This study aimed to examine the effect of Financial target (ROA), Ineffective monitoring (IND) and Total accrual (TATA) on Financial distress. The research method used in this research is a quantitative method. Data collection techniques are carried out using documentation techniques. The population used in this research is Sharia Commercial Banks registered with the Financial Services Authority in 2018-2022 using a purposive sampling method, so the number of samples for this research is 60 financial report data from Sharia Commercial Banks registered with the Financial Services Authority for 5 years. Data was obtained by collecting data from the annual financial reports of Sharia Commercial Banks on each company's website. The data analysis technique used is logistic regression analysis which has previously passed the multicollinearity test, model suitability test and hypothesis testing using SPSS software for windows. The research results show that Financial target(ROA) has a significant influence on financial distress, while Ineffective monitoring (IND) and Total Accruals (TATA) do not have a significant influence on financial distress. And simultaneously Financial target (ROA), Ineffective monitoring (IND) and Total accrual (TATA) have a significant effect on financial distress in Islamic commercial banks, with a Nagelkerke R Square value of 17.8%.

This research aims to empirically test the partial and simultaneous influence between the independent variables profitability, firm size and financial leverage with the dependent variable income smoothing in BUMN Go Public companies on the Indonesia Stock Exchange for the period 2018 to 2022. The population in this study is all BUMN Go Public companies listed on the Indonesia Stock Exchange totaling 20 companies with 5 years of observation. The research method used is a quantitative method with secondary data originating from the company's financial reports. The sampling technique used was simple random sampling with the final sample results being 80 total samples. The data analysis techniques used are descriptive statistical analysis, classic multicollinearity assumption test, overall model test, model feasibility test, classification matrix, logistic regression analysis, and hypothesis testing. The data was processed with the help of Eviews version 12 software. This research shows the following results: (1) Partially, the profitability variable has a significant positive effect on income smoothing. (2) Partially, the firm size variable has a significant negative effect on income smoothing. (3) Partially, the financial leverage variable has no effect on income smoothing. (3) Simultaneously all independent variables, profitability, firm size, and financial leverage are proven to have an effect on income smoothing.