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This study aims to examine whether level 1 fair value assets and intangible assets have a significant impact on earnings management within Indonesia's banking service sector. The research sample included 136 foreign exchange banks that reported financial data on the Indonesia Stock Exchange between 2019 and 2022. Data analysis was conducted using multiple linear regression. The findings show a significant effect of level 1 fair value assets on earnings management in Indonesia's banking industry, while no significant effect was found for intangible assets. The study concludes that fair value asset measurements do not influence earnings management, whereas intangible assets do. To support ongoing improvements in financial accounting standards, it is recommended to implement the guidelines from accounting standards 68 (measuring fair value) and 19 (intangible assets), and to comply with the requirements of International Accounting Standards (IAS) 13 and IAS 38. Additionally, continuous enhancements to corporate governance and internal control systems are essential for boosting entity performance, improving financial reporting processes, and increasing earnings quality. This study serves as a preliminary investigation into the effect of intangible assets and level 1 fair value measurements on earnings management in the Indonesian banking sector.

This research aims to examine the effect of dividend policy and accounting conservatism on earnings quality in companies in the infrastructure, utilities & transportation and mining sectors listed on the Indonesia Stock Exchange (BEI). This type of research is quantitative research. The sampling method used is a purposive sampling method based on certain criteria. From the specified criteria, a sample of 25 companies was obtained. The analytical method used is multiple linear regression analysis using IBM SPSS statistics 22. The results of this research indicate that the dividend policy variable has no effect on earnings quality. Meanwhile, accounting conservatism has a significant positive effect on earnings quality. The principle of accounting conservatism is applied by companies on the basis of management's caution against exaggerating the profit value of the financial statements.

The aim of this research is to determine the extent of the influence of Capital Structure (DAR), Company Size (Ln), Investment Opportunity Set (EPS), Leverage (DER), Liquidity (CR) and Profitability (ROA) on the Quality of Profits in banking companies. registered on the IDX in 2019-2021. The method used in this research is a quantitative descriptive method and multiple linear regression analysis, where the population in this research is 46 banks and uses a purposive sampling technique with the sample size being 34 banks registered on the BEI in 2019-2021. Based on the research results, it shows that partially only the variables Company Size (Ln) and Profitability (ROA) have a positive and significant effect on Earnings Quality, while Capital Structure (DAR), Investment Opportunity Set (EPS), Leverage (DER) and Liquidity (CR) has no effect on the Quality of Profits in Banking Companies listed on the IDX in 2019-2021. Simultaneously, the variables Capital Structure (DAR), Company Size (Ln), Investment Opportunity Set (EPS), Leverage (DER), Liquidity (CR) and Profitability (ROA) have a positive and significant effect on the Quality of Profits in Banking Companies listed on the IDX 2019 -2021.

This research was carried out to determine the impact of earnings quality on financial resilience at CV. Rhoda Jaya. The qualitative methodology used in this research is by conducting interviews, observations, notes regarding problems, and other data sources against company informant CV. Rhoda Tiga. The data management stages start with the first data collection, second data triangulation, third Data reduction, fourth, presentation of data and finally, verification and conclusions. For data analysis methodsThe research uses a narrative analysis approach where the researcher constructs a narrative or story from the collected data.