EKUITAS (Jurnal Ekonomi dan Keuangan)

DONALD TRUMP'S IMPACT: MEASURING STOCK REACTION AND CRYPTO ASSET VOLATILITY

2026-03-03T16:14:04+07:00

This study analyzes the impact of Donald Trump’s political dynamics on the Indonesian stock market and the volatility of global cryptocurrency assets. The objective is to compare the responses of both markets to major political events during the Trump 2.0 era. The study employs an event study approach, using the Wilcoxon test to examine stock abnormal returns and GARCH (1,1) and EGARCH models to analyze cryptocurrency volatility. The findings show that the 2024 U.S. presidential election and Donald Trump’s inauguration did not produce significant reactions in the average abnormal returns of Indonesian stocks. However, the announcement of import tariff increases in April 2025 generated a significant negative response in the short to medium term. In contrast, the cryptocurrency market experienced sharp increases in volatility around the election period, with strong evidence of volatility clustering. These results indicate that the Indonesian stock market is primarily driven by economic fundamentals, whereas the cryptocurrency market is more sensitive to political sentiment and pro-cryptocurrency figures. The findings support the semi-strong form of the Efficient Market Hypothesis and the Uncertain Information Hypothesis, highlighting the need for distinct investment strategies and improved financial literacy amid global political dynamics.

PERFORMANCE MANAGEMENT SYSTEM AT INDONESIA HIGHER EDUCATION INSTITUTION

2026-03-12T14:06:20+07:00

The intense competition among higher education institutions (HEIs) in Indonesia requires them to have a robust performance management system. This study aims to identify general performance management practices at HEIs in Indonesia, specifically at Widyatama University (UTama). This study is a qualitative study. Data credibility was tested using method triangulation. Data analysis employed content analysis and direct interpretation. The research data sources were scientific articles, secondary data, and primary data. The scientific articles were sourced from national and international journals. Secondary data consisted of strategic planning documents, quality manuals, and other related documents from several top universities in Indonesia. Primary data were collected through interviews with leaders and experts at UTama. The results of the study indicate that HEI in Indonesia and UTama already have a structured performance management system. Leaders and experts at HEI in general, and at UTama in particular, tend to choose or use the TWOS Matrix and the Balanced Scorecard (BSC) as part of their performance management system. The research results suggest that HEIs in Indonesia and UTama can create a combined performance management system using TWOS, BSC, Performance Prism, and Key Performance Indicators (KPIs) that meet both national and international criteria.

EARLY DETECTION OF VILLAGE FUND FRAUD VIA FORENSIC ACCOUNTING SYSTEMS IN INDONESIA

2026-03-03T15:58:05+07:00

The rising incidence of corruption in village funds in Indonesia poses a serious threat to rural development. Data from the Corruption Eradication Commission (KPK) for 2020–2024 show state losses exceeding IDR 2.5 trillion. This study examines the effects of forensic accounting, the village financial system (SISKEUDES), and human resource quality on the early detection of village fund fraud and tests the moderating role of moral justification. A mixed-method approach with an explanatory sequential design was employed. The quantitative phase involved 325 village officials in West Java Province and was analyzed using SEM-PLS, followed by qualitative in-depth interviews and focus group discussions to enrich interpretation. The findings indicate that forensic accounting, SISKEUDES, and human resource quality significantly improve early fraud detection. The study’s main contribution is empirical evidence that moral justification negatively moderates these relationships, weakening the effectiveness of technical systems and personnel competence. This research advances the literature by integrating technical, systemic, and psychological factors into a unified framework for village-level fraud detection, highlighting moral justification as a critical factor undermining fraud prevention.

TAX EFFORT DETERMINANTS: THE ROLE OF TAX STRUCTURE AND FINANCIAL DEVELOPMENT IN SOUTHEAST ASIA

2026-03-16T11:03:50+07:00

Tax revenue is vital for financing sustainable development and ensuring fiscal stability, yet several Southeast Asian countries continue to face declining collection performance. This study assesses the tax effort of eight Southeast Asian economies between 1990 and 2020, employing an empirical panel regression model to estimate tax capacity based on macroeconomic, structural, and institutional factors. The resulting tax effort (the ratio of actual to predicted tax revenue) captures each country’s efficiency in mobilizing taxes relative to its potential. The analysis reveals wide disparities: Cambodia shows remarkable improvement, while Malaysia and Indonesia exhibit declining trends. Key determinants include GDP per capita, trade openness, and agricultural share, with financial development (measured by banking sector credit) emerging as a critical enabler of effective tax administration. The findings suggest that expanding the VAT base, enhancing financial inclusion, and strengthening tax-financial sector linkages can significantly improve revenue mobilization and fiscal resilience in the region.

LEVERAGE AND PROFITABILITY THROUGH AI-ENHANCED DUPONT IN INDONESIA’S OIL AND GAS SECTOR

2026-04-17T12:09:59+07:00

This study revisits the relationship between leverage and profitability within the DuPont framework by integrating Artificial Intelligence (AI) into financial performance evaluation. The study addresses the limitations of conventional financial analysis in capturing complex and non-linear relationships among financial variables, particularly in capital-intensive and high-risk industries such as oil and gas. It aims to examine the effects of leverage, profitability, and asset efficiency on Return on Equity (ROE) and to assess whether AI can strengthen the analytical value of the DuPont framework. Using a quantitative approach, this research analyzes secondary data from 12 oil and gas companies listed on the Indonesia Stock Exchange during 2022-2024. ROE is decomposed into Net Profit Margin (NPM), Total Asset Turnover (TATO), and Financial Leverage Multiplier (FLM) through DuPont analysis, while an Artificial Neural Network (ANN) is used to identify non-linear relationships. The findings show that leverage has the strongest influence on ROE, followed by profitability, while asset efficiency has a weaker effect. The study concludes that AI-enhanced DuPont analysis improves financial performance evaluation and supports better strategic decision-making.

DIGITAL BANKING ADOPTION AND FINANCIAL PERFORMANCE: EMPIRICAL EVIDENCE IN INDONESIA

2026-05-11T15:48:46+07:00

Digital transformation in Indonesia’s banking industry continues to evolve, yet its impact on banks’ financial performance remains inconsistent. This study aims to examine the effects of digital banking adoption on profitability, risk-taking, and stock returns. Using a quantitative approach with panel data, this study analyzes nine BUKU III and BUKU IV banks listed on the Indonesia Stock Exchange during the 2015–2024 period employing the Random Effects Model (REM). The results indicate that digital banking does not have a significant direct effect on profitability. However, digitalization was found to significantly increase risk-taking and stock returns. These findings indicate that digital activities drive bank business expansion and enhance investor confidence in the banks’ future growth prospects. Furthermore, the results confirm that the impact of digitalization is reflected more rapidly in risk behavior and market responses than in short-term profitability performance. Thus, to achieve optimal financial performance, the implementation of digital banking must be balanced with sound risk management and long-term business strategies.

GENERATIVE ARTIFICIAL INTELLIGENCE EQUALISES LOW-DIGITAL MICROENTERPRISE CAPABILITY

2026-05-05T15:56:54+07:00

This study investigates whether a generative AI copilot can raise marketplace performance for micro and small enterprises and whether the gains concentrate among lower-ability sellers. Across a 12-week randomized controlled field trial, 240 Manado sellers were evenly split between a high-traffic mall and a residential area and assigned either to business-as-usual or to an AI copilot that generated optimized titles, persuasive descriptions, relevant tags, and photo guidance for their TikTok videos. We tracked the click-through rate, conversion rate, average order value, buyer rating, and an internal listing-quality index, and estimated causal effects using difference-in-differences models with seller-clustered standard errors. Compared with the control, the AI treatment increased click-through and conversion rates, raised the average order value by approximately IDR 19,000, improved ratings, and enhanced listing quality, with more potent effects in the residential segment. Mediation analysis showed that AI primarily improved listing quality; the resulting quality gains translated into higher conversion rates, and the indirect effect was statistically significant. The approach is scalable as a low-cost, platform-embedded marketing aid in urban markets.

THE IMPACT OF FINANCIAL STRESS IN ADVANCED AND DEVELOPING ASIA ON INDONESIA’S STOCK MARKET RETURNS

2026-04-17T11:26:51+07:00

This study examines the impact of the Financial Stress Index (FSI) for Advanced Asia and Developing Asia on Indonesia’s equity returns. Monthly data from July 2003 to December 2024, comprising 258 observations, were sourced from the Asia Regional Integration Center (ARIC). The analysis utilized a Vector Autoregression (VAR) model to capture dynamic relationships among the variables. The results indicate that financial stress in Advanced Asia exerts a negative and significant short-term effect on Indonesia’s equity returns. This finding suggests a financial contagion effect, or negative spillover, from advanced Asian economies such as Japan and Australia, which are structurally integrated into the global financial system. In contrast, financial stress in Developing Asia has a positive and significant short-term impact on Indonesia’s equity returns, reflecting a reallocation spillover mechanism in which financial stress in other developing economies prompts investors to reallocate funds to Indonesia, which is perceived as more macroeconomically stable. Domestic financial stress in Indonesia demonstrates a negative but statistically insignificant effect on stock market performance. These findings underscore the need for enhanced cross-regional policy coordination and for implementing adaptive macroprudential measures to strengthen Indonesia’s capital market's resilience against regional financial risk transmission.

DIGITAL FINANCIAL CAPABILITY AND SOCIAL CAPITAL ON GEN Z FINANCIAL RESILIENCE

2026-05-21T16:21:43+07:00

The expansion of the digital economy has increased young people's reliance on technology-based financial services, underscoring the need to understand the determinants of their financial resilience. This study examines the effects of digital financial capability, social capital, and consumptive lifestyle on financial resilience, with financial stress considered as a mediating variable among Generation Z in semi-urban areas. A quantitative explanatory approach was employed, using an online questionnaire to collect data from 128 purposively selected respondents. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that digital financial capability and social capital exert a significant positive influence on financial resilience, while a consumptive lifestyle does not. Additionally, financial stress does not mediate the relationships between the independent variables and financial resilience, likely because most respondents continue to receive financial support from their families and face relatively low financial burdens. These results emphasize the critical roles of digital capability and social support in enhancing young people's financial resilience in semi-urban contexts.

ECOSYSTEM-SPECIFIC MACROECONOMIC DYNAMICS OF ETHEREUM, BUILD AND BUILD, AND SOLANA IN INDONESIA

2026-05-12T12:47:42+07:00

The rapid development of smart-contract-based blockchain ecosystems has transformed the perception of digital assets. However, the extent to which these assets are influenced by macroeconomic conditions in emerging markets remains poorly understood. This study aims to examine the long-term and short-term relationships between three major smart-contract platforms: Ethereum (ETH), Build and Build (BNB) Chain, and Solana (SOL), and several Indonesian macroeconomic indicators: money supply (M2), consumer price index (CPI), the rupiah-to-US dollar exchange rate (IDR/USD), and the policy interest rate (BI Rate). The study draws on monthly data spanning April 2023 to September 2025. The findings reveal that each platform exhibits a distinct degree of sensitivity to Indonesian macroeconomic conditions. Overall, the three platforms demonstrate a strong long-run relationship with the selected macroeconomic variables. The rising money supply (M2) tends to have a positive effect on all three platforms, while the influence of the exchange rate varies across ecosystems. Furthermore, this study traces how shocks in macroeconomic variables are transmitted to cryptocurrency prices and identifies distinct volatility patterns across the three platforms. Its findings contribute to understanding the relationship between crypto assets and macroeconomic conditions. It also offers practical insights for portfolio diversification strategies and for developing regulatory frameworks in Indonesia's growing digital asset market.