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 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.

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 BANKRUPTCY PREDICTION ANALYSIS USING THE ZMIJEWSKI MODEL (X-SCORE) AND THE ALTMAN MODEL (Z-SCORE)

2020 ◽  
Vol 1 (5) ◽  
pp. 794-806
Author(s):  
Viciwati Viciwati
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Accuracy Rate ◽  
Financial Reports ◽  
Normality Test ◽  
The Difference ◽  
Score Model

This study aims to identify and analyze the accurate models of Financial Distress in retail companies listed on the Indonesian Stock Exchange in 2014-2018 using the Zmijewski (X-Score) and Altman (Z-Score) Model. The sample used is 70. This study uses secondary data from the 2014-2018 annual financial reports. This study tested the hypothesis using the normality test and the Kruskal Wallis test or the difference test using SPSS version 26. The results of this study indicate that the Zmijewski (X-Score) model is the model that has the highest accuracy rate in predicting bankruptcy with an accuracy rate of 90%.

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 Analisis Kinerja Keuangan Perusahaan pada PT. Japfa Comfeed Indonesia Tbk

2020 ◽  
Vol 5 (2) ◽  
pp. 203
Author(s):  
Jezzyca Ria Paramita ◽  
Iwan Eka Putra ◽  
Abd Halim ◽  
Ermaini Ermaini
Keyword(s):  
Financial Performance ◽  
Secondary Data ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Financial Ratios ◽  
Z Score ◽  
Financial Ratio ◽  
Financial Condition ◽  
Score Method ◽  
Solvency Ratio

Financial performance is an overview of how a company's financial condition is. To assess financial performance is used with a benchmark commonly called financial ratios. Financial ratios used are usually such as profitability ratio, liquidity ratio and solvency ratio. in addition to using financial ratios, the company can also use the Altman Z-Score method to assess the level of the company's bankruptcy prediction. This research aims to find out the financial performance of PT Japfa Comfeed Indonesia Tbk as well as the company's future bankruptcy predictions. the research method used is quantitative analysis based on secondary data taken from the Financial Statements of PT Japfa Comfeed Indonesia Tbk for the period 2014 to 2019. The results of the study are measurements of the company's financial ratio showing sufficient value while measurements using the company's Altman Z-Score method show healthy value which means it does not go into 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 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.

Pengaruh Model Prediksi Kebangkrutan, Leverage, Audit Lag, Dan Ukuran Perusahaan Terhadap Opini Audit Going Concern

2013 ◽  
Vol 5 (1) ◽  
pp. 55-76
Author(s):  
Anastasia Paula Salean
Keyword(s):  
Prediction Model ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Annual Reports ◽  
Company Size ◽  
Financial Reports ◽  
Audit Opinion ◽  
Going Concern

The objective of this research is to examine the effect of bankruptcy prediction model, leverage, audit lag, and company size towards obtaining a going concern audit opinion.  The samples in this study are 11 companies listed in Indonesian Stock Exchange being classified as manufacturing sector in the year 2008-2011. The sample in this study determined based on purposive sampling. Data used in this study is a secondary data such as annual reports or financial reports.  The results from this study are (1) bankruptcy prediction model having no significant impact on obtaining a going concern audit opinion, (2) leverage having a significant impact on obtaining a going concern audit opinion, (3) audit lag leverage having a significant impact on obtaining a going concern audit opinion, (4) company size having no significant impact on obtaining a going concern audit opinion. Keywords: obtaining a going concern audit opinion, bankruptcy prediction model,leverage, audit lag, company size

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