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Tax Management refers to a company’s efforts to manage its tax obligations efficiently and legally in order to optimize net income. This study aims to examine the effect of Fixed Asset Intensity and Leverage on Tax Management, with Profitability as a moderating variable, in mining companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2024 period. This research is conducted because tax management practices are considered to potentially influence corporate profitability and financial performance. The study is grounded in Agency Theory and employs a quantitative approach. The sample was selected using purposive sampling, resulting in 28 companies observed over four years, with a total of 112 secondary data observations obtained from annual reports or financial statements. Data analysis was performed using EViews 13 with a Moderated Regression Analysis (MRA) approach. The findings indicate that: (1) Fixed Asset Intensity has no significant effect on Tax Management; (2) Leverage has a significant negative effect on Tax Management; (3) Profitability does not moderate the relationship between Fixed Asset Intensity and Tax Management; and (4) Profitability strengthens the effect of Leverage on Tax Management.

Micro, Small, and Medium Enterprises (MSMEs) in Indonesia and Malaysia constitute the core drivers of employment and economic growth, yet many remain constrained by limited competitiveness in international markets due to uneven digital adoption. This study addresses the problem of how international digital transformation can be effectively leveraged to enhance the performance and sustainability of Smart MSMEs, with the objective of identifying key digital strategies that support sustainable business development. Employing a mixed-methods approach, the research combines quantitative surveys of MSME actors with qualitative in-depth interviews of business owners who have implemented international digital initiatives, including cross-border e-commerce, global payment systems, and international digital marketing. The data are analyzed using descriptive and comparative techniques to examine enabling factors, challenges, and cross-country differences between Indonesia and Malaysia. The findings indicate that international digital transformation significantly improves market access, operational efficiency, and business resilience, while strategic integration of digital platforms and international networks strengthens long-term sustainability. The study concludes that developing Smart MSMEs through internationally oriented digital transformation is a critical pathway for achieving sustainable business development and enhancing regional and global competitiveness, and it offers strategic and policy-oriented recommendations for MSME stakeholders.

This study explores the integration of adaptive streaming models with edge computing to optimize multimedia delivery, particularly in real-time applications such as video conferencing, live streaming, and virtual reality. The proposed model leverages adaptive compression techniques, including scalable video coding (SVC) and hybrid adaptive compression (HAC), which adjust video quality based on real-time network conditions. The use of edge computing further enhances the model by processing and delivering content closer to the user, reducing latency and optimizing bandwidth usage. The research demonstrates that the edge computing-based adaptive streaming model significantly improves latency by up to 30%, reduces bandwidth consumption, and ensures higher visual quality during video playback, even under fluctuating network conditions. This model addresses key challenges in multimedia streaming, such as maintaining video quality in bandwidth-constrained environments and minimizing buffering times. Furthermore, it enhances the overall Quality of Experience (QoE) for users by providing smoother interactions and real-time responsiveness. The study highlights the potential impact of this model on various fields, including remote education, entertainment, and interactive applications, where low-latency content delivery and high-quality streaming are critical. The findings suggest that integrating AI algorithms for even more efficient compression and expanding edge computing infrastructures will further optimize multimedia streaming in the future, ensuring reliable and high-quality user experiences in increasingly connected environments.

The increasing complexity and scale of modern cybersecurity threats necessitate the development of advanced systems capable of efficiently detecting, analyzing, and mitigating incidents in real time. This paper proposes an automated framework for digital forensics and incident response that leverages big data analytics and real time network traffic profiling. The framework integrates cutting-edge technologies, including Apache Spark for real time data processing and Hadoop for scalable data storage, combined with machine learning models like LSTM and Autoencoders to detect anomalies and threats in network traffic. By automating the process of incident detection and response, this framework significantly reduces the time required to identify threats and improves the accuracy of forensic evidence correlation across heterogeneous network environments. The study highlights the advantages of using machine learning models and big data tools to address the limitations of traditional manual and semi-automated systems, which often struggle to keep pace with large-scale data generation. Testing results demonstrate that the proposed framework can handle large data volumes efficiently, providing real time, actionable insights with significantly reduced response times. Additionally, the framework improves forensic analysis by enabling the correlation of evidence from different devices and protocols, making it more effective than traditional methods in identifying the root cause of security incidents. However, challenges related to data heterogeneity, scalability, and system integration were encountered during testing. The proposed framework holds promise for significantly enhancing the efficiency and effectiveness of cybersecurity operations, with future work focusing on further integration of advanced AI techniques and machine learning models for dynamic and adaptive incident response.

This study investigates the role of Enterprise Information Systems (EIS) in driving innovation within organizations. The research employs a mixed-method approach, combining survey-based structural analysis and in-depth organizational case studies to explore how different EIS capabilities influence organizational innovation. The study focuses on four key EIS capabilities: functional capabilities such as workforce management and customer value creation; technological capabilities including ERP systems and real-time analytics; dynamic capabilities, especially organizational learning; and collaborative innovation through external partnerships. The survey results reveal that EIS capabilities, particularly data analytics and integration, significantly enhance organizational agility, decision-making, and innovation outcomes. In-depth case studies provide detailed insights into how these capabilities are applied in real-world organizational settings, illustrating their impact on process and service innovation. The findings indicate that the effective integration of EIS across organizational functions, along with improved access to data, contributes to operational efficiency and innovation success. However, challenges such as integration issues, resistance to change, and lack of skilled personnel were also identified as barriers to successful EIS adoption. The study contributes to the literature by offering a comprehensive understanding of how EIS capabilities drive innovation and highlighting the importance of organizational culture and leadership in the adoption process. The research provides practical recommendations for organizations to leverage EIS for fostering innovation, such as focusing on EIS integration, overcoming organizational barriers, and ensuring leadership engagement. Finally, the study suggests future research directions, including the refinement of multi-method approaches and the need for longitudinal studies to better understand the long-term impact of EIS on innovation outcomes.

In the context of both public organizations and Small and Medium Enterprises (SMEs), inefficient business processes remain a significant challenge. Fragmented information systems often hinder the optimization of these processes, leading to slower decision-making, redundant efforts, and increased operational costs. This study aims to analyze and optimize business processes by utilizing integrated information systems (IIS), providing a comparative analysis between the two sectors. The theoretical framework explores key theories such as Business Process Management (BPM) and the integration of information systems for process optimization. Previous studies highlight the differences in how IIS implementation impacts the public and SME sectors, noting challenges such as data silos, legacy systems, and resistance to change. A case study analysis methodology was employed to assess the effectiveness of IIS across both sectors. Business Process Modeling (BPMN) was used to visualize business processes before and after optimization, and process performance was measured through key metrics such as time reduction, error rates, and cost efficiency. The results show that IIS integration improved business process efficiency by an average of 28%, with reductions in redundancy and faster decision cycles observed in both sectors. Public organizations benefited from enhanced service delivery and better resource management, while SMEs gained competitive advantages through streamlined operations and increased responsiveness to market demands. The comparison reveals that integrated systems had a greater operational impact than traditional isolated process reengineering methods. Public organizations faced more regulatory and governance challenges, while SMEs leveraged their flexibility for faster integration. Recommendations for both sectors include focusing on overcoming barriers such as resistance to change and investing in system modernization. Future research should explore the long-term effects of IIS integration and further sector-specific comparisons.

This study investigates the relationship between corporate governance characteristics, financial structure, and Enterprise Risk Management (ERM) disclosure in Indonesian non-financial firms. Focusing on manufacturing companies listed on the Indonesia Stock Exchange in 2023, the analysis examines whether board size, the proportion of independent commissioners, and leverage influence the extent of ERM disclosure. Using a quantitative approach, multiple linear regression is applied to secondary data obtained from firms’ annual reports. The findings indicate that board size and the proportion of independent commissioners do not have a significant effect on ERM disclosure, while leverage exhibits a positive and significant relationship. This result suggests that firms with higher debt levels are more inclined to enhance risk disclosure as a mechanism to address information asymmetry and demonstrate accountability to investors and creditors. The study contributes to the ERM and corporate governance literature by providing evidence from an emerging market setting and highlighting the practical importance of financial structure in shaping risk transparency, offering relevant insights for corporate decision-makers and regulators to strengthen sustainable risk management practices.

This study aims to analyze the effect of sustainability report disclosure, audit committee meeting frequency, liquidity, leverage, and total asset turnover on profitability in mining companies listed on the Indonesia Stock Exchange (IDX) during the 2021–2023 period. Profitability is measured using Return on Equity (ROE). This research adopts a quantitative approach using secondary data obtained from annual financial statements and sustainability reports. The sample was selected using purposive sampling, yielding 34 mining companies with 102 observations in total. Multiple linear regression analysis was employed after fulfilling classical assumption tests. The results indicate that sustainability report disclosure, audit committee meetings, liquidity, leverage, and total asset turnover simultaneously have a significant effect on profitability. However, partially, total asset turnover has a positive and significant impact on profitability. Meanwhile, sustainability report disclosure, audit committee meeting frequency, liquidity, and leverage do not significantly affect profitability. These findings suggest that asset utilization efficiency plays a crucial role in improving profitability in the mining sector. This study is expected to provide insights for companies, investors, and regulators to understand the determinants of profitability better and to support improved corporate governance and financial decision-making in mining companies.

This study aims to evaluate the effects of profitability, leverage, liquidity, and cash-flow shocks on the financial distress of companies in the hotel, restaurant, and tourism subsector listed on the Indonesia Stock Exchange during the period 2021 to 2024. The research approach employed is quantitative, using logistic regression analysis. The data analyzed are secondary data obtained from the annual financial statements of the respective companies. The results of the study indicate that, simultaneously, the four independent variables significantly influence financial distress. However, based on partial testing, each variable, namely Return on Assets (ROA), Debt to Equity Ratio (DER), Current Ratio (CR), and cash flow shock, does not show a significant relationship with financial distress. These findings imply that the risk of financial distress in this industry cannot be explained solely through a single financial indicator; instead, a more holistic approach is required. This study provides essential contributions to both management and investors in assessing companies' financial condition and formulating appropriate strategic decisions.

This study aims to analyze the effect of profitability, leverage, and liquidity on firm value in food and beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2024 period. Profitability is measured by Return On Assets (ROA), leverage by Debt to Equity Ratio (DER), and liquidity by Current Ratio (CR), while firm value is proxied by Price to Book Value (PBV). The study employs a quantitative approach using multiple linear regression analysis. The sample consists of 25 companies selected through purposive sampling, with a total of 125 secondary data observations obtained from annual financial statements. The results indicate that, partially, profitability, financial risk, and liquidity have a positive and significant effect on firm value. Simultaneously, the three independent variables also significantly affect firm value, with an adjusted R² of 43.4%, meaning that 56.6% of the variation in firm value is explained by other factors outside the model. These findings support agency theory and signaling theory, which suggest that strong financial performance, optimal debt management, and adequate liquidity provide positive signals to investors, thereby enhancing firm value.

This study examines how company size, asset growth, tangibility, leverage, and total asset turnover affect profitability in consumer manufacturing companies listed on the Indonesia Stock Exchange from 2019 to 2023, using secondary data collected via purposive sampling. The independent variables in this study include the natural logarithm of total assets, asset growth (this year’s total assets relative to the previous year), and tangibility (the fixed asset ratio to total assets). Leverage uses the debt-to-asset ratio, and total asset turnover uses the total asset turnover ratio, while the dependent variable of profitability uses return on assets. Of the 108 companies in the population, 19 that met the research sample criteria were selected, yielding 95 observations. Data analysis was conducted using multiple linear regression, accompanied by classical assumption tests and hypothesis testing through F-tests and t-tests. The findings of this study reveal that asset growth has a significant positive effect on profitability, while leverage shows a significant negative effect. However, firm size, tangibility, and total asset turnover do not exhibit significant relationships with profitability. This study contributes both theoretically and practically to understanding the internal determinants of financial performance in the consumer sector and serves as a reference for management.

This study aims to analyze the effect of asset growth, capital structure, and asset structure on the profitability of PT Astra Graphia Tbk during the period 2016–2023. The research employs a quantitative approach with a causal research design using secondary data derived from the company’s quarterly financial statements. A total of 32 quarterly observations were selected through purposive sampling. Profitability is measured using Return on Equity (ROE), while data analysis is conducted using multiple linear regression. Prior to hypothesis testing, classical assumption tests including normality, multicollinearity, heteroskedasticity, and autocorrelation tests were performed to ensure the robustness of the regression model. The results indicate that asset growth, capital structure, and asset structure simultaneously have a significant effect on firm profitability. However, partially, only asset structure has a significant effect on profitability, while asset growth and capital structure show no significant influence. These findings suggest that efficient asset composition plays a more critical role in improving profitability than mere asset expansion or increased leverage. The managerial implication of this study highlights the importance of optimizing asset structure to enhance the firm’s ability to generate sustainable profits.

The digital era demands that organizations be fast-moving, adaptable, and innovative. With the advancement of information technology, changes in work methods, global competition, and stakeholder demands are becoming increasingly complex. Knowledge Management (KM) plays an important role as a strategic mechanism for identifying, acquiring, storing, sharing, and utilizing knowledge to improve organizational effectiveness and efficiency. In this context, knowledge management becomes one of the important elements for organizations to enhance performance. Knowledge management is not just about collecting data or information, but how organizations can store, share, create, and utilize knowledge to gain a competitive advantage. This article aims to analyze the importance of knowledge management for organizational performance in the digital age, including how the digital era changes the dimensions of knowledge management, how knowledge management contributes to organizational performance, the challenges faced, and their implications. The data obtained for this study were gathered from observations thru interviews with relevant parties and a literature review study by examining the results of empirical research from the past five years (2020–2025). The method used was descriptive literature analysis of 15 scientific articles from accredited national journals. The analysis focuses on the relationship between knowledge management dimensions (knowledge creation, storage, sharing, and application) and organizational performance indicators (financial performance, innovation, productivity, and customer satisfaction). The study results show that the implementation of knowledge management significantly contributes to improving organizational performance, both directly thru increased efficiency and effectiveness of work processes, and indirectly thru strengthening a culture of innovation and organizational learning. This article asserts that an organization's success in the digital age is not solely determined by its ability to adopt technology, but also by its ability to manage and leverage knowledge as a strategic resource. Therefore, knowledge management needs to be systematically integrated into the organization's digital strategy, accompanied by strengthening a learning culture, human resource training, and adaptive information technology systems.

This study aims to determine the effect of green accounting on firm profitability, with firm size, leverage, and liquidity as moderating variables. This research employs a quantitative approach using secondary data analysis derived from annual reports and sustainability reports of energy firms listed on the Indonesia Stock Exchange (IDX) during the 2021–2024 period. The study applies multiple regression analysis. The sampling method used is non-probability sampling with a purposive sampling technique, resulting in 170 observations. The data collection method uses documentation techniques. The results show that green accounting and firm size have a positive effect on profitability, while leverage and liquidity have no effect on profitability. These findings provide important insights into the role of green accounting and firm size in encouraging firms to obtain legitimacy, which can enhance profitability through disclosures in financial reports. The implications of this study demonstrate the application of legitimacy theory and provide benefits to relevant parties, particularly firms and stakeholders associated with the firm, in paying attention to the presentation of high-quality annual and sustainability reports.

The size of the company as a moderator in defining the correlation between capital structure, profit, and firm value is the focus of this study. Adopting a quantitative associative approach, this research focuses on the non-cyclical consumer sector registered on the Indonesia Stock Exchange (IDX) for the period 2020–2023. Of the 125 companies, 73 were purposively selected to create the research sample, yielding 292 observations after excluding entities with incomplete data and those with special monitoring status. The authors gathered secondary data from audited yearly financial reports through the IDX portal and corporate websites. The analysis used quasi-moderation techniques by combining independent variables, moderation, and interaction in a single regression model, processed through EViews 13. The research results show that capital structure has a significant positive impact on firm value, while profitability has no significant impact. Firm size has been shown to affect the relationship that exists between capital structure and firm value, but it does not moderate the association between profitability and firm value. These findings confirm that leverage’s effectiveness in increasing firm value is independent of company size and that profitability is not a primary determinant in this context. This research provides empirical evidence to advance capital structure theory and to inform executives’ strategic financial decisions and investors’ evaluations of corporate outlooks.

This study aims to analyze the effect of profitability, liquidity, and asset structure on the capital structure of banking companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period, with firm size as a moderating variable. The research employs a quantitative approach using secondary data obtained from financial statements. The sample was determined through a purposive sampling technique, resulting in 27 banking companies that met the criteria. Data were analyzed using multiple regression analysis and Moderated Regression Analysis (MRA). The results reveal that profitability has a negative and significant effect on capital structure, indicating that banks with higher profitability tend to reduce their dependence on external financing. In contrast, liquidity and asset structure do not have a significant effect on capital structure, suggesting that these factors are less influential in determining debt policy within the banking sector. Furthermore, the MRA results demonstrate that firm size moderates the relationship between profitability and capital structure, implying that larger firms can better manage internal funds to reduce leverage. However, firm size does not moderate the effects of liquidity and asset structure on capital structure. These findings contribute to understanding capital structure determinants in the Indonesian banking industry.

Competition in the songkok (traditional cap) industry in Gresik Regency has become increasingly intense, especially for small enterprises such as UD. Arif Bersaudara, which face challenges in maintaining competitiveness amid changing market trends and consumer preferences. This study aims to analyze effective marketing strategies for UD. Arif Bersaudara by identifying internal and external factors and determining the most appropriate strategic priorities for business development. The research employs the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to identify strategic factors and the QSPM (Quantitative Strategic Planning Matrix) to determine the order of strategic priorities. Data were collected through questionnaires distributed to 92 respondents and analyzed quantitatively using weighting and attractiveness score calculations. The results show that the total IFE Matrix score is 4.80 and the EFE Matrix score is 4.772, placing UD. Arif Bersaudara in the “Grow and Build” strategic position. Based on the QSPM results, the main priority strategy is to leverage superior product quality, design variations, and size diversity to capture opportunities in digital and international markets, with the highest TAS value of 8.37. The study concludes that UD. Arif Bersaudara should focus its strategy on improving product quality and implementing digital marketing to strengthen competitiveness. The strength of this research lies in the application of the combined SWOT–QSPM methods, which provide measurable analytical results, while its limitation lies in the relatively small and region-specific number of respondents. Future research is recommended to expand respondent coverage and incorporate digital marketing–based analysis to make MSME marketing strategies more adaptive to technological developments.

A competitive company is basically a company that is able to maintain consistency and stability of profits in various business activities, without having to commit acts of fraud that can harm internal and external parties. Achieving high-quality profits is an important indicator of the company's sustainability because it reflects management's ability to effectively manage assets, resources, and business strategies. In the context of this study, the main focus is directed to the effect of leverage, liquidity, and profitability on the quality of profit with the size of the company as a variable of moderation. The study was conducted on food and beverage subsector manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the period 2019 to 2023. The research method used is quantitative with analytical descriptive approach. The selection of samples was carried out by purposive sampling technique so that 25 companies were obtained as samples with a total of 125 financial statement data for five years of observation. Based on the results of the analysis, it was found that leverage, liquidity and profitability have a negative and significant influence on the quality of profit. This finding shows that the higher the three variables, the quality of profit actually decreases. Furthermore, the results revealed that the size of the company is not able to moderate the relationship between leverage, liquidity, and profitability to the quality of profit.

This study aims to analyze the effect of profit growth, liquidity, and Leverage on profit quality with company size as a moderation variable in manufacturing companies listed on the Indonesia Stock Exchange for the 2019-2023 period. This research is based on the importance of profit quality as an indicator of real financial performance, as well as the phenomenon of profit management practices that can reduce the quality of financial information. The research method used was quantitative with a causal and associative approach, using secondary data from the financial statements of 65 manufacturing companies over five years. Data analysis techniques include multiple linear regression analysis and moderated regression analysis (MRA) with the help of SPSS software. The results show that profit growth, liquidity, and Leverage have a significant negative effect on the quality of profit. This indicates that the increase in these three variables tends to decrease the quality of profits, which is likely due to profit management practices to maintain the company's financial image. In addition, company size is not able to moderate the relationship between profit growth, liquidity, and Leverage to profit quality. These findings imply that the scale of the company does not affect the strength of the relationship between these variables and the quality of profits. This research makes a theoretical contribution in enriching the accounting literature regarding the factors that affect the quality of profits and the role of company size. Practically, the results of the research can be a reference for company management and investors in improving the transparency and quality of financial reporting.

The rapid growth of digital technology has revolutionized marketing practices, with social media becoming a primary platform for brand communication and audience engagement. Shopee Indonesia, as one of the leading e-commerce platforms in Southeast Asia, leverages various social media channels to strengthen its brand presence and connect with consumers. This study examines Shopee's digital marketing strategy through the management of the @notapprovedyet social media account, which creatively promotes Shopee products based on current social trends. The main focus of this study is to explain the content creation process and analyze the performance of accounts on Instagram, TikTok, and YouTube managed by Shopee Indonesia's Content Marketing Division. Using a creative marketing approach, this study aims to provide insights into effective social media management. The research findings are expected to contribute to understanding how the right social media strategy can increase audience engagement and brand awareness, especially in the highly competitive e-commerce industry.