scholarly journals Analisis Kondisi Financial Distress pada Perusahaan Perbankan di Bursa Efek Indonesia

2021 ◽  
Vol 20 (1) ◽  
pp. 33
Author(s):  
Anindya Aulia Nisa ◽  
Elok Sri Utami ◽  
Ana Mufidah
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Sampling Technique ◽  
Financial Ratios ◽  
Net Income ◽  
Data Pooling ◽  
Purposive Sampling

This study aims to analyze financial ratios in predicting financial distress in banking companies listed on the IDX using the CAR, NPL, BOPO, ROA, ROE, and LDR ratios. The sampling technique is purposive sampling with the criteria of companies that have the potential to experience financial distress, characterized by companies that experience negative net income for at least two consecutive years and those that do not. The method of analysis is logistic regression with data pooling. The results show that NPL can predict the financial distress condition of a banking company, while CAR, BOPO, ROA, ROE, LDR cannot predict the financial distress condition of a banking company. Keywords:  Financial Distress, Financial Ratios, Banking, Logistic Regression

scholarly journals Analisis Diskriminan Untuk Memprediksi Kebangkrutan Perusahaan: Studi Kasus Pada Perusahaan Sektor Textile Dan Garment Di Bursa Efek Indonesia 2016-2018

2021 ◽  
Vol 5 (1) ◽  
pp. 132-140
Author(s):  
Deny Ismanto ◽  
Dyah Ernawati
Keyword(s):  
Discriminant Analysis ◽  
Data Collection ◽  
Discriminant Function ◽  
Financial Distress ◽  
Sampling Technique ◽  
Quantitative Approach ◽  
Financial Ratios ◽  
Collection Method ◽  
Purposive Sampling ◽  
Financial Difficulties

Failure to make a continuous profit will hamper the company's development and this can lead to bankruptcy. Bankruptcy is usually marked by financial distress. Companies that are not able to overcome financial difficulties and problems are getting protracted, then the company will go bankrupt. One way to predict bankruptcy is by using discriminant analysis. This type of research is descriptive with a quantitative approach. The data collection method used is documentation. The population in this study were Textile & Garment companies listed on the IDX in 2016-2018. The sampling technique was purposive sampling and obtained a sample of 8 companies with a potential bankruptcy and 10 companies for 3 years of observation. The results showed that of the 2 financial ratios used Quick Ratio (QR) and Return On Asset (ROA), only the Quick Ratio (QR) ratio proved significant to be able to distinguish bankrupt and non-bankrupt companies. By using discriminant analysis. The dominant variable informing the discriminant function is the Quick Ratio (QR).

scholarly journals PENGARUH FINANCIAL DISTRESS DAN AUDIT CLIENT TENURE TERHADAP PENERIMAAN OPINI AUDIT GOING CONCERN (Studi Empiris pada Perusahaan Manufaktur yang Terdaftar di BEI tahun 2010-2012)

2016 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Dhama Lisan Shidqi ◽  
Sutapa Sutapa
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Sampling Technique ◽  
Manufacturing Firm ◽  
Audit Opinion ◽  
Purposive Sampling ◽  
Going Concern

This research aimed to show empirical proves about the effect of financial distress and audit client tenure to an acceptance of going concern audit opinion. Hypothesis proposed by the researcher were (1) Financial distressnegatively affected to the acceptance of going concern audit opinion, (2) Audit client tenure negatively affected to the acceptance of going concern audit opinion. The sample of this research was manufacturing firm in the period of 2010-2012. Purposive sampling technique was used to obtain the sample. Logistic regression was used to analyze the data. The variables of this research were financial distress and audit client tenure. The result shows that financial distress have negatively affected on the acceptance of going concern audit opinion, while audit client tenure do not have significant effect on the acceptance of going concern audit opinion.

scholarly journals ANALISIS RASIO KEUANGAN UNTUK MEMPREDIKSI KONDISI FINANCIAL DISTRESS PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI

2020 ◽  
Vol 7 (2) ◽  
pp. 156
Author(s):  
Sulistyani Sulistyani ◽  
Deny Ismanto
Keyword(s):  
Financial Distress ◽  
Market Price ◽  
Financial Ratios ◽  
Total Asset ◽  
Significant Variable ◽  
Net Income ◽  
Leverage Ratio ◽  
Purposive Sampling ◽  
Statistic Method ◽  
Earnings Per Share

Financial  distress  precedes  bankruptcy.  Most  financial  distress  models actually rely on bankruptcy data, which is easier to obtain. The purpose of this research to examine financial ratios that predict financial distress condition of a firm. The sample of this research consist of 14 distress firm and 79 non-distress firms, chosen by purposive sampling. The statistic method which is used to test on the research hypothesis  is logistic regresion. The results show that the liquidity ratio (current assets/current liabilities) and a leverage ratio  (current leabilities/total  asset)  is  a  significant  variable  to  determine  of  financial  distress firms.  When  profitability  ratio  (net  income/net  sales)  and  price  earning  ratio (market  price  per  share/earnings  per  share)  are  not  significant  variables  to determine of financial distress.

scholarly journals MODEL PREDIKSI KESULITAN KEUANGAN DENGAN RASIO KEUANGAN (Studi kasus Pada Perusahaan Manufaktur di Indonesia yang telah terdaftar selama 5 Tahun di BEI 2008-2012)

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Diaz Lunardi Santoso
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Manufacturing Industry ◽  
Sampling Method ◽  
Stock Exchange ◽  
Market Value ◽  
Financial Ratios ◽  
Predicting Model ◽  
Book Value ◽  
Purposive Sampling

This research aimed to figure financial distress model and to determined wihich financial ratios can predict financial distress for 1 year; 2 years; and 3 years before. This research was using samples of manufacturing industry thst listed on The Indonesian Stock Exchange in 2008-2012. Based on purposive sampling method, the research samples total are 160 manufactured companies. To figure the model, this research used logistic regression. This research indicated that financial ratios likes leverage, profitability, activity, RE to Total Assets, Market value of Equity to Book Value of Debt can predict financial distress 1 year; 2 years; and 3 years before. These financial ratios can predict above 64% of financial distress for 1 year; 2 years, and 3 years before, while around 36% were influeced by others factors. The predicting model for 1 year have 96,3% clasification accuracy ,while 2 years model have 96,3% clasification accuracy and 3 years model  have 92,5% clasification accuracy

scholarly journals Pengaruh Rasio Keuangan pada Financial Distress

2020 ◽  
Vol 30 (8) ◽  
pp. 1969
Author(s):  
A. A. Istri Agung Mahaningrum ◽  
Ni Ketut Lely Aryani Merkusiwati
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Financial Ratios ◽  
Observation Data ◽  
Analysis Technique ◽  
Negative Effect ◽  
Industry Sectors ◽  
Profitability Ratios

The purpose of this study is to obtain empirical evidence about the effect of financial ratios on financial distress. This research was conducted on companies in the basic and chemical industry sectors listed on the Indonesia Stock Exchange in the 2016-2018 period. The sample was determined using the nonprobability sampling method with a purposive sampling technique. The number of samples used was 39 companies and the overall observation data for the 2016-2018 period was 117 observation data. The analysis technique used is logistic regression analysis. Based on the results of the study, it was stated that liquidity ratios had no effect on financial distress, leverage ratios had a positive effect on financial distress, profitability ratios had a negative effect on financial distress, activity ratios had no effect on financial distress and growth ratios had no effect on financial distress. Keywords: Financial Distress; Financial Ratios; Logistic Regression.

scholarly journals Akurasi Model Logistik Springate, Zmijewski, dan Grover Dalam Menakar Kesulitan Keuangan Perusahaan Pembiayaan

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Munawarah Munawarah
Keyword(s):  
Logistic Regression ◽  
Predictive Models ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Total Sample ◽  
Annual Reports ◽  
Analysis Model ◽  
Purposive Sampling

This study aims to determine springate, grover and zmijewski able to predict the condition of financial distress in finance companies listed on the Indonesia Stock Exchange. From  three models can be known which model is the most accurate in predicting financial distress. There are 17 companies in Financing sector as population in this study from 2013-2017. Using purposive sampling technique, total sample of 85 financing companies was obtained. Secondary data were used in this research sourced from the company's annual reports. The analysis model used is logistic regression. Simultaneously, all predictive models affect the probability of financial distress. While partially only Zmijewski can influence the prediction of financial distress conditions in Financing sub-sector companies listed on the Indonesia Stock Exchange. Nagelkerqe Square value shows 0.606 meaning that only 60.6% variation of the accuracy of these three models in predicting financial distress conditions of finance companies. While 39.4% can be explained by other models not examined in this study.

scholarly journals CAPITAL ADEQUACY RATIO, NON PERFORMING LOAN, NET INTEREST MARGIN, BIAYA OPERASIONAL PENDAPATAN OPERASIONAL DAN LOAN TO DEPOSIT RATIO TERHADAP FINANCIAL DISTRESS

2018 ◽  
Vol 10 (2) ◽  
pp. 90-98
Author(s):  
Baiq Defika Zahronyana ◽  
Dewa P.K. Mahardika
Keyword(s):  
Logistic Regression ◽  
Commercial Bank ◽  
Financial Distress ◽  
Sampling Technique ◽  
Model Analysis ◽  
Capital Adequacy ◽  
Purposive Sampling ◽  
Net Interest Margin ◽  
Capital Adequacy Ratio ◽  
Research Population

The purpose of this research is to determine the effect of CAR, NPL, NIM, BOPO, LDR on the fianancial distress of BUMN Commercial Bank either simultaneously or partially. BUMN Commercial Bank in 2012-2016 was selected as a research population. The purposive sampling technique was used for sampling and obtained samples as much of 4 companies with a five-year period every three months, resulting 80 data to be observed. The Model analysis in this research is logistic regression by using software SPSS 20. The results showed that the variables CAR,NPL,NIM,BOPO,LDR simultaneously affect the financial distress. Partially NPL,NIM, and BOPO variables don’t have effect on financial distress, while CAR variable has significant negative has effect to financial distress and LDR variable significant positf has effect on financial distress.

scholarly journals PENGARUH KOMPLEKSITAS OPERASI PERUSAHAAN DAN KOMITE AUDIT TERHADAP AUDIT DELAY DENGAN FINANCIAL DISTRESS SEBAGAI VARIABEL MODERASI PADA PERUSAHAAN PERTAMBANGAN YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2016 – 2018

2020 ◽  
Vol 4 (1) ◽  
pp. 94-101
Author(s):  
Yoosita Aulia
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Audit Committee ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Purposive Sampling ◽  
Mining Companies ◽  
Analysis Technique

This study aims to analyze and prove financial distress is able to moderate the influence of the audit committee and audit committe on audit delay. The population in this study are mining companies listed on the Indonesia Stock Exchange for the period of 2016-2018. The sampling technique uses a purposive sampling technique with a total of 66 samples. The analysis technique used in this study is logistic regression. The results of this study indicate that . Financial distress does not moderate the effect of the complexity of the company's operations on audit delay on mining companies listed on the Indonesia Stock Exchange during the period 2016-2018. Financial distress does not moderate the effect of the audit committee on audit delay on mining companies listed on the Indonesia Stock Exchange during the period 2016-2018.

scholarly journals PENGARUH OPERATING CAPACITY, SALES GROWTH DAN ARUS KAS OPERASI TERHADAP FINANCIAL DISTRESS

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Annisa Livia Ramadhani ◽  
Khairun Nisa
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Financial Distress ◽  
Agricultural Sector ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Cash Flows ◽  
Sales Growth ◽  
Operating Capacity ◽  
Operating Cash Flows

This study aims to determine how the influence of operating capacity, sales growth and operating cash flows on financial distress. The population in this study israll agricultural sector companies listed on the Indonesia Stock Exchange (IDX) in 2013-2017. The sampling technique in this study used purposive sampling which produced 8 samples in a period of 5 years, namely as many as 40 units of data samples. The analytical method used is logistic �regression analysis which is processed. using SPSS Version 25. Based on the results of this study, it was found that simultaneous operating capacity, sales growth and operating cash flows influence the occurrence of financial distress. Then partially, operating capacity and sales growth have no effect on the occurrence of financial distress, while operating cash flows have a positive and significant effect on the occurrence of financial distress.�Keyword : Financial Distress, Operating capacity, Sales growth, Operation cash flow.

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