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

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.

2017 ◽  
Vol 2 (02) ◽  
pp. 11
Author(s):  
Irwansyah .

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.


Author(s):  
Rianti Fifriani ◽  
Perdana Wahyu Santosa

Bankruptcy prediction is needed to assess the prospect of going concern and sustainability of the corporations in the future. This study aims to predict the bankruptcy of corporates with the Altman Z-Score Modification model in the telecommunications industry in Indonesia. The data used are the financial statements of the telecommunications industry that listing on the Indonesia Stock Exchange for the period 2011-2015. Samples for this study uses purposive sampling according to company criteria. The results of the study using the Altman Z-score modification method found two potentially bankrupt companies, namely Bakrie Telecom, Tbk, and Smartfren, Tbk. While Indosat, Tbk, and XL Axiata, Tbk have high financial distress potential due to liquidity and profitability problems that tend to weaken. Meanwhile, Telkom Indonesia, Tbk, and Infracom Inovisi financial concessions are relatively healthy and have the right business expectations


PERSPEKTIF ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 447-452
Author(s):  
Wardayani Wardayani ◽  
Azhar Maksum

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.


2020 ◽  
Vol 5 (1) ◽  
pp. 24-33
Author(s):  
Dewi Oktary

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%.


2019 ◽  
pp. 191
Author(s):  
I Komang Try Satriawan Korry ◽  
Made Pratiwi Dewi ◽  
Ni Luh Anik Puspa Ningsih

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.


2018 ◽  
Vol 2 (2) ◽  
pp. 93-105
Author(s):  
Elysa Lisitiana Putri

The research aims to predict financial distress at the Foreign Exchange National Private Commercial Bank by using analysis of risk, good corporate governance, earnings, capital and size. Using  sample 17 national foreign exchange private banks, and data analysis techniques using Multiple Linear Regression for four conditions, namely all conditions, financial distress conditions, gray area conditions, and non financial distress conditions. The results of this study indicate that the NPL and the proportion of independent commissioners do not have a significant effect on all conditions, financial distress conditions, gray area conditions, and non financial distress conditions. ROA has a significant effect only for all conditions, gray area, and non financial distress conditions. CAR has a significant effect on all conditions, and financial distress conditions, size only has a significant effect on all conditions and conditions in the gray area.


IKONOMIKA ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 144
Author(s):  
Anissa Agustina Rahmadini

Abstract-This research aims at bankruptcy prediction in PT. Bank Ekonomi Raharja which delisted from The Indonesia Stock Exchange and determine the level of suitability of these predictions with the auditor's opinion on the financial statements. This research is a descriptive study with a sample of companies that delisting from the stock exchange in 2015. Based on processing and analysis of financial data year 2011-2015 results obtained from three models of bankruptcy prediction Springate and Fulmer predicted PT. Bank Ekonomi Raharja went bankrupt during that period, while the method of Altman predicts PT. Bank Ekonomi Raharja are in the category of "gray area". In addition the level of agreement between the predictions of bankruptcy by the auditor's opinion is only 20%, this corresponds to the condition that the company is still operating despite at delisted from the stock exchange.


2021 ◽  
pp. 99-108
Author(s):  
Armadani Armadani ◽  
Abid Ilmun Fisabil ◽  
Dexta Tiara Salsabila

This research was conducted with the aim of knowing financial distress and bankruptcy predictions in the hotel, restaurant & tourism sub-sector companies during the pandemic of Covid-19 in 2020 using the Altman Z”-Score ratio analysis. The population of this research is all service and hospitality companies listed on the Indonesian Stock Exchange before 2018, the sample was selected based on predetermined purposive sampling criteria. From a sample of 25 companies, using the Z”-Score ratio, it is predicted that there was an increase in the category of bankruptcy (red zone) of 3 companies only within a quarter during the crisis. Companies that were initially included in the safe category as well as having a low risk of bankruptcy (healthy) also decreased, adding 2 companies to the vulnerable category (gray area). This indicates that there are difficulties both financially and in liquidity as well as  a decrease in the company's ability to grow, which may lead to bankruptcy. Keywords: Financial Distress, Altman Z”-Score, Bankruptcy, Covid-19.


2017 ◽  
Vol 1 (2) ◽  
pp. 156-173
Author(s):  
Erwita Dewi

This study aims to determine the financial statements prior to the bankruptcy can be used to predict the rate of bankruptcy with Altman Model and Foster on coal mining company listed on the Indonesia Stock Exchange. Model classification Altman Z score Z score> 2.90 is classified as a healthy company, while the company has a Z score <1.20 were classified as potentially bankrupt company. Furthermore, scores between 1.20 to 2.90 is classified as a company in the gray area or the gray area. While the Model Z score Foster use the "Cut-off Point" Z = 0.640, so companies that have Z < 0.640 belongs to a group of companies that go bankrupt, while if Z > 0.640 included in the group of companies that are not bankrupt. After that tested the difference between the predicted results using independent samples t test. The results of the analysis of financial ratios and Foster Altman model proved capable of predicting corporate bankruptcies coal mining sector in Indonesia Stock Exchange in 2014-2015. Results Zscore Altman bankruptcy prediction for the year 2014-2015 shows an increase in predictive companies entering bankrupt category. In 2014 by 22% (there are four companies that PT.BUMI Resources Tbk, PT.Darma Henwa Tbk, PT.Delta Dunia Makmur Tbk and PT.Perdana Karya Perkasa Tbk), and in 2015 by 44% (there are eight companies, namely       PT. Adaro Energy Tbk, PT.Atlas Resources Tbk, PT. Bumi Resources Tbk, PT. Darma Henwa Tbk, PT. Delta Dunia Makmur Tbk, PT.Perdana Karya Perkasa Tbk, PT.Petrosea and  PT. Golden Eagle Energy Tbk). Foster Zscore bankruptcy prediction results for the year 2014-2015 shows that there is consistency predictive companies entering bankrupt category. Year 2014-2015 by 28% (there are five companies that PT.Atlas Resources Tbk, PT.Baramulti Sukses sarana Tbk, PT. Bayan Resources Tbk, PT. Darma Henwa Tbk and PT. Perdana Karya Perkasa Tbk). Both models are Zscore Altman bankruptcy prediction and Zscore Foster in this study proved to be no different in corporate bankruptcy prediction results were proved by analysis of independent sample t test.


2016 ◽  
Vol 12 (2) ◽  
pp. 141
Author(s):  
Augustpaosa Nariman

This study aims to examine and analyze the bankruptcy prediction on coal mining company listed onthe Indonesia Stock Exchange. Bankruptcy prediction on coal mining companies using the Altman ZScore to see how big a bankruptcy prediction coal mining company. The data used in this study arethe financial statements of coal mining companies that are in the period 2012-2014 on the IndonesiaStock Exchange. The analysis technique used is a bankruptcy prediction model Altman Z-Score usingfive variables representing liquidity ratios, profitability ratio, and activity ratio. During theobservation period of 2012-2014 shows that the research data as many as 19 coal mining companiesthere are in a state of bankruptcy. In 2012 and 2013 there were 31.6% of companies experiencingbankruptcy prediction, and 26.32% are in the gray area. 2014 showed an increase where there are42.10% of companies experiencing bankruptcy prediction and 5.26% in the gray area..Keywords: Altman Z-Score, Predicted Bankruptcy, Stock price


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