Publication Search

This study aims to analyze the prediction of financial distress using the Altman Z-Score, Springate, and Zmijewski methods at PT Sri Rejeki Isman Tbk in 2019-2023. This type of research is descriptive research with a quantitative approach. Using secondary data with documentation techniques and literature studies in the form of related company financial reports, books, articles, journals and other publications related to the research topic. The sampling technique was carried out using a purposive sampling method. The sample in this study was obtained using a purposive sampling technique and obtained as many as 5 financial reports from the company PT Sri Rejeki Isman Tbk for the period 2019-2023. The results of the study show that the results of calculations using the Altman Z-Score method indicate that in 2019-2023 PT Sri Rejeki Isman Tbk experienced fluctuations in the company consistently still in the category of bankruptcy, the Springate method shows that the company experienced a decline in its financial performance, and the Zmijewski method shows that companies that experience fluctuations in financial performance conditions, Although there are fluctuations in the X-Score value and improvements in certain years.

This research is motivated by significant fluctuations and a decline in profits for companies in the clothing and luxury goods subsector listed on the IDX for the period 2021-2023, indicating potential financial difficulties. This research aims to evaluate the company's condition using four prediction models, namely Altman-ZScore, Springate, Fulmer, and Taffler, and to determine the most suitable model for the sector. The method applied is quantitative comparative with a purposive sample of 11 companies, using financial statement data from 2021-2023 and analyzed using the formulas for each predictive model. The research findings indicate that the four models produce different predictions regarding the company's financial condition. Additionally, there are differences in the accuracy levels of the four models. The Springate and Taffler models achieved the highest accuracy rate of 85%, followed by Altman at 67% and Fulmer at 64%. The findings of this study confirm that the Springate model is the most reliable tool for early warning for companies and stakeholders, enabling faster preventive measures to prevent bankruptcy.

Financial distress refers to a company’s persistent inability to meet financial obligations, signaling severe monetary strain that precedes formal bankruptcy or liquidation proceedings. This study investigates the impact of intellectual capital (VAICTM), operational capacity (TATO), capital structure (DER), and operating cash flow (OCF) on financial distress (Altman Z-Score), with profitability (ROA) serving as a mediating variable. The theoretical framework of this research is grounded in signaling theory, agency theory, and resource-based view theory. The study focuses on basic materials companies listed on the Indonesia Stock Exchange (IDX) between 2019 and 2023. The study utilized criterion-based sampling to select qualified respondents. Secondary datasets were analyzed through panel regression and path analysis, with Eviews 12 as the computational tool. Key findings include: (1) intellectual capital and operating capacity demonstrate a statistically significant positive influence on profitability; (2) capital structure exerts a significant adverse impact on profitability; (3) operating cash flow exhibits no statistically discernible impact on profitability; (4) both operating cash flow and profitability are positively and significantly associated with increased financial distress; (5) capital structure displays a significant inverse relationship with financial distress severity; (6) intellectual capital and operating capacity show no statistically significant associations with direct financial distress prediction; (7) profitability partially mediates the influence of intellectual capital, operating capacity, and capital structure on financial distress; and (8) profitability does not serve as a mediating variable between operating cash flow and financial distress.

The purpose of this research was to identify the influence of profitability, debt to equity and sales growth on financial distress in companies listed on the Indonesia Stock Exchange (BEI). The dependent variable tested is financial distress which is calculated using the Altman Z-score. Companies listed on the Indonesia Stock Exchange (BEI) face a number of economic and financial challenges that require careful risk management strategies. One of the main challenges that can threaten business continuity is the risk of financial difficulties. The research applies a purposive sampling method. The research sample consisted of 70 data or the equivalent of 14 companies listed on the IDX in the mining sector for the 2018-2022 period. The data analysis method used is multiple linear regression analysis with SPSS 20 application tools. The results of statistical test research show that profitability has a significant effect on financial distress because the significance value is <0.05, while debt to equity and sales growth have a positive and no effect. significant for financial distress because the significance value is >0.05. The results of the F statistical test show that profitability, debt to equity and sales growth have a significant and equal effect on financial distress because the significance value shows <0.05.

The purpose of this study was to predict the financial difficulties of companies using the Altman Z-Score on companies in the automobile subindustry from 2019 to 2021. This research is qualitative research that uses descriptive methods. The data used in this study is secondary data, namely the financial statements of companies in the car subindustry from 2019 to 2021. The data analysis method used is the Altman Z-Score method by calculating five ratios, namely the ratio of Working Capital to Total Assets (X1), the ratio of Retained Earnings to Total Assets (X2), the ratio of EBIT to Total Assets (X3), the ratio of Market Value of Equity to Book Value of Total Liabilities (X4), and the ratio of Sales to Total Assets (X5). Research findings show that during the 2019-2021 period, there are four companies that are in safe zone conditions, namely PT. Garuda Metalindo Tbk, PT. Indospring Tbk, PT. Multi Prima Sejahtera, and PT. Congratulations. Two companies are in a gray zone condition, namely PT. Astra Internasional Tbk and PT. Astra Otoparts Tbk. Meanwhile, three companies are in crisis zone conditions, namely PT. Gajah Tunggal Tbk, PT. Indomobil Sukses Internasional Tbk, and PT. Prima Alloy Steel Universal Tbk. PT. Indo Kordsa Tbk, in 2019 was in a safe zone condition, in 2020 it was in a gray zone condition, and in 2021 it was in a safe zone condition. PT. Goodyear Indonesia Tbk, in 2019 was in a gray zone condition, in 2020 it was in a crisis zone condition, and in 2021 it was in a gray zone condition. While PT. Multistrada Arah Sarana Tbk, in 2019 was in a crisis zone condition, in 2020 it was in a gray zone condition, and in 2021 it was in a safe zone condition.

Financial distress is a condition whene the company are in a state financial difficultes. Every company must have an early an early warning system to detect the potential for financial distress in order to avoid bankruptcky. The Purpose of this is to analyze and provide empirical evidence regarding the effect profitability (ROA), as a moderating between liquidity (CR), leverage (DAR), sales gowth (SG), in predicting financial distress (Altman Z-Score). The population in this purpose were retail companies on the IDX for the 2016-2020 period, with a sample of 19 companies studied for 5 years so that 95 samples were obtained, using the purposive sampling method. The data used is secondary data in the form of information from the company’s financial statements. The data analysis technique used logistic regression and moderating regretion analysis (MRA). The rsults prove that the variables of liquidity, sales growth and profitability are able to predict financial distress, while leverage cannot predict financial distress, the profitability variable strengthens the influence of liquidity and sales growth in predicting financial distress but weakens leverage in predicting financial distress. The advince given is expected thet the company can increase the effectiveness and efficiency in managing assets and can increase sales so that the profit received by the company increases so that the company can avoid financial distress.

Penelitian ini dilakukan untuk mengetahui kemungkinan terjadinya financial distress pada perusahaan sub sektor transportasi akibat dari adanya dampak pandemic covid-19 pada periode 2020 dengan menggunakan metode Altman Z-Score. Data yang digunakan pada penelitian ini adalah laporan keuangan perusahaan sub sektor transportasi periode 2020 yang diperoleh dari Bursa Efek Indonesia. Penilaian financial distress menggunakan rumus Z-Score Modifikasi atau Model III yang dikemukakan oleh Altman dengan menggunakan 3 kategori kalsifikasi yaitu kategori sehat, rawan atau grey area, dan financial distress. Hasil dari penelitian ini menunjukkan bahwa terdapat 13 perusahaan yang mengalami financial distress, 5 perusahaan berada pada kondisi rawan atau grey area, serta 5 perusahaan yang berada pada kondisi sehat. Variabel-variabel yang digunakan sangat berpengaruh pada hasil perhitungan analisis Altman Z-Score, terutama apabila perusahaan mengalami defisiensi modal maka kemungkinan terjadinya financial distress pada perusahaan juga semakin tinggi.

The purpose of this study is to produce a design to predict, analyze and determine the level of potential bankruptcy of a company using the Altman Z-Score method. Predictions are made by analyzing the financial statements of a company. The research approach used is a qualitative approach. Data analysis technique in this research is descriptive analysis technique. The results of the first phase of research are in the form of a review of bankruptcy prediction analysis using secondary data from banks in Indonesia that are already on the stock exchange and have branch offices in the city of Semarang, while the second year produces an information system design that has added value from the first year to the third year. testing the system that has been designed using actual financial statement data.