scholarly journals DETEKSI KRISIS KEUANGAN PERUSAHAAN SEKTOR PERBANKAN DI INDONESIA

2018 ◽  
Vol 16 (2) ◽  
pp. 1-8
Author(s):  
Qidida Sela Dati ◽  
Kholisa Mirzayatiq ◽  
Citra Agis Fitriana ◽  
Bayu Sindhu Raharja
Keyword(s):  
Stock Exchange ◽  
Prediction Method ◽  
Bankruptcy Prediction ◽  
Capital Adequacy ◽  
Z Score ◽  
Financial Reports ◽  
Book Value ◽  
Capital Adequacy Ratio ◽  
Score Method ◽  
Gray Areas

Altman Z-Score is a method of scoring bankruptcy. The bankruptcy prediction method that will be used in this study is the Altman Z-Score method that is in accordance with the financial ratios which also have a cut-off point to determine the value of bankruptcy. This study uses five ratios, that is Capital Adequacy Ratio (CAR) to the Asset Sector (X1), Earnings Balance on Total Assets (X2), EBIT to Total Assets (X3), Market Value of Debt Book Value (X4), and Interest Income on Total Assets (X5). This research is a descriptive study conducted on 32 banks listed on the Indonesia Stock Exchange. Financial reports for 2013-2016 Taken from the official website of the Indonesia Stock Exchange (IDX) and the Indonesian Capital Market Directory (ICMD) then bankruptcy analysis is used the Altman Z-Score modification model. Based on the results of research and discussion that has been carried out, it can be concluded from 2013-2016 that banks in a healthy condition is 22.66%, banking in gray areas or gray is 34.38%, and bankrupt is 42.97 %.

scholarly journals Bankruptcy Prediction Analysis Using the Altman Z-Score Method at PT Aneka Tambang (Persero) Tbk

2020 ◽  
Vol 1 (2) ◽  
pp. 51-58
Author(s):  
Iis Fitriani ◽  
Puji Muniarty
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Literature Study ◽  
Test Analysis ◽  
Financial Reports ◽  
Score Method ◽  
Data Collection Technique ◽  
Retained Earnings

This study aims to determine the prediction of bankruptcy in Aneka Tambang (Persero) Tbk for the period 2011 to 2018. Z-score is the independent variable (X) measuring by five ratios: working capital to total assets, retained earnings to total assets, earnings before interest and tax to total assets, the market value of equity to total liabilities, and sales to total assets. The background of this research is the government's ban on the export of raw minerals, which resulted in Aneka Tambang (Persero) Tbk no longer making overseas sales of nickel ore, which made the company's profit decline. This research method uses descriptive research with a quantitative approach, the source of the data used is secondary data based on financial reports published on the Indonesia Stock Exchange and the official website www.antam.com. The population used is the financial statement data for ten years, namely from 2009 to 2018, while the sample using for eight years, namely from 2011 to 2018. The data collection technique carried out using documentation and literature study techniques. Data analysis techniques were carried out by discriminant analysis using the Altman Z-Score method and one sample t-test analysis. The Altman Z-Score uses five variables that represent liquidity ratios X1, profitability ratios X2 and X3, and activity ratios X4, and X5. The formula Z-Score Z = 0.717 X1 + 0.847 X2 + 3.107 X3 + 0.420 X4 + 0.998 X5. With criteria, Z> 2.99 categorized as a good company. Z between 1.23 to 2.99 categorized as a company in the grey area or area of ​​financial difficulty. Z <1.23 is categorized as a potentially bankrupt company.

scholarly journals PENGARUH KINERJA KEUANGAN TERHADAP RISIKO KEBANGKRUTAN BANK UMUM SYARIAH DI INDONESIA (METODE ALTMAN Z-SCORE MODIFIKASI PERIODE 2011-2017)

2018 ◽  
Vol 4 (2) ◽  
pp. 166
Author(s):  
Luluk Afiqoh ◽  
Nisful Laila
Keyword(s):  
Capital Adequacy ◽  
Z Score ◽  
Return On Assets ◽  
Analysis Techniques ◽  
Panel Data Regression ◽  
Capital Adequacy Ratio ◽  
Data Regression ◽  
Negative Effect ◽  
Score Method ◽  
Positive Effect

This research aims to find out the influence of financial performance measured using the Capital Adequacy Ratio variable, Financing to Deposit Ratio, Leverage, Bank Size, Loan to Asset Ratio and Return on Assets to the risk of sharia bank bankruptcy in Indonesia calculated using the Altman Z-Score method Modification. This study uses a quantitative approach with panel data regression analysis techniques. The results of this study show partially the variable Capital Adequacy Ratio, Financing to Deposit Ratio, Bank Size has a significant positive effect, the variable Loan to Asset Ratio Leverage has a significant negative effect, and Return on Asset has a positive and insignificant effect. Nevertheles the variable Capital Adequacy Ratio, Financing to Deposit Ratio, Leverage, Bank Size, Loan to Asset Ratio and Return on Asset have a significant effect on the value of Altman Z-Score as a measure of the risk of bankruptcy in Islamic commercial banks in Indonesia.

scholarly journals Analysis of Method Used to Predict Financial Distress Potential in Pulp and Paper Companies of Indonesia

2020 ◽  
Vol 1 (1) ◽  
pp. 57-69
Author(s):  
Fadrul Fadrul ◽  
Ridawati Ridawati
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Descriptive Analysis ◽  
Prediction Method ◽  
Pulp And Paper ◽  
Z Score ◽  
Accuracy Rate ◽  
Error Type ◽  
Paper Company ◽  
Score Method

This study aims to predict financial distress in pulp and paper companies in Indonesia. The data used are the financial statements of each pul and paper company listed on the Indonesia Stock Exchange in 2012-2017. Data analysis techniques used descriptive analysis with three methods of financial distress prediction, namely the Altman Z-Score, Springate, and Zmijewski methods. The results showed that the Zmijewski method is a prediction method with the highest accuracy rate of 100%, with an error type of 0%. The Altman Z-Score method has an accuracy rate of 28.6%, with an error type of 71.4%. While the Springate method has an accuracy rate of 14.3%, with an error type of 85.7%. Therefore an accurate prediction method to predict the potential for financial distress is the Zmijewski method.

scholarly journals Prediksi Kebangkrutan Dengan Altman Z-Score dan Harga Saham pada Perusahaan Manufaktur

2019 ◽  
Vol 2 (2) ◽  
pp. 121
Author(s):  
Hikmah Hikmah
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Financial Report ◽  
Basic Industry ◽  
Manufacturing Company ◽  
Score Method

Bankruptcy Prediction With the Altman Z-Score Method and the stock price on Manufacturing Company. This research aims to analyze the bankruptcy prediction on stock prices in manufacturing company of basic industry sector and chemical sub-sector of metals that listed in Indonesia Stock Exchange for the period of 2015-2017. The sampling method was done with purposive sampling which then determined 15 companies as sample. Sources of data used are secondary data in the form of financial report published in BEI. Data analysis used data panel regression using eviews version 8. These result shows that Altman Z-Score variable: 1) Working capital to total assets, 2) Retained earning to total assets, 3) Earning before interest and taxes to total assets, 4) Market value of equity to book value of total debts, and 5) Sales to total assets significantly influence stock prices in the metal subsector on the Indonesia Stock Exchange, the average company is in the gray area

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 PREDICTING THE POTENTIAL BANKRUPTCY OF COAL MINING COMPANIES USING ALTMAN Z-SCORE METHOD DURING 2012-2016 PERIOD

2020 ◽  
Vol 8 (1) ◽  
pp. 491-500
Author(s):  
Rihfenti Ernayani
Keyword(s):  
Coal Mining ◽  
Stock Exchange ◽  
Study Data ◽  
Z Score ◽  
Working Capital ◽  
Book Value ◽  
Mining Companies ◽  
Grey Area ◽  
Score Method ◽  
Retained Earnings

Purpose of the study: This study aimed to determine and predict potential bankruptcy in coal mining companies listed in Indonesia Stock Exchange (IDX) period 2012-2016. Methodology: This study to using the Altman Z-Score method, with five (5) ratios, namely Working Capital to Total Asset, Retained Earnings to Total Assets, Earning before interest and tax to total assets, Market Value of Equity to Book Value of Debt, and Sales to Total Assets. The ratio of working capital to total assets (X1) is a ratio of liquidity which measures the extent of working capital that is used to finance the total assets. Main Findings: The result showed, by the Z-Score value in 2016 from the coal mining companies studied, four companies fall in the category of potential bankruptcy, three companies in the grey area, and four in the healthy category. Applications of this study: Data sources in this study were coal mining companies listed on the Indonesia Stock Exchange (IDX) for the period 2012-2016. Novelty/Originality of this study: There are 11 coal mining companies taken as sample based on purposive sampling. The result shows, by the Z-Score value in 2016 from the coal mining companies studied, four companies fall in the category of potential bankruptcy, three companies in the grey area, and four in the healthy category.

scholarly journals ANALISIS PENILAIAN FINANCIAL DISTRESS MENGGUNAKAN MODEL ALTMAN (Z-SCORE) PADA PERUSAHAAN FARMASI YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2013-2015

2017 ◽  
Vol 5 (1) ◽  
pp. 55
Author(s):  
Sri Yati ◽  
Katarina Intan Afni Patunrui
Keyword(s):  
Financial Distress ◽  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Pharmaceutical Companies ◽  
Z Score ◽  
Financial Reports ◽  
Book Value ◽  
Total Debt ◽  
Score Model

This study aims to observe the financial distress assessment for pharmaceutical companies listed on the Indonesia Stock Exchange using the Altman Z-Score model. The sample is selected using purposive sampling method. Ten pharmaceutical companies were selected with the criteria listed in the Indonesia Stock Exchange (BEI) and regularly published financial reports in 2013 until 2015. Secondary data was derived from www.idx.co.id site.  The results indicate that the Altman Z-Score model can be implemented in detecting the possibility of financial distress in the pharmaceutical company. Working capital to total assets and book value equity to book value of total debt are two determinant variables which is determining the decrease in Z-score value in this research.  One from ten companies have the lowest value of the Z-Score and experiencing financial distress. For two years, the company is in distress zones but in the third year, the company is managed to increase the value of the company and included in the gray zones. This company must continue to strive in order to stabilize the company's financial and asset utilization to obtain maximum profit, and until it was declared as a healthy company.

scholarly journals Pengaruh Kinerja Keuangan dan Kebijakan Restrukturisasi Kredit pada Nilai Perusahaan Perbankan di Bursa Efek Indonesia

2021 ◽  
Vol 31 (6) ◽  
pp. 1494
Author(s):  
Putu Pryanka Chitta Surya ◽  
Made Gede Wirakusuma
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Firm Value ◽  
Sampling Method ◽  
Stock Exchange ◽  
Capital Adequacy ◽  
Financial Reports ◽  
Company Value ◽  
Analysis Technique ◽  
Capital Adequacy Ratio

This study aims to obtain empirical evidence of the effect of Non Performing Loans (NPL), Loan to Deposit Ratio (LDR), Capital Adequacy Ratio (CAR), and credit restructuring policies on the value of banking firms on the Indonesia Stock Exchange. The research was conducted by analyzing quarterly financial reports published on the Indonesia Stock Exchange website which contained information on banking financial performance ratios, credit restructuring policies, and company value using the PBV method. The Sampling method uses purposive sampling method. The data analysis technique uses multiple linear regression. The results showed that NPL had a negative and significant effect on firm value, LDR had a positive and significant effect on firm value. CAR has a positive and significant effect on firm value. The Credit Restructuring Policy has a negative and significant effect on firm value. Keywords: Non Performing Loans; Loan to Deposit Ratio; Capital Adequacy Ratio; Credit Restructuring Policy; Company Value.

scholarly journals DETERMINANT FACTORS OF NON-PERFORMING LOANS IN CHINESE COMMERCIAL BANKS

2021 ◽  
Vol 8 (02) ◽  
pp. 125-135
Author(s):  
Purwanto Purwanto ◽  
Mei Ling Sun
Keyword(s):  
Growth Rate ◽  
Hypothesis Testing ◽  
Commercial Banks ◽  
Stock Exchange ◽  
Capital Adequacy ◽  
Gdp Growth ◽  
Observation Data ◽  
Financial Reports ◽  
Gdp Growth Rate ◽  
Capital Adequacy Ratio

The purpose of this research is to identify the influence of GDP growth rate, bank interest rate, inflation rate, capital adequacy ratio, and return on asset towards non-performing loans in Chinese commercial banks partially and simultaneously. This study has applied descriptive statistical analysis, classical hypothesis testing, multiple linear regression, and hypothesis testing. When selecting the observation data, this research adopts the intentional sampling method and panel data, 70 units of observational data in total, one part of the data was taken from the financial reports of seven selected sample companies on the Shanghai Stock Exchange in China, and another part of the data was taken from the kyle website. The method used in a quantitative approach with the instrument is EViews 10. The result indicates that BIR and IFR have a partially negative significant influence on NPL. However, GDP growth rate, CAR, and ROA have a negative insignificant effect on NPL. Simultaneously, all of the independent variables have a significant effect on NPL which is described by the value of 63.9% and the left 36.1% is explained by another factor that is excluded in this study. Furthermore, IFR was chosen as the most significant factor which influences NPL.

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%.

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