In the era of data-driven digital commerce, Artificial Intelligence (AI)-based product personalization has become a key strategy to enhance user experience and foster customer loyalty. However, in the Indonesian e-commerce landscape, there remains a lack of empirical understanding of how personalization systems influence long-term user engagement. This study investigates the impact of AI-driven product personalization on customer loyalty among Indonesian e-commerce users. Employing a mixed-methods approach, quantitative data were collected through an online survey of 150 active users, and qualitative insights were obtained from in-depth interviews with six informants. Statistical analysis using simple linear regression revealed that personalization significantly influences customer loyalty, with a beta coefficient of 0.653 (t = 8.241, p < 0.001) and an R² value of 0.567. Qualitative findings highlight user concerns over recommendation accuracy, interface overload, and repetitive suggestions, which affect emotional satisfaction and platform attachment. This research contributes to the growing body of knowledge on AI adoption in e-commerce by integrating behavioral and technological dimensions of loyalty formation. It also offers practical implications for designing more context-sensitive personalization systems that prioritize not only algorithmic precision but also user control and experience quality.

Cost stickiness refers to an increase in costs when activities increase more than a decrease in costs in response to a decline in activities of the same magnitude. In this respect, managers play a crucial role in resource adjustment decisions, and various factors affect these decisions, including managerial optimism. In turn, managerial optimism is affected by economic conditions and economic crises, including the latest one affected by the Covid-19 pandemic. This will greatly reduce managerial optimism and motivate them to reduce greater resources when sales decline, even greater than the sales decline. Accordingly, this study tests the relationships between The Covid-19 pandemic, cost stickiness, and profitability of Indonesian listed firms in 2018-2020. We find that (1) firms reduce SG&A costs more to respond to sales decline during The Covid-19 pandemic, and (2) firms experiencing sales decline during The Covid-19 pandemic even exhibit better financial performance. Thus, this study indicates that higher profits are not always affected by increased income but also probably by cost decline that is greater than sales decline.

Savings and loan cooperatives play an important role in strengthening the community's economy, especially in the micro and small sectors. However, many cooperatives face various challenges related to proper financial management and recording. Limited human resources and lack of understanding of relevant accounting standards are the main obstacles. This community service aims to increase understanding and application of SAK ETAP (Financial Accounting Standards for Entities Without Public Accountability) in the Koperasi Simpan Pinjam (KSP) Inti Dana Semarang.  The methods used include training, mentoring, and evaluation of the implementation of  SAK ETAP. The results of this program show an improvement in the quality of financial reports and transparency in cooperative management. This initiative has a positive impact on member trust and the sustainability of cooperative businesses

This study aims to analyze the influence of profitability, asset growth, and company size on the capital structure of companies listed on the Indonesia Stock Exchange. Capital structure is a crucial element in financial management that affects funding decisions and company risks. The analysis method used was multiple regression, with a sample during the period 2014-2018. The results showed that profitability had a significant negative effect on capital structure, indicating that high-profit companies tended to use less debt. Asset growth, on the other hand, has a significant positive effect on capital structure, suggesting that fast-growing companies are more likely to capitalize on debt. Meanwhile, the size of the company does not show a significant influence on the capital structure. These findings provide important insights for managers in formulating effective and efficient funding strategies, and emphasize the need to consider internal and external factors in decision-making related to capital structure.

The financial sector has experienced significant transformation with the adoption of Artificial Intelligence (AI) technology, particularly in improving business decision-making. This study aims to analyze the impact of AI on decision-making quality, focusing on risk analysis and portfolio management in Indonesia's financial sector. A mixed-method approach was utilized, combining quantitative and qualitative data to provide a comprehensive view of AI’s role in financial decision-making processes. Quantitative data were gathered through surveys of 50 respondents from various financial institutions, while qualitative data were obtained from semi-structured interviews with industry executives. The findings indicate that AI significantly enhances risk analysis accuracy by 25%, optimizes portfolio management, accelerates decision-making processes, and improves operational efficiency by automating manual tasks and reducing human errors. Despite these benefits, the study also identifies challenges such as data quality issues and high implementation costs, which hinder the broader adoption of AI in the financial sector. The study concludes that AI offers substantial potential to improve decision-making in the financial industry, but addressing data infrastructure and training needs is critical for achieving optimal outcomes