Financial Distress Condition Research Articles

Pengaruh Financial Distress pada Trade Credit Provisions pada Perusahaan Manufaktur di BEI

Purpose: (IDX) period 2018-2023 by focusing on Financial Distress conditions on Trade Credit Provisions. Financial distress is identified through delisting conditions due to negative net income and book value and inappropriate management decisions. Methodology: Through a quantitative approach with 46 samples of companies selected based on stratified random sampling and purposive sampling methods. Results: The results of the analysis show that there is a significant negative relationship between financial difficulties and accounts payable and there is a significant negative relationship between financial difficulties and accounts receivable in the shares of manufacturing sector companies on the IDX. Limitations: The limitations of this research are only on financial distress and manufacturing sector companies 2018-2023 Contribution: It is therefore worth considering a deeper exploration of how internal mechanisms, such as working capital management and financing strategies, play a role in determining trade credit policies.

ANALISIS PENGARUH OPERATING CASH FLOW, PROFITABILITAS, SALES GROWTH, FIRM SIZE, DAN LEVERAGE TERHADAP PREDIKSI KONDISI FINANCIAL DISTRESS

The phenomenon of PKPU (Application for Insolvency and Delayed Debt Payment) on some issuers in the IDX appears to indicate financial problems (financial distress). The research was conducted to test and analyze the impact of operating cash flow, profitability, sales growth, firm size, and leverage on the prediction of financial distress conditions in sub-sector companies heavy construction and civil engineering registered in the IDX in 2020-2022. The sampling techniques used are purposive samplings with samples obtained of 60 data. The quantitative method is used in this study through an associative approach using secondary data as well as using double linear analysis with the SPSS version 22 test tool. The results of this study show that the profitability variables with proxy return on asset have a significant impact on financial distress, while the operating cash flow, sales growth, firm size, and leverage variables of proxy debt to asset ratio have no influence on financial stress. The implications of this study are expected to inform investors to always do financial analysis first before making decisions in the heavy construction and civil engineering subsectors.

PENGARUH FINANCIAL DISTRESS DAN CORPORATE GOVERNANCE TERHADAP KECEPATAN PUBLIKASI LAPORAN KEUANGAN TAHUNAN

The matter of submitting annual financial reports on time greatly affects the quality of the financial report itself. Financial reports are said to be of quality when information is presented on time and available when needed. The purpose of this study is to determine whether the condition of financial distress and the form of corporate governance of a company affect the speed of publication of annual financial reports. The study was conducted on companies engaged in the property and real estate sector and listed on the Indonesia Stock Exchange in 2021-2022. The purposive sampling technique was used to select samples with a total of 140 samples. The data in the study are secondary data. The data analysis technique is multiple linear analysis. The results of the study show that financial distress and corporate governance represented by managerial ownership and audit quality do not affect the speed of publication of annual financial reports. Meanwhile, corporate governance represented by independent commissioners, institutional ownership and audit committees have a negative effect on the speed of publication of annual financial reports

The Influence of Sales Growth, Profitability, Liquidity and Firm Size Towards Financial Distress

There are several models that can be used in analyzing a company's Financial Distress, the most widely used is the Altman model. The study aims to analyze and identify the influence of fundamental factors represented by ratios such as Sales Growth Analysis, ROA Ratio, Current Ratio, and Firm size on Financial Distress conditions. This research was conducted on financial statements of oil and gas mining sector. Data was collected using data panel with multiple linear regression technique analysis. Data was proceed using Eviews 12. The result show Sales growth, ROA, Current Ratio and TATO ratio have a partially significant effect on Financial Distress. Sales growth ROA, Current Ratio and TATO ratio together and a simultaneous have an effect on Financial Distress

Financial Distress: Ratio of Financial Statements of Mining And Metals Companies

This research aims to determine the influence of profitability, leverage and liquidity on financial distress in the mining and metals company sub-sector in Indonesia during the 2018-2022 Period. Profitability is measured using Return on Assets (ROA), leverage is measured by Debt to Equity Ratio (DER), and liquidity is measured using Current Ratio (CR). Financial distress was identified using the Altman Z-score model. This type of research is a quantitative research sampling in this study using purposive sampling techniques and data that has been processed for this study as many as 11 Mining and Metal companies listed on the Indonesia Stock Exchange. The data source in this study uses a secondary data source sourced from the Annual Report published by mining and metals companies listed on the Indonesia Stock Exchange. The data analysis used in this study used Descriptive Satistic analysis, Pooled Data, Chow Test, Hausman Test, Fixed Effect, Partial Test, Determination Coefficient Test (R2). The test results showed that the Return on Asset (ROA) variable, Debt to Equity ratio (DER), did not have a significant effect on financial distress, while the Current Ratio (CR) had a significant effect on financial distress in Mining and Metal Companies listed on the Indonesia Stock Exchange in 2018-2022. The Result of this study is that profitability, leverage, and liquidity significantly affect the condition of financial distress in mining and metals sub-sector companies in Indonesia.

Analysis Prediction of Financial Distress in Islamic Commercial Banks in Southeast Asia Using the Springate S-Score Method

Financial distress is a condition of financial difficulties before entering the bankruptcy stage, so bankruptcy itself is the impact of financial distress, and the company can no longer be saved. The chaotic economy caused by the COVID-19 pandemic had a negative impact on various sectors, especially Islamic banking institutions, which experienced a decline in financial performance and even experienced financial distress. The purpose of this study is to analyze the prediction of financial distress in Islamic Commercial Banks in Southeast Asia using the Springate S-Score method, as well as to see and determine differences in the level of financial distress in each Islamic Commercial Bank that is used as the research sample. The research method used in this research is quantitative, and the research design used is descriptive and comparative. This study used a purposive sampling technique with a sample of 4 Islamic Commercial Banks in Southeast Asia with a 5 year research period. The data analysis applied descriptive analysis techniques, the Springate S-Score method, and the ANOVA Test. The results of this study indicate that each Islamic commercial bank used as a sample is categorized as distressed based on Springate calculations for the 2017-2021 period, and there are differences in financial distress conditions at each bank.

Analysis of Factors that Influence Financial Distress Conditions using the Debt Service Coverage Ratio Approach (Case Study of the Food and Beverage Industry Listed on the Indonesian Stock Exchange Before and During Covid-19)

Covid-19 condition is known to have had a major impact on the financial performance of issuers. The food and beverage industry is one of the mainstay manufacturing sectors in making a major contribution to national economic growth. The data used in this study was pre-covid data, year 2018 until 2021 during covid. The method used in this study is the Debt Service Coverage Ratio Pranowo et al. (2010). The analysis used in this research is descriptive analysis and panel data regression. The results of this research were that 26 company experienced a decrease in distress, 26 company experienced an company in Profitability, 26 company experienced an increase in Liquidity, 26 company experienced an increase in Efficiency, 26 company experienced a decrease in Leverage, 26 company experienced a decrease in Solvency. Factors that show a significant influence on financial distress in the period before Covid-19 are Efficiency, Liquidity. The factor of increasing efficiency also influences the reduction in the occurrence of financial distress. The factor of increasing liabilities also influences the increase in the occurrence of financial distress. Factors that show a significant influence on financial distress during Covid-19 are Solvability and Efficiency. This shows that during Covid-19, the increase in the value of debt will influence the tendency to increase the occurrence of financial distress. The decline in the value of income during Covid-19 also influenced the increase in financial distress. Advice to investors to be more selective in choosing food and beverage issuers as a place to invest during Covid-19. One important consideration is that investors focus more on factors that have a significant influence on Liquidity, Efficiency, Solvency.

Analisis Financial Distress pada Perusahaan Sektor Perdagangan, Jasa dan Investasi yang Terdaftar di Bursa Efek Indonesia

Identification of financial distress conditions was an important thing for companies to anticipate bankruptcy. This study was aimed to analyze the financial distress model in trading, service and investment sector companies in 2018-2020 using the Altman Z-Score, Grover, Springate and Zmijewski modified models. In addition, this was also aimed to determine the level of accuracy of the Modified Altman Z-Score, Grover, Springate and Zmijewski models. This research was included in the type of quantitative research. The research population consisted of all trading, service and investment companies listed on the Indonesian Stock Exchange during the period 2018-2020. This study used purposive sampling technique with total 133 companies. The data analysis model used in this study were the Altman Z-Score, Grover, Springate and Zmijewski Modified Model. It was conducted by taking secondary data from the Indonesian Stock Exchange website (www.idx.co.id). Based on the results of the analysis that had been carried out, the results showed that: (1) There were 55,89% companies experiencing financial distress and 44,11% non-financial distress using the Springate model on the analysis; (2) On the analysis using the Altman Z-Score Modified model, there were 25.81% companies experiencing financial distress and 59,65% nonfinancial distress; (3) Using the Zmijewski model, it showed that 20,80% of companies experienced financial distress and 79,20% of non-financial distress; (4) Using the Grover model, it showed that 20.80% of companies experienced financial distress and 77,94% of non-financial distress; (5) The Springate model was the most accurate model in analyzing the financial distress. Keywords: Accuracy Level, Altman Z-Score Modification, Financial Distress, Grover, Springate, Zmijewski.

Pengaruh Rasio Keuangan Terhadap Financial Distress Pada Perusahaan Manufaktur Yang Terdaftar Di Jakarta Islamic Index 70 (JII70) Periode 2018-2021

Financial management is very important and vital for a company to maintain its business continuity and avoid financial distress. Financial distress is a condition of financial difficulties that can cause bankruptcy in a company which can be characterized by low financial ratios. This quantitative study aims to determine the effect of financial ratios on financial distress partially and simultaneously on the financial distress conditions of manufacturing companies listed on the Jakarta Islamic Index 70 (JII70) during the 2018-2021 period. This research involved 48 annual financial reports from 12 manufacturing companies in JII70 during the 2018-2021 period obtained from a purposive sampling technique. Data analysis used panel data regression which was processed using Eviews12 software. The results of this study indicate that financial ratios consisting of liquidity, solvency, activity and profitability ratios significant effect on financial distress. Then partially, the liquidity ratio and activity ratio have a positive and significant effect on financial distress. The solvency ratio has a negative and significant effect on financial distress. Meanwhile, the profitability ratio has no effect on financial distress. Following up on the findings of this study, companies need to pay attention to their financial ratios so they can avoid financial distress.

The Effect of Debt to Asset Ratio (DAR) and Total Assets Turnover (TATO) on Financial Distress Conditions at PT Gajah Tunggal Tbk.

The Effect of Debt to Asset Ratio (DAR) and Total Assets Turnover (TATO) on Financial Distress Conditions at PT Gajah Tunggal Tbk.

Effect of Leverage, Profitability and Operating Capacity on Financial Distress in Manufacturing Companies Listed on The Indonesia Stock Exchange

This study aims to examine whether leverage, profitability and operating capacity affect financial distress in food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange for the period 2019-2023. The data used is secondary data obtained from www.idx.co.id website. Determination of samples in research using porpusive sampling methods with special criteria. The results of the analysis are known to be a significant value of leverage of 0.000 < 0.05 with a calculation of -4.862 < table 1.992, so the variable leverage has a significant negative effect on financial distress conditions. The significant value on profitability is 0.000 < 0.05 with a count of 9,196 > table 1,992. So the probability variable has a significant positive effect on financial distress conditions. Significant value in Operating Capacity of 0.000 < 0.05 with a calculation of 8.422 > table 1.992, So operating capacity has a significant positive effect on financial distress.

Pengaruh Women on Board of Commisioner, Women on Board of Director, Sales Growth dan Board Size, terhadap Financial Distress

This research aims to determine the condition of financial distress and how women on the Board of Commissioners, Women on the Board of Directors, Sales Growth and Board Size influence financial distress using the Altman Z-Score analysis model. The population studied came from the LQ45 company listed on the Indonesia Stock Exchange (BEI) in the 2018-2022 period and samples were taken using a purposive sampling method so that the total number of data studied was 92 samples. This data is taken from the company's financial reports and annual reports which are availableon the BEl website or each company's website. There were several tests carried out inthis research. namely the normality test. classical assumption deviation test, and hypothesis testing. The results of this test show that Women on the Board of Commissioners have no effect on Financial Distress, then Women on the Board of Directors have a positive effect on Financial Distress, while Sales Growth has no effect on Financial Distress and Board Size has a positive effect on Financial Distress. Keywords: Financial Distress, Sales Growth dan Board Size, Women on Board of Commissioner, Women on Board of Director.

Prediksi Financial Distress Model Almant Z-Score, Kinerja Keuangan dan Pengaruhnya terhadap Nilai Perusahaan

The aim of this research is to predict financial distress conditions using the Almant Z-Score model and to test the influence of financial distress and financial performance on company value in basic industrial and chemical sector companies listed on the Indonesia Stock Exchange for the 2017-2021 period. The sample selection technique is purposive sampling method, research data is secondary data obtained from the Indonesia Capital Market Directory for the period 2017 - 2021. The data analysis method used is multiple regression analysis with the eviews 12.0 application tool. The research results show that financial distress and debt to equity ratio (DER) partially do not have a significant effect on company value. Meanwhile, financial performance as proxied by return on assets (ROA) and return on equity (ROE) partially has a positive and significant effect on company value.

Balancing Techniques for Advanced Financial Distress Detection Using Artificial Intelligence

Imbalanced datasets are one of the main issues encountered by artificial intelligence researchers, as machine learning (ML) algorithms can become biased toward the majority class and perform insufficiently on the minority classes. Financial distress (FD) is one of the numerous real-world applications of ML, struggling with this issue. Furthermore, the topic of financial distress holds considerable interest for both academics and practitioners due to the non-determined indicators of condition states. This research focuses on the involvement of balancing techniques according to different FD condition states. Moreover, this research was expanded by implementing ML models and dimensionality reduction techniques. During the course of this study, a Combined FD was constructed using five distinct conditions, ten distinct class balancing techniques, five distinct dimensionality reduction techniques, two features selection strategies, eleven machine learning models, and twelve weighted majority algorithms (WMAs). Results revealed that the highest area under the receiver operating characteristic (ROC) curve (AUC) score was achieved when using the extreme gradient boosting machine (XGBoost) feature selection technique, the experimental max number strategy, the undersampling methods, and the WMA 3.1 weighted majority algorithm (i.e., with categorical boosting (CatBoost), XGBoost, and random forest (RF) having equal voting weights). Moreover, this research has introduced a novel approach for setting the condition states of financial distress, including perspectives from debt and change in employment. These outcomes have been achieved utilizing authentic enterprise data from small and medium Lithuanian enterprises.

Why Does Financial Distress Happen to Companies? (Case Study on Primary Consumer Goods Sector Companies Listed on IDX)

Purpose: This research aims to find out how the influence of liquidity, leverage, probability and sales growth on financial distress conditions. The dependent variable in this study is financial distress. Meanwhile, the independent variables are liquidity, leverage, profitability, and sales growth. Method: The population in this study are primary consumer goods sector companies listed on the Indonesia Stock Exchange during 2018-2022. The samples obtained were 16 companies which were selected using purposive sampling method. The analytical tool used is panel data regression analysis with the help of eviews 10 software. Result and conclusion: The results showed that liquidity and leverage are significantly influenced to financial distress, while profitability and sales growth are not significantly influenced to financial distress. The limitation in this study are the independent variables used were only liquidity, leverage, profitability and sales growth, and the research was only conducted on consumer non- cyclical. Future researchers are expected to use another measure for projecting financial distress, to add independent variables and examine companies other than consumer non-cyclicals and increases the observation period in the study. Research implications: The implication of this research is that the company is expected to increase current assets, controlling external loans, increase profitability and increase sales growth to avoid financial distress.

Penerapan Model Log-Logistik Proporsional Hazard Untuk Menentukan Faktor yang Mempengaruhi Kondisi Financial Distress

<p class="AbstractEnglish">Every company is likely to experience an up or down phase in its financial performance. A decline in financial performance is a condition of financial distress. Financial distress is an event of a continuous decline in a company's financial performance over a certain period of time. The variables in this research are the response variable in the form of the time of company experiences financial distress, while the covariates are the solvency ratio, liquidity ratio, growth ratio, profitability ratio, company size and activity ratio. The aim and objective of the research is to obtain the property and significance of covariates when a company experiences financial distress. How to determine covariates that are significant to financial distress. The model used is a log-logistic proportional hazard regression model. The log-logistic model is a regression model in the form of a maximum extreme function with right asymptotics and non-negative random variables, while the Cox proportional hazards model is a survival model with the independent variables being time and covariates, between time and covariates being independent. The results of this research are that companies in the infrastructure, utilities and transportation sectors experience financial distress, influenced by solvency ratios, liquidity ratios and profitability ratios. The solvency ratio and profitability ratio have a positive effect, while the liquidity ratio has a negative effect on the timing of financial distress. The contribution of these factors to companies experiencing financial distress is 1.1% (for liquidity ratio), 3.4% (for solvency ratio), and 95.5% (for profitability ratio).</p><p class="AbstractEnglish"><strong>Keywords: </strong>financial distress; log-logistic; portional hazard; profitability ratio</p>

ANALISIS MODEL ALTMAN Z-SCORE TERHADAP INDIKASI FINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR SUB SEKTOR KOSMETIK DAN KEPERLUAN RUMAH TANGGA YANG TERDAFTAR DI BURSA EFEK INDONESIA

This study aims to determine the indication of financial distress using the calculation of the Altman Z-Score model in manufacturing companies in the cosmetics and household utilities sub-sector listed on the Indonesia Stock Exchange for the 2018-2022 period. This study will use descriptive research methods with a qualitative approach using research objects, namely as many as 6 manufacturing companies in the cosmetics and household utilities sub-sector listed on the Indonesia Stock Exchange. The results showed that PT. Martina Berto Tbk with an average Z-Score obtained in 2018-2022 of 0.338 (Distress Zone), which means that the company is in a condition of financial distress. Companies with the category of being in standard financial condition (Grey Zone) with an average Z-Score value , namely PT. Mustika Ratu Tbk amounted to (2,642), and PT. Kino Indonesia Tbk amounted to (1,898). While PT. Unilever Indonesia Tbk (3,259), PT. Akasha Wira International Tbk (3,981), and PT. Mandom Indonesia (4,896) shows the average Z-Score in a healthy financial condition (Safe Zone). The conclusion in this study is that the Altman Z-Score model can be used to calculate an indication of the level of financial distress in a company. The results of the calculation analysis of the Altman Z-Score model of companies that are indicated to have financial difficulties are PT. Martina Berto Tbk. Policy carried out by PT. Martina Berto Tbk is business transformation, increasing marketing and promotion, expanding distribution cooperation, and divesting assets. The impact of this policy is that in 2021 the company recorded positive performance improvements

Financial Distress Assessment Through Altman Z-Score

This research aims to assess the financial distress condition of PT Waskita Karya Tbk (WSKT), a state-owned construction company in Indonesia, from 2017 to 2022 using the Altman Z-Score model. The Altman Z-Score combines financial ratios to predict the likelihood of bankruptcy. Secondary data derived from WSKT’s financial statements were analyzed quantitatively using the Z-Score formula for non-manufacturing firms. The findings indicate that WSKT has experienced significant financial distress. In 2017 and 2022, WSKT was in the Distress Zone with scores of 0.96570 and 0.78271 respectively. The company was also in distress in 2020 with a negative score of -1.12303. For 2018, 2019 and 2021, WSKT was in the Grey Zone with scores of 1.51502, 1.05679 and 1.17451. WSKT did not achieve Safe Zone status during the six years examined. Overall, 66.67% of the period reviewed falls in the Distress Zone, predicting a high bankruptcy risk for WSKT. To address this financial vulnerability, recommendations include conducting operational optimization to enhance efficiency and profitability, diversifying business portfolios to tap into promising segments, and proactively monitoring financial health using analytical models like Altman Z-Score. With disciplined implementation of strategies to rectify distressed ratios, WSKT can achieve financial stability.

Analisis Faktor-Faktor Yang Mempengaruhi Financial Distress

The development of the flight companies that continues to increase has also made the level of competition increasingly fierce. There is news that several flight companies are experiencing financial distress conditions, this makes awareness of theimportance of researching whatfinancial ratios have an effect on triggering financialdistress conditions on the flight companies. This study aims to examine the effect of financial ratios consisting of profitability, liquidity and Leverage ratios on financialdistress in Flight Companies in Indonesia. This research is classified into quantitative research with a sampling method that is non-probability sampling. The sample in this study is an flight company listed on the Indonesia Stock Exchange (IDX). The method of analysis in this research is panel data regression test, and the hypothesized relationship in the proposed theoretical model. The results of this study have proven that all of the financial ratio variables tested, namely the ratio of profitability, liquidity and Leverage partially have a significant effect on the financial distress of flight companies.Keywords :Profitability; Liquidity; Leverage; Financial distress

Pengaruh Kepemilikan Institusional, Kepemilikan Manajerial, dan Komisaris Independen terhadap Financial Distress dengan Leverage sebagai Variabel Moderasi

Financial distress conditions have a bad impact on a company, where companies experiencing financial distress conditions can lose the trust of parties who have a relationship with the company. This study aims to analyze and describe the effect of institutional ownership, managerial ownership and independent commissioners on financial distress with leverage as a moderating variable. The population of this study consisted of 86 property and real estate companies for the period 2018-2021 listed on the Indonesia Stock Exchange (IDX). The collection method used was purposive sampling, and 40 company samples were selected. The data analysis technique applied in this study is multiple linear regression analysis and Moderating Regression Analysis (MRA) using IBM SPSS. The results of hypothesis testing show that institutional ownership has a positive effect on financial distress, while managerial ownership and independent commissioners have a negative effect on financial distress. The results of the moderation test in this study indicate that leverage is unable to moderate the effect of institutional ownership, managerial ownership and independent commissioners on financial distress.