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The adoption of PSAK 116 changes the accounting treatment of leases by recognising right-of-use assets and lease liabilities, replacing operating lease expenses with depreciation and interest. These changes have a direct impact on ability-to-pay financial ratios such as Debt Service Coverage Ratio (DSCR) and Net Debt to EBITDA. This study analyses the financial statements of PT Mitra Adiperkasa Tbk (MAPA) for 2019-2024 using a descriptive-comparative and simulation approach in case PSAK 116 is not applied. The results show a technical increase in EBITDA due to PSAK 116, which has an effect on the apparent improvement of DSCR and Net Debt to EBITDA. Simulations using the PSAK 30 approach show more conservative and realistic ratios. These findings highlight the importance of understanding the impact of accounting standards on ratio interpretation and credit decision-making.

This study aims to analyze and compare the financial performance of PT Asuransi Dayin Mitra Tbk and PT Asuransi Jasa Tania Tbk in 2023 using the DuPont analysis method. The data used in this study are the financial statements of both companies for the year ended December 31, 2023. The analysis was conducted by calculating the net profit margin (NPM), total asset turnover (TATO), financial leverage (EM), and return on equity (ROE) of each company. The results indicate that PT Asuransi Dayin Mitra Tbk achieved better financial performance with an ROE of 5.66%, while the ROE of PT Asuransi Jasa Tania Tbk was only 1.24%. PT Asuransi Dayin Mitra Tbk outperformed in TATO and EM, whereas PT Asuransi Jasa Tania Tbk demonstrated a higher NPM. These findings provide practical implications for insurance company management and investors in decision-making processes. However, this study has limitations in terms of sample size, time period, and its focus on financial factors. Further research is needed to explore non-financial factors influencing the performance of insurance companies.

This study aims to examine in depth the influence of financial variables consisting of Current Ratio (CR), Return on Equity (ROE), Debt to Equity Ratio (DER), and Earning per Share (EPS) on Stock Returns in primary consumer sector companies listed on the Indonesia Stock Exchange (IDX) during the 2018–2022 period. This study uses a quantitative approach by utilizing secondary data in the form of annual reports published through the official websites of each company and the Indonesia Stock Exchange page, so that the data used can be accounted for its validity. Sample selection was carried out through a purposive sampling technique with certain criteria resulting in 15 sample companies with a total of 75 observation data which were then analyzed using Eviews 13 statistical software. The analysis focused on partial and simultaneous relationships between variables to determine how much each factor contributed to the movement of Stock Returns. The results showed that the Current Ratio had no significant effect on Stock Returns with a probability value of 0.4079, so that company liquidity in the short term was not a major determining factor for investors. Return on Equity also did not show a significant effect with a probability value of 0.2591, indicating that the company's efficiency in generating profits from shareholder equity has not been a consistent benchmark for investment returns. Conversely, the Debt to Equity Ratio was shown to have a significant negative effect on Stock Returns with a probability value of 0.0053, meaning that the higher the company's leverage level, the greater the risk borne, thus implying a decrease in investor interest and a decrease in returns. Earnings per Share also did not have a significant effect on Stock Returns with a probability value of 0.2989, indicating that although EPS is one of the fundamental indicators, in the context of this research period its effect was inconsistent on the returns received.

The integration of autonomous systems in traffic management has become increasingly important as urban populations and vehicle numbers continue to rise, leading to significant congestion. Traditional traffic signal control systems, which rely on fixed timing, are no longer sufficient to handle the dynamic and complex nature of urban traffic. To address these challenges, the proposed explainable Deep Reinforcement Learning (DRL) framework aims to optimize traffic signal control by dynamically adjusting traffic signals based on real-time data. This approach enhances traffic flow efficiency, reduces congestion, and improves overall system performance. The framework leverages Vehicle-to-Everything (V2X) communication, which enables real-time data exchange between vehicles, infrastructure, and other road users, extending the perception range of autonomous vehicles and providing valuable insights for traffic signal optimization. Additionally, the integration of smart infrastructure, such as smart intersections, plays a crucial role in enabling adaptive traffic management and facilitating better coordination across multiple intersections. One of the key advantages of the proposed system is its transparency, achieved through the implementation of explainable AI (XAI) techniques. These mechanisms provide clear insights into the decision-making processes, ensuring that traffic management authorities and system users can understand the rationale behind the system’s decisions. Although challenges such as data accuracy, scalability, and cybersecurity risks remain, the proposed DRL framework shows great promise in revolutionizing traffic management systems. Future research directions include enhancing data collection methods, improving the scalability of the system for larger cities, and further developing explainability features to improve trust and adoption in real-world applications.

This study aims to analyze the effect of leverage, liquidity, and company size on profitability in food and beverage companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period. Testing was conducted both partially and simultaneously to obtain a comprehensive picture of the relationship between variables. This study uses a quantitative approach with a sample of 14 companies selected through a purposive sampling method based on certain criteria, such as the completeness of annual financial reports during the study period and the availability of relevant data. The data used are secondary data obtained from the official IDX website (www.idx.co.id), including annual financial reports containing information on total assets, total liabilities, total equity, financial ratios, and the company's profit level. Data analysis was carried out using the multiple linear regression method using SPSS version 26 software, so that the effect of each independent variable on the dependent variable can be tested both individually and together. The results of the study indicate that simultaneously, the variables leverage (X1), liquidity (X2), and company size (X3) have a significant effect on profitability (Y). However, partial test results revealed that leverage had a negative and significant effect on profitability, indicating that a high proportion of debt can reduce a company's ability to generate profits. Meanwhile, liquidity and company size were not shown to have a significant influence on profitability, suggesting that these factors are not the main determinants of profit performance in this sector. This study implies that food and beverage company management needs to carefully consider capital structure to maintain profitability. For further research, it is recommended to add other variables such as operational efficiency, sales growth, and dividend policy, as well as extend the observation period for more in-depth and representative analysis results.

This paper explores the application of quantum-inspired optimization algorithms in the training of large-scale Graph Neural Networks (GNNs) within distributed cloud-edge environments. GNNs have gained significant attention due to their ability to model complex relationships in graph-structured data, yet their training presents challenges such as high computational demand, inefficient resource allocation, and slow convergence, especially for large datasets. Traditional meta-heuristic algorithms, while useful, often face scalability and performance issues when applied to such large-scale tasks. To address these challenges, we propose a quantum-inspired meta-heuristic algorithm that leverages quantum principles, such as superposition and entanglement, to enhance optimization processes. The algorithm was integrated into a hybrid cloud-edge system, where computational tasks are dynamically distributed between edge nodes and the cloud, optimizing resource utilization and reducing latency. Our experimental results demonstrate significant improvements in training speed, resource efficiency, and convergence rate when compared to traditional optimization methods such as Genetic Algorithms and Simulated Annealing. The quantum-inspired algorithm not only accelerates the training process but also reduces memory usage, making it well-suited for large-scale GNN applications. Furthermore, the system's scalability was enhanced by the hybrid cloud-edge architecture, which balances computational load and enables real-time data processing. The findings suggest that quantum-inspired optimization algorithms can significantly improve the training of GNNs in distributed systems, opening new avenues for real-time applications in areas such as social network analysis, anomaly detection, and recommendation systems. Future work will focus on refining these algorithms to handle even larger datasets and more complex GNN architectures, with potential integration into edge devices for enhanced real-time decision-making.

This study examines the factors that influence financial distress in companies affiliated with Israel, focusing on the roles of profitability, liquidity, leverage, sales growth, and firm size. The research is driven by the phenomenon of boycotts caused by geopolitical conflicts involving Israel, which have impacted the financial performance of several companies, particularly in Indonesia. The study uses a quantitative approach, analyzing a sample of companies listed on the Indonesia Stock Exchange (IDX) that are affiliated with Israel during the 2023-2024 period. The data consists of quarterly financial statements, which are analyzed using the Altman Z-Score bankruptcy prediction model. The findings show that profitability and liquidity have a significant effect on financial distress, while leverage and sales growth have a smaller impact. Firm size is also found to reduce the risk of financial distress. These results suggest that companies linked to Israel are more vulnerable to financial risks due to boycotts triggered by international political tensions.

This study examines the influence of leverage, profitability, and capital structure on earnings management in consumer non-cyclicals companies listed on the Indonesia Stock Exchange (IDX) during the period 2019–2023. Earnings management has become a central issue in financial reporting, as it reflects managerial discretion in presenting financial information that may not fully align with the company’s actual economic condition. Understanding the determinants of earnings management is therefore essential to enhance transparency, credibility, and stakeholder trust in corporate financial reports. The research employed a quantitative approach using multiple linear regression analysis, with data processed through SPSS version 25. The sample consisted of 104 company-year observations, which were selected using purposive sampling techniques and subsequently refined through outlier testing to ensure data validity and reliability. The independent variables analyzed were leverage, profitability, and capital structure, while earnings management served as the dependent variable. The empirical findings demonstrate that leverage and profitability exert a significant influence on earnings management practices. Specifically, companies with higher leverage tend to engage in earnings management as a mechanism to meet financial obligations and reduce the risk of violating debt covenants. Similarly, higher profitability motivates managers to manipulate earnings in order to sustain investor confidence and maintain a favorable corporate image. In contrast, capital structure is found to have no significant effect on earnings management, indicating that financing decisions between debt and equity may not directly influence managerial behavior in financial reporting. These results highlight the importance of monitoring leverage and profitability indicators as potential predictors of earnings management. For corporate management, the findings suggest the need to implement stronger internal control systems and uphold ethical financial practices. For investors and regulators, the study provides useful insights into assessing company performance beyond reported earnings, thereby supporting more informed decision-making and promoting the integrity of capital markets.

This study investigates the forms and functions of language registers across diverse social contexts, including traditional markets, professional communities, digital media, and podcasts, through a literature review of ten scholarly articles published in accredited journals between 2021 and 2025. Employing a descriptive qualitative approach, the data were analyzed to identify linguistic variations that reflect specific social contexts, situations, and communicative purposes, aligned with Halliday’s (1978) concept of register, which emphasizes language adaptation to social contexts. The findings indicate that register forms encompass specific words, phrases, abbreviations, acronyms, and reduplications. Their communicative functions include instrumental, interactional, representational, and regulative roles, which enhance communication efficiency and preserve cultural identity. This study provides insights for researchers, educators, and practitioners to leverage registers in contextual communication.

PT Bank BTPN Syariah is one of the banks with a mission to provide access, education, and guidance to MSMEs spread across Indonesia. PT Bank BTPN Syariah invites students from public and private universities to join the Bestee program. Currently, PT Bank BTPN Syariah has empowered 37,311 MSMEs in 682 sub-districts spread across Indonesia. The entrepreneurial mentoring conducted by students as facilitators is part of PT Bank BTPN Syariah's mission. In the Bestee program, students act as facilitators, providing mentoring activities to SME entrepreneurs to expand market access both online and offline. The mentoring and empowerment activities for SME operators were conducted at the homes of PT Bank BTPN Syariah customers in Medan, specifically in the sub-districts of Medan Johor, Medan Labuhan, and Medan Timur, from March to May 2025. The first stage involved customer assessment. The second stage involved delivering instructional materials during the second week of mentoring. The third phase involves reviewing and practicing the material taught in the previous meeting. The fourth and final phase is the closing session, where the facilitator assists customers in enhancing their knowledge to maximize business development, leverage marketing technology, and provide crucial information on business identity, promotion, business diversification, excellent service, licensing, financial record-keeping, and appropriate partner materials.

This study aims to determine the effect of leverage on financial performance and the effect of financial distress risk on the relationship between leverage and financial performance. The population in this study is several oil, gas, & coal sub-sector companies listed on the Indonesia Stock Exchange in 2020, 2021, 2022, and 2023. This study uses secondary data. The sampling technique uses the simple purposive sampling method, resulting in 57 companies as samples for 4 years. This study uses Moderated Regression Analysis as the data analysis technique. The results of the study show that leverage has a negative effect on financial performance, and financial distress risk is able to strengthen the relationship between leverage and financial performance.

Carbon emission disclosure is increasingly important for companies in establishing legitimacy, enhancing stakeholder trust, and drawing public attention to sustainability issues. This study aims to examine how profitability, leverage, and company size affect carbon emission disclosure. The research is grounded in legitimacy theory and stakeholder theory, which provide the theoretical foundation for understanding corporate carbon disclosure behavior. The population of this study comprises energy companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2023 period. The sample was selected using non-probability purposive sampling, resulting in 113 observations. Data were analyzed using SPSS with multiple linear regression techniques. The results indicate that profitability and company size have a positive influence on carbon emission disclosure, while leverage does not have a significant effect. Theoretically, the findings support the notion that profitability and company size drive carbon disclosure, in line with legitimacy and stakeholder theories.

This study aims to analyze the effect of sales growth, liquidity, and leverage on tax avoidance in food and beverage companies listed on the Indonesia Stock Exchange (BEI) during the period 2021-2023. Using a sample of 10 companies, this research collected financial data and annual reports to evaluate the relationship between these variables. The results of analysis indicate that sales growth and leverage have a significant effect on tax avoidance. Furthermore, the simultaneoustest results how that three variables collectively have a significant effect on tax avoidance. This study provides insights for stakeholders in understanding the dynamics of taxation within this industry and highlights the importance of considering other financial factors that may influence tax avoidance

The timeframe of financial statement publication refers to the interval between the end of the financial reporting period and the date the report is made available to the public. Prompt and timely publication of financial statements reduces information asymmetry between agents and principals. This study aims to provide empirical evidence on the effect of profitability and leverage on the timeframe of financial statement publication. The research was conducted on all companies listed on the Indonesia Stock Exchange (IDX) during the 2023 period. Industry type was used as a control variable. The sample was determined using a non-probability sampling method with a purposive sampling technique, resulting in 788 observations. The data were analyzed using multiple linear regression. The results show that profitability has a negative effect on the timeframe of financial statement publication, while leverage has no significant effect

This study aims to determine the effect of profitability, liquidity, and leverage on financial distress of tourism sector companies listed on the Indonesia Stock Exchange for the period 2018-2023. The number of companies used as samples was 32 companies with certain criteria. The sampling technique used purposive sampling, so that the total analysis units in this study were 192. Multiple linear regression analysis was used in the analysis of this research data. The results of the study indicate that profitability, liquidity, and leverage have a positive effect on financial distress. Thus, it can be concluded that the overall results of this study are that profitability, liquidity, and leverage can influence financial distress.

TikTok has transformed into an effective digital marketing platform, not only for introducing products but also for shaping impulsive shopping behavior. This study aims to analyze the impulsive shopping behavior of Generation Z on TikTok Shop. The research was conducted using a qualitative descriptive approach, with data obtained from digital searches and observations. The findings indicate that Generation Z has a strong interest in utilizing the TikTok Shop feature within the TikTok application, making it one of their preferred alternatives for online shopping transactions. TikTok significantly influences Generation Z’s shopping behavior, as they tend to purchase products after seeing them on the platform. Businesses leverage TikTok as an efficient marketing tool, particularly through creative content, short videos, and influencer recommendations. By utilizing an algorithm that tailors content to users’ preferences, TikTok Shop creates offers that appear attractive to consumers. Generation Z is often influenced to buy items they do not actually need. Sudden purchases driven by emotions—such as low prices or limited-time offers—often lead them to overlook product quality. As a generation living in the digital era, Gen Z needs to better regulate their impulsive consumer behavior. Wisely utilizing technology and understanding the marketing strategies used by platforms like TikTok Shop can help them avoid excessive impulsive spending. By prioritizing needs over wants and carefully considering the value and benefits of a product before purchasing, Gen Z can become smarter and more responsible consumers.

The rapid growth of the beauty industry, particularly in Indonesia, has created a potential market for entrepreneurs while simultaneously intensifying business competition. Aligned with the development of the internet and information technology, companies are encouraged to leverage these advances through advertising on social media, including platforms such as TikTok. One local cosmetic brand that utilizes TikTok for product promotion is Dear Me Beauty. This phenomenon has led to a study that examines the mediating role of brand awareness in the relationship between advertising appeal and purchase intention. The purpose of this research is to analyze the influence of advertising appeal and brand awareness on the purchase intention of Dear Me Beauty’s cosmetic products, and to investigate the mediating role of brand awareness in that relationship. This study was conducted in Denpasar City with a sample size of 100 respondents using a non-probability sampling method and purposive sampling technique. The analysis techniques employed include descriptive analysis and inferential analysis, specifically path analysis and the Sobel test. The results show that advertising appeal has a positive and significant effect on purchase intention; advertising appeal has a positive and significant effect on brand awareness; brand awareness positively and significantly influences purchase intention; and brand awareness mediates the effect of advertising appeal on purchase intention for Dear Me Beauty products.

This research is a literature study that aims to identify and analyze the elements that influence tax avoidance practices in trading sector companies. Tax avoidance is a strategy taken by companies to minimize the tax burden that must be paid. Although legal, it often raises ethical debates and has an impact on the country's foreign exchange earnings. The research method used in this study is a literature review of various scientific journals and relevant publications that discuss the determinants of tax avoidance, especially in the trade sector. This research takes data from various sources that have been indexed by SINTA. Researchers searched for all relevant data until it was classified into nine relevant sources and discussed in this study. The following factors that affect tax avoidance include leverage on tax avoidance, profitability on tax avoidance, and company size on tax avoidance. The results of the study indicate that leverage, profitability, and company size affect the practice of tax avoidance. This study provides insight for stakeholders, such as the government and investors, in understanding the characteristics of companies that tend to practice tax avoidance, as well as a basis for formulating more effective tax policies.

This study aims to evaluate the financial performance of PT Jasa Marga (Persero) Tbk during the period 2021 to 2024 in an effort to assess the effectiveness of financial management within the infrastructure sector. The main focus of the study is to determine whether there has been an improvement in financial performance based on relevant financial indicators. The analysis was conducted using a descriptive quantitative approach based on the company’s published annual financial statements. The results indicate that, in general, PT Jasa Marga has experienced a significant improvement in financial performance over the past four years. This is reflected in improved liquidity, solvency, profitability, and activity ratios. The increase in toll revenue, as the company’s main source of income, along with profit growth and operational efficiency, serve as key indicators of the success of management strategies in addressing post-pandemic challenges and expanding national toll road projects. Additionally, improved debt management is evidenced by the declining leverage ratios year after year. These findings support the hypothesis that there has been an improvement in financial performance during the observation period.

Carbon emission disclosure is increasingly important for companies in establishing legitimacy, enhancing stakeholder trust, and drawing public attention to sustainability issues. This study aims to examine how profitability, leverage, and company size affect carbon emission disclosure. The research is grounded in legitimacy theory and stakeholder theory, which provide the theoretical foundation for understanding corporate carbon disclosure behavior. The population of this study comprises energy companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2023 period. The sample was selected using non-probability purposive sampling, resulting in 113 observations. Data were analyzed using SPSS with multiple linear regression techniques. The results indicate that profitability and company size have a positive influence on carbon emission disclosure, while leverage does not have a significant effect. Theoretically, the findings support the notion that profitability and company size drive carbon disclosure, in line with legitimacy and stakeholder theories.