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.

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 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 ANALISIS TINGKAT AKURASI MODEL ALTMAN Z-SCORE, INDEKS KEPAILITAN, DAN INDEKS IN05 SEBAGAI PREDIKTOR KEBANGKRUTAN PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2011-2015

Jurnal Ecogen ◽  
2018 ◽  
Vol 1 (4) ◽  
pp. 197
Author(s):  
Diana Novita
Keyword(s):  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Total Sample ◽  
Bankruptcy Prediction ◽  
Manufacturing Companies ◽  
Z Score ◽  
Sample Test ◽  
Score Model ◽  
Post Hoc

This study discusses the use of bankruptcy prediction model that does not exist applied in Indonesia and determine the accuracy of each model. The research objective is to analyze the differences in outcome prediction and know the model that has the best accuracy level between the model Altman Z-Score, Bankruptcy Index, and IN05 Index. This type of research is a comparative study, the population of all manufacturing companies listed on the Indonesia Stock Exchange in 2011 to 2015. The sample is determined by purposive sampling method so acquired 28 companies, and the total sample is 140 years old company. Data used is secondary data obtained from the official website of Indonesia Stock Exchange (www.idx.co.id). The analytical method used is the analysis of different test-independent k-sample test, descriptive statistics and the accuracy of the model using post hoc test and the type of error. The results show that: 1) there are significant differences between the model of the Altman Z-Score model Insolvency Index, and models IN05 index on manufacturing companies listed on the Stock Exchange. 2) The model has the best accuracy by post hoc test is a model of the Altman Z-Score and by type of error is the most accurate models are models IN05 index.Keywords: Altman Z-Score, Insolvency Index, IN05, Bankruptcy

scholarly journals ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z-SOCRE DAN MODEL INTERNAL GROWTH RATE

2018 ◽  
Vol 1 (1) ◽  
pp. 18-25
Author(s):  
Dian Safitri ◽  
Dina Fitri Septarini
Keyword(s):  
Growth Rate ◽  
Empirical Study ◽  
Stock Exchange ◽  
Secondary Data ◽  
Analytical Techniques ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Rate Model ◽  
Research Objects ◽  
Score Model

Analysis of Bankruptcy Prediction Using Altman Z-Score Model and Internal Growth Rate Model An Empirical Study on Delisting Companies from Indonesia Stock Exchange Year 2012-2015. This study aims to predict bankruptcy using the Altman Z Score model and the Internal Growth Rate model in delisting companies from the Indonesia Stock Exchange in 2012-2015 and to find the most appropriate model in predicting bankruptcy.The number of companies studied were 12 companies delisted from the Indonesia Stock Exchange 2012-2015 with a year of observation for 3 years before delisting, so that the object of research selected as many as 36 objects of research, with the object that can be studied as many as 24 research objects. The data used is secondary data. Analytical techniques used are Altman Z-Score model and Internal Growth Rate model.Results from 24 objects of the research using modification Altman Z-Score model there are 10 objects that fall into the category of bankruptcy. While using the Internal Growth Rate model there are 12 companies that fall into the category of bankruptcy. From the results of the analysis can be seen that the model of Internal Growth Rate is more appropriate and easier to use to shave bankruptcy of 12 companies delisting from the Indonesia Stock Exchange.   Keywords: Altman Z-Score, Internal Growth Rate, and Prediction of bankruptcy.

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 TESTING BHANDARI Z-SCORE MODEL BANKRUPTCY PREDICTION USING CASH FLOW

2018 ◽  
Vol 2 (1) ◽  
pp. 121-128
Author(s):  
Barcha Handal Sakti ◽  
Ely Kartikaningdyah
Keyword(s):  
Cash Flow ◽  
Stock Exchange ◽  
Predictor Variable ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Discriminating Power ◽  
Significant Difference ◽  
Operating Cash Flow ◽  
Score Model

This research aimed to know whether the predictor variables on Bhandari’s z-score model having discriminating power which in each of the group has significant difference. Sample which was being used to assist was the manufacture company that consisted of healthy company and the unhealthy company enrolled in Indonesia stock exchange in the period of 2012-2014. Sample collecting method used purposive sampling and cross section was the data used in this research. This research was conducted by using Multivariat Discriminant Analysis (MDA). The result of this study showed predictor variable that gave discriminating power which stood of quality of earning (EAQ), operating cash flow divided by current liabilities (OCFCL), operating cash flow margin (OCFM), and operating cash flow return on total assets (OCFA) in distinguishing the healthy and unhealthy company significantly.

Pengaruh Prediksi Kebangkrutan Model Altman Z-Score, Reputasi Auditor dan Opinion Shopping terhadap Opini Audit Going Concern

Owner ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 343-355
Author(s):  
Muhammad Yunus ◽  
Calen Calen ◽  
Sarida Sirait
Keyword(s):  
Stock Exchange ◽  
Sampling Technique ◽  
Bankruptcy Prediction ◽  
Manufacturing Companies ◽  
Z Score ◽  
Audit Opinion ◽  
Going Concern ◽  
Opinion Shopping ◽  
Score Model ◽  
Auditor Reputation

This study aims to determine the effect of the bankruptcy prediction of the Altman z-score model, auditor reputation and opinion shopping on going concern audit opinion in manufacturing companies listed on the Indonesia Stock Exchange in 2015-2019. This research is a causal associative research with a quantitative approach. The sample in this study were 25 manufacturing companies listed on the Indonesia Stock Exchange which were determined using purposive sampling technique. Observations in this study were carried out throughout the period 2015 to 2019 so that the number of observations was 125 data. The type of data used in this study is secondary data. While the data analysis method used in this research is panel data regression analysis with statistical data processing software, namely STATA. Based on the results obtained in this study, it can be seen that the prediction of bankruptcy based on the Altman z-score model has no significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange. Auditor reputation is proven to have a negative and significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange. And opinion shopping is also proven to have a negative and significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange.

scholarly journals ANALISIS PREDIKSI KEPAILITAN PADA BANK UMUM SWASTA NASIONAL DEVISA YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2010 – 2013

2018 ◽  
Vol 4 (1) ◽  
pp. 93
Author(s):  
Sumaniyatun Fadhilah ◽  
Indah Kurniawati
Keyword(s):  
Commercial Bank ◽  
Foreign Exchange ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Working Capital ◽  
Purposive Sampling ◽  
Gray Area ◽  
Private Banks

The purpose of this study is to assess bankruptcy prediction in the National Private Banks Foreign Exchange listed in Indonesian Stock Exchange. This study uses the size of liquidity ratio of working capital to total assets. This study uses the find were the purposive sampling. The population in this study is the National Private Commercial Bank Foreign Exchange listed on the Indonesian Stock Exchange during the period of the study, namely between 2010 until 2013. The sample amounted to 21 banks during the 4 years that have been selected based on specific criteria. Based on the results of the analysis carried out stating that the National Private Commercial Bank Foreign Exchange listed in Indonesian Stock Exchange in 2010 there were 29 % of banks that are insolvent, 71 % of banks that are in the gray area, and no banks that are in not bankruptcy predictions. In 2011 29 % of banks that are insolvent, 67 % of banks that are in the gray area and 5 % are located on the banks not bankruptcy prediction. In 2012 29 % of banks that are insolvent, 67 % of banks that are in the gray area, and 5 % of banks that are in the prediction of the bank is not bankrup. In 2013 29 % of banks that are in bankruptcy prediction, 71 % of banks that are in the gray area, and there are no banks that are in not bankruptcy predictions. There is no difference in Z-score on bankruptcy prediction National Private Banks Foreign Exchange Listed in Indonesian Stock Exchange between 2010, 2011, 2012, and 2013.

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

Sign in / Sign up

Export Citation Format

Share Document