
Wilhelmina Mitan
Keyword(s):  
Secondary Data ◽  
Credit Union ◽  
Bankruptcy Prediction ◽  
Regional Government ◽  
Financial Health ◽  
Z Score ◽  
Analytical Technique ◽  
Gray Area ◽  
Credit Cooperatives ◽  
Score Model

Abstract Problems that often occur in a cooperative are usually caused by financial problems. To measure the level of financial health cooperatives can be used analysis of financial ratios using the Altman Z-Score model. This research aims to predict bankruptcy in the credit Union of the regional government Puskopdit, Maumere, using the Altman Z-Score model. The samples in this study were credit cooperatives of the main district Puskopdit in 2015-2017 consisting of 16 cooperatives. The data source used is the secondary data in the form of cooperative financial statements. The analytical technique used is the Altman Z-Score Bankruptcy Prediction model. The results showed that there is a cooperative that has been in the healthy category during the year 2015-2017, namely Torch Mas Cooperative, Tuke Jung, Ortal, Plantation, star East, and Serba Te. In the years 2015 and 2016 Kelubagolit cooperatives entered in the category of gray area, but in the year 2017 the cooperative is in a healthy category. In addition, there are cooperatives during the year 2015-2017 in the category of gray area namely Sube Huter Cooperative, Tuke Ler, Hiro Heling, Bina Pertiwi, and Surya Sakti. The cooperatives of San Dominggo in 2015 and 2016 were in the category of bankruptcy, but the following year entered the gray area category. The cooperative in the category of bankruptcy from 2015-2017 is the youth cooperative Hokeng and Ankara. In the year 2015 Plelu Meluk Cooperative entered in the category of gray area, the cooperative's performance continued to decline and in the year 2016 and 2017 the cooperative was entered in the category of bankruptcy. In the years 2018, Hokeng Youth Cooperative experienced an amalgamation with Mitan Gitan Cooperative. This indicates that the accuracy level of the Altman Z-Score model is high..

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 An Update on Airline Financial Condition and Insolvency Prospects Using the Altman Z" Score Model

2011 ◽  
Vol 47 (2) ◽  
Author(s):  
Richard D. Gritta ◽  
Bahram Adrangi ◽  
Brian Adams ◽  
Nina Tatyanina
Keyword(s):  
Financial Stress ◽  
Stress Model ◽  
Z Score ◽  
Fuel Prices ◽  
Financial Condition ◽  
Score Model ◽  
Altman Model

Stricken by the events of Sept. 11, 2001, and by increases in fuel prices, a key cost which has spiked upward as the price of oil has risen to more than $130 per barrel, the airlines find themselves, once again, in fragile financial shape. The purpose of this article is to measure the financial condition of the industry, given this situation, using a popular financial stress model, the Altman Model.

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