Publication Search

This study aims to determine and analyze the effect of entrepreneurial knowledge and entrepreneurial skills on business success in Micro, Small, and Medium Enterprises (MSMEs) in Aesesa District, Nagekeo Regency. The background of this research is driven by fluctuations in MSME performance, unstable turnover, suboptimal management, low customer satisfaction, and limited practical skills and knowledge. This study utilizes a quantitative approach with a causal associative method. The population consists of all 3,705 active MSMEs in Aesesa District. The sampling technique used was purposive sampling with specific criteria, and the sample size was calculated using the Slovin formula with a 10% margin of error, resulting in exactly 100 respondents. Data collection was conducted via structured questionnaires with a 1–5 Likert scale. Data analysis techniques include descriptive statistics, validity and reliability tests, classical assumption tests (multicollinearity, heteroscedasticity, and normality), multiple linear regression analysis, t-test, F-test, and coefficient of determination administered through SPSS. The multiple linear regression analysis yielded the equation Y = 12.450 + 0.412X1 + 0.385X2. The partial test (t-test) demonstrates that entrepreneurial knowledge has a positive and significant effect on business success (t count 4.120 > t table 1.984, sig 0.000). Entrepreneurial skills also exert a positive and significant impact on business success (t count 3.850 > t table 1.984, sig 0.000). Simultaneously (F-test), entrepreneurial knowledge and entrepreneurial skills have a significant combined effect on business success with F count 38.450 > F table 3.09. The coefficient of determination (Adjusted R Square) value of 0.442 indicates that the variation in business success is influenced by both independent variables by 44.2%, while the remaining 55.8% is explained by external factors outside this research model.

The development of artificial intelligence (AI) has driven fundamental changes in the way organizations manage work processes, make decisions, and coordinate teams in digital environments. However, an integrated understanding of how AI-based leadership affects digital team performance, particularly through the roles of transformational leadership and digital literacy, remains limited and dispersed across different streams of literature. This study aims to analyze the role of AI in supporting digital leadership, identify its influence on decision-making effectiveness and team performance, and examine the challenges and ethical implications of its implementation in organizations. The study employs a Systematic Literature Review (SLR) approach by reviewing relevant scholarly literature on AI, leadership, digital literacy, human–AI collaboration, and digital team performance. The findings indicate that AI-based leadership can enhance team management effectiveness when implemented through transformational leadership practices that foster vision, change readiness, learning, and team coordination, and when supported by adequate digital literacy. Conversely, barriers such as low trust in AI, digital competency gaps, resistance to change, and ethical issues remain major challenges. This study contributes by offering a conceptual synthesis that positions AI-based leadership, transformational leadership, and digital literacy within a single framework to explain the optimization of digital team performance in modern work environments.

Student dropout in higher education remains a persistent socioeconomic challenge, yet many predictive models reported in the literature are methodologically compromised by randomized cross-validation schemes that introduce temporal data leakage and artificially inflate predictive performance. This study proposes a longitudinal prescriptive learning analytics framework integrating three complementary methodological components: a Leave-One-Cohort-Out (LOCO) temporal validation protocol, a hybrid SMOTE-ENN class balancing strategy, and temporal velocity feature engineering derived from Learning Management System (LMS) behavioral trajectories. The framework was evaluated on a longitudinal dataset comprising 464,739 enrollment records and 77 features. Five predictive algorithms—XGBoost, LightGBM, CatBoost, Random Forest, and Logistic Regression—were comparatively assessed on a strictly isolated blind holdout cohort (2022), with CatBoost emerging as the champion estimator, achieving a PR-AUC of 0.8859, a Macro F1-Score of 0.9143, and the lowest Brier Score (0.0221), thereby demonstrating superior calibration and discriminative capability under severe class imbalance (93:7 ratio). Comprehensive ablation analysis revealed that temporal velocity features function not merely as additive predictors, but as a structural prerequisite enabling Synthetic Minority Oversampling Technique with Edited Nearest Neighbors (SMOTE-ENN) to generate high-quality synthetic boundary instances; removing these features reduced minority-class precision from 0.8302 to 0.6721. To operationalize predictive outputs into actionable intervention pathways, Diverse Counterfactual Explanations (DiCE) were implemented under a three-tier causal constraint architecture on 96 borderline high-risk students, generating 384 feasible intervention scenarios exclusively targeting forward-looking behavioral velocity metrics without constraint violations. Collectively, these findings advance the paradigm of prescriptive learning analytics by providing educational institutions with interpretable risk diagnostics and operationally feasible intervention guidance grounded in empirically validated behavioral and temporal dynamics.

This study examines the role of QRIS as a non-cash payment system in supporting the digitalization of micro, small, and medium enterprises (MSMEs) in Indonesia. The rapid growth of digital transactions has encouraged MSMEs to adopt more efficient, practical, and secure payment systems. This study aims to integrate the benefits and barriers of QRIS, map its position in the MSME digitalization process, and develop a conceptual framework for future research. A descriptive qualitative approach with a literature study design was employed, utilizing relevant academic sources related to QRIS, MSMEs, digital payments, and user behavior. Data were analyzed using content analysis by comparing, interpreting, and synthesizing findings from selected literature. The results indicate that QRIS contributes to simplifying transactions, improving operational efficiency, reducing cash dependency, and supporting MSMEs’ adaptation to digital payment trends. However, its implementation remains constrained by factors such as digital literacy, user readiness, trust, and infrastructural limitations. The study also highlights that QRIS adoption is influenced not only by technological advantages but also by perceived value and user trust. Therefore, QRIS can be positioned as a strategic instrument in accelerating the digital transformation of MSME payment systems. The findings imply the need for further empirical research to examine the direct impact of QRIS adoption on MSME performance and sustainability.

This study aims to investigate the influence of academic qualifications, managerial capabilities, and Perceived Organizational Support (POS) on emotional exhaustion and its implications for employee productivity at Sunan Kudus Islamic Hospital. Using a quantitative approach, data were collected via a questionnaire from 138 respondents. Instrument evaluation procedures were conducted through validity and reliability tests, while hypothesis testing was analyzed using Structural Equation Modeling (SEM). The findings reveal that academic qualifications and POS have a significant negative effect on emotional exhaustion, indicating that increased intellectual competence and strong organizational support are effective in reducing staff emotional exhaustion. Conversely, managerial capabilities were found to have no significant influence on emotional exhaustion. In the context of performance, the analysis results show that academic qualifications, managerial capabilities, and POS have a partial, positive, and significant effect on work productivity. Practically, this study suggests that hospital management prioritize human capital development and the strengthening of a supportive organizational climate to mitigate emotional exhaustion while accelerating operational efficiency in a sustainable manner.

Sweet corn (Zea mays saccharata Sturt.) is an increasingly popular horticultural commodity in Indonesia, attracting both farmers and consumer. This study aims to evaluate the effectiveness of single‑micronutrient fertilizer Mn‑EDTA (12%) in enhancing the growth and yield of sweet corn (Zea mays saccharata Sturt.). The treatments consisted of control, standard NPK, 0.25 NPK, 0.50 NPK, 0.75 NPK, and 1.00 NPK. The experimental findings demonstrated that the application of single‑micronutrient Mn‑EDTA (12%) fertilizer had a highly significant effect on vegetative growth and yield components of sweet corn, with statistically higher values compared with the control treatment. In general, fertilizer dosages equivalent to 0.25–1.00 NPK produced greater plant height, stem diameter, leaf number, ear length, ear diameter, biomass weight, ear weight with husk, ear weight without husk, plot yield, and productivity than the control. The RAE calculation indicated that the fertilizer was effective when applied at dosages equivalent to 0.75 and 1.00 NPK. The highest effectiveness was observed at the 1.00 NPK dosage, with an RAE value of 101%. Notably, the application of Mn‑EDTA (12%) fertilizer at the 1.00 NPK dosage provided significant field effectiveness, as reflected by the RAE value of 101%. This result implies that the use of single‑micronutrient Mn‑EDTA (12%) fertilizer at the 1.00 NPK dosage increased yield by 1.01 times compared with the yield improvement obtained from the reference fertilizer relative to the control treatment.

This study aims to describe the aesthetics of the performance form of the Lenggok Dance created by Ida Sulistyarini and Susiati, which has developed in Banyumas Regency. The Lenggok Dance is a creative dance work rooted in the local Banyumasan tradition and presents distinctive movement characteristics along with regional cultural values. This research uses Djelantik’s aesthetic theory with a qualitative method and a phenomenological approach. Data collection techniques include observation, interviews, and documentation. Data validity techniques employ triangulation of sources, techniques, and time. Data analysis is carried out by examining the aesthetic elements of the dance, which include form, content or substance, and presentation or performance contained in the show. The results of the study indicate that the aesthetics of the Lenggok Dance are reflected through the harmony between dynamic and flexible lenggeran movements and the rhythmic Banyumasan musical accompaniment, as well as visual support from makeup and costumes that strengthen the character of the dance. In addition, the Lenggok Dance contains aesthetic values that represent the cultural identity of Banyumas, particularly in the processing of movements and expressions that reflect flexibility, joy, and local wisdom. This study is expected to contribute to the development of dance studies, especially related to the aesthetics of regional creative dance, and to serve as a reference for the preservation and development of Banyumasan performing arts.

This study aims to analyze the effect of Knowledge Sharing and Knowledge Leakage on Supply Chain performance, with Monitoring Opportunity as a mediating variable at the Library Office of Mesuji Regency. The research problem arises from the limited structure of knowledge-sharing practices, weak documentation of organizational knowledge, and the potential risk of knowledge leakage that may disrupt the effectiveness of library service supply chains. This study employs a quantitative approach using a survey method. Data were collected through questionnaires distributed to 115 employees of the Library Office of Mesuji Regency and analyzed using Structural Equation Modeling based on Partial Least Squares with SmartPLS. The results show that Knowledge Sharing has a positive and significant effect on Supply Chain performance and Monitoring Opportunity. Knowledge Leakage does not have a significant direct effect on Supply Chain performance, but it has a negative and significant effect on Monitoring Opportunity. Furthermore, Monitoring Opportunity significantly mediates the relationship between Knowledge Sharing and Supply Chain performance, but does not mediate the relationship between Knowledge Leakage and Supply Chain performance. These findings indicate that knowledge sharing becomes more valuable when supported by monitoring capability, while knowledge leakage should be controlled through documentation, access control, and knowledge protection mechanisms. This study contributes to knowledge management and supply chain literature in public library service organizations.

 This study examines women’s transformational leadership in educational institutions through a systematic literature review approach. The increasing involvement of women in leadership positions in schools and universities has attracted academic attention to understand their contribution to organizational development and the improvement of educational quality. This study aims to synthesize recent empirical research findings on women’s transformational leadership in education. The method used was a Systematic Literature Review (SLR) by identifying, evaluating, and synthesizing relevant studies published between 2021–2026 through academic databases such as Google Scholar and ScienceDirect using the keywords “transformational leadership,” “women leadership,” and “education or school.” After a selection process based on inclusion and exclusion criteria, 15 empirical articles were analyzed. The findings indicate that female leaders tend to demonstrate transformational leadership characteristics, including inspirational motivation, intellectual stimulation, idealized influence, and individualized consideration. These leadership practices positively affect teacher motivation and performance, organizational commitment, organizational climate, and learning innovation. However, women in leadership positions still face challenges such as gender stereotypes, structural bias, and social expectations regarding gender roles, indicating the need for institutional support and more inclusive policies.

This research is motivated by the increasing role of Artificial Intelligence (AI) in organizational transformation and the crucial function of leadership in ensuring its successful implementation. The primary objective of this study is to analyze the relationship between leadership, AI integration, and organizational performance, as well as to identify various challenges and supporting factors in the process. This study employs a systematic literature review (SLR) method by examining 30 relevant, reputable scientific articles from the Scopus and Google Scholar databases within the 2020–2026 timeframe through selection, evaluation, and thematic synthesis processes. The results indicate that AI integration significantly contributes to improving operational efficiency, data-driven decision-making quality, and organizational innovation. However, this success heavily depends on the role of adaptive, transformational, and digitally-oriented leadership capable of steering the technological vision. Conversely, major challenges were identified, such as employee resistance, limited digital competencies, and ethical issues surrounding data privacy. This study contributes to strengthening the conceptual understanding of leadership's role as a bridge between technology and organizational performance, while offering practical implications for management in designing effective, inclusive, and sustainable digital transformation strategies.

This study aims to analyze the effect of Good Corporate Governance (GCG), Firm Size, and Sales Growth on Financial Performance at PT Ace Hardware Indonesia Tbk listed on the Indonesia Stock Exchange (IDX) during the 2015–2024 period. Good Corporate Governance (GCG) in this study is proxied by institutional ownership, financial performance is measured using Return on Assets (ROA), firm size is measured by the natural logarithm of total assets, and sales growth is measured using the sales growth ratio. This study employed a quantitative method with a descriptive approach. The data used were secondary data in the form of annual financial statements obtained from the official websites of the IDX and the company. Data analysis techniques included descriptive statistics, classical assumption tests, multiple and simple linear regression analysis, and hypothesis testing consisting of t-test, F-test, and coefficient of determination with the assistance of SPSS version 27 software. The results of the study indicate that partially, the Good Corporate Governance (GCG) variable has a t-value of -1.526 < t-table 2.447, meaning that it has no significant effect on financial performance. The firm size variable has a t-value of -2.857 > t-table 2.447, indicating a significant negative effect on the company’s financial performance. The sales growth variable has a t-value of 1.593 < t-table 2.447, meaning that it has no significant effect on financial performance. Simultaneously, Good Corporate Governance (GCG), firm size, and sales growth have a significant effect on financial performance, with an F-value of 13.023 > F-table 4.76 and a significance value of 0.005 < 0.05. This study is expected to provide consideration for management and investors in decision-making and serve as a reference for future research in related fields.

This study is motivated by the importance of work effectiveness as a key indicator of organizational success in facing an increasingly complex and competitive work environment. Work discipline is viewed as one of the critical factors that can support the achievement of optimal work effectiveness. This study aims to analyze the relationship between work discipline and work effectiveness and to identify the factors influencing them within an organizational context. The method used is a Systematic Literature Review, which involves examining various relevant scientific articles through the stages of identification, selection, evaluation, and data synthesis. The results of the study indicate that work discipline plays a significant role in enhancing work effectiveness through adherence to rules, punctuality, responsibility, and consistency in task execution. Furthermore, work effectiveness can also foster the development of discipline through structured work systems and clear operational standards. The relationship between these two variables is reciprocal and influenced by factors such as leadership, organizational culture, motivation, human resource competencies, and the utilization of technology. The implications of this research underscore the importance of integrating work discipline and organizational systems to sustainably enhance work effectiveness.

The plantation sector is one of the main pillars in Indonesia’s international trade. Commodities such as palm oil, rubber, coffee, and cocoa serve as leading export products that contribute significantly to the country’s foreign exchange earnings. This study aims to analyze the role of plantation commodity exports in Indonesia’s international economic performance and to identify the challenges faced. The method used is a descriptive qualitative approach through literature review from various scientific sources. The results indicate that plantation exports contribute substantially to economic growth, employment generation, and the stability of the trade balance. However, several challenges persist, including global price fluctuations, sustainability issues, and international trade barriers. Therefore, strategic policies are required to enhance the competitiveness of Indonesia’s plantation commodities in the global market.

Using Non Performing Financing (NPF) as a moderating variable, this study looks at how profit sharing and profit margin financing affect the effectiveness and stability of Islamic banks in Indonesia. The primary topic discussed is how various Islamic financing arrangements affect the operational effectiveness and financial stability of banks, as well as whether credit risk enhances or diminishes these connections. This study aims to examine the direct impacts of financing modalities as well as the moderating influence of NPF on the performance of Islamic banks. Based on secondary data from eight Islamic banks in Indonesia between 2018-2024, this study employs a quantitative methodology using panel data regression and Moderated Regression Analysis (MRA). The findings indicate that while profit margin financing has no discernible impact on efficiency, profit sharing financing has a favorable and considerable impact. Profit margin financing has a negative and negligible impact on stability, whereas profit sharing financing has a positive but negligible impact. Additionally, by changing the direction of influence, NPF significantly moderates the association between profit sharing financing and both efficiency and stability. However, it does not significantly moderate the effect of profit margin financing on efficiency, but it does on stability. In summary, the effectiveness of Islamic financing is heavily reliant on risk management, especially credit risk control, where NPF is a key factor in evaluating whether financing can improve stability and efficiency in Islamic banks.

This study examines the efficiency of financial ratios in assessing corporate performance across countries. Although financial ratios are widely used as concise indicators of profitability, liquidity, solvency, and market value, their interpretive accuracy may vary across institutional, regulatory, financial, and macroeconomic environments. The objective of this study is to conceptually evaluate whether financial ratios can function as universally comparable performance measures in heterogeneous cross-country settings. Using a qualitative literature-based method, this study synthesizes prior findings on financial ratio analysis, financial statement comparability, market efficiency, regulatory enforcement, and macroeconomic stability. The findings indicate that profitability, liquidity, solvency, and market-based ratios are context-dependent indicators rather than universally stable measures. Their efficiency is influenced by accounting standards, audit quality, leverage norms, tax systems, capital market maturity, and macroeconomic volatility. The study proposes a contextual framework for interpreting financial ratios according to their sensitivity to national conditions. The implication is that researchers, analysts, and investors should combine ratio analysis with institutional and macroeconomic diagnostics to reduce biased performance interpretation in cross-country corporate evaluation.

. A website is a crucial digital promotion medium for companies to convey information and attract potential customers. However, many websites experience low user interaction despite having high visitor traffic. This study aims to analyze the effectiveness of A/B Testing implementation in improving the performance of the PT Pamor Putra Mandiri website. A quantitative experimental approach was used, applying A/B Testing to two page variations: Variation 1 (Rafting & Outdoor Activity theme) and Variation 2 (Camping & Accommodation theme). The evaluation focused on three main performance metrics: Click, Page Visit, and Engagement. The results show that Variation 1 consistently outperformed Variation 2 across all metrics. Statistical testing using a two-proportion z-test confirmed that these differences were statistically significant (p-value < 0.05). Therefore, A/B Testing proves to be an effective method in identifying superior content strategies and page structures, as well as a relevant tool for data-driven decision-making in corporate website development.

This study examines the integration of Sound Governance principles within the sustainable tourism policy cycle to address institutional fragmentation and evaluation inefficiencies in developing economies. Using a sequential explanatory mixed-methods design, the research develops a multidimensional evaluation framework aligned with the Sustainable Development Goals (SDGs), analyzing policy performance across five strategic domains: Economy, Social-Welfare, Culture-Education, Environment, and Governance. The quantitative phase utilizes 17 adapted SDG indicators to measure policy efficacy, while the qualitative phase employs semi-structured interviews and stakeholder mapping to deconstruct power dynamics in multi-actor co-management structures. The findings reveal that Sound Governance—specifically transparency and accountability—serves as a critical catalyst for policy effectiveness, significantly influencing destination sustainability through an input-process-output-outcome-impact pathway. Empirical evidence from the case of Penglipuran Village, Bali, corroborates these results, demonstrating that indigenous institutional legitimacy enhances social responsiveness but remains vulnerable to overtourism-driven economic dependency. Notably, the study demonstrates that integrating SDGs into the policy evaluation cycle transforms assessments from mere administrative formalities into strategic instruments for long-term demand stability and ecosystem preservation. These findings position Sound Governance as a strategic intangible asset, offering theoretical contributions to development administration and practical guidance for policy-makers navigating the complexities of sustainable destination management in competitive global markets

Leadership in educational management has a strategic role in determining the success of educational implementation. This study aims to examine the integrative paradigm between psychology and leadership in educational management, focusing on the psychological dimensions of educational leadership. This research employs a qualitative approach using a systematic literature review method. Data were collected from scientific articles published between 2020 and 2026 through Google Scholar using Publish or Perish. The findings indicate that the integration of psychological perspectives into leadership significantly enhances organizational effectiveness, particularly in fostering work motivation, strengthening interpersonal communication, and improving adaptive decision-making. Furthermore, psychological approaches contribute to conflict management and the development of a positive organizational climate. The study also highlights that leadership effectiveness is strongly influenced by psychological characteristics such as personality, emotional intelligence, and empathy. Therefore, integrating psychology into leadership serves as a strategic foundation for advancing educational management and improving human resource performance sustainably.

This study examines the determinants of the Jakarta Composite Index (JCI) based on three main macroeconomic factors namely inflation, the USD/IDR exchange rate, and the SBI interest rate (BI Rate) covering the period January 2020 to December 2025, in the context of post-COVID-19 pandemic recovery and global economic turmoil. A quantitative approach was employed using the Ordinary Least Squares (OLS) method, with 72 monthly observations derived from secondary data sourced from official institutions including Bank Indonesia (BI), the Central Statistics Agency (BPS), the Indonesia Stock Exchange (IDX), and the Financial Services Authority (OJK). Classical assumption tests were applied comprising the Jarque-Bera normality test, Variance Inflation Factor (VIF) for multicollinearity, Breusch-Godfrey for autocorrelation, White Test for heteroscedasticity, and Ramsey RESET for model specification. Partially, inflation, exchange rate, and BI Rate each demonstrate a positive and significant effect on the JCI (p < 0.05). Simultaneously, all three variables exert a significant combined influence on the JCI, with a coefficient of determination R² = 0.4414, indicating that the model explains 44.14% of the variation in the JCI. The remaining 55.86% is attributed to other variables outside the model. Classical assumption test results reveal violations of normality, autocorrelation, and heteroscedasticity assumptions, although the model is free from multicollinearity. These findings confirm that Bank Indonesia's monetary policy has a significant and measurable impact on capital market performance. Further research is recommended using more advanced time series models such as GARCH or VECM to address violations of classical assumptions and improve estimation efficiency.

 Cryptocurrency price prediction, particularly for highly volatile assets like Solana (SOL), is a crucial challenge in time series data analysis in digital finance. This study aims to compare the performance of the XGBoost machine learning algorithm with the Temporal Fusion Transformer (TFT) deep learning model in predicting Solana's daily closing price. The dataset used consists of historical Solana price data and network fundamentals data in the form of Total Value Locked (TVL). The research process includes data preprocessing, dividing training and test data, model training, and evaluation using the Root Mean Squared Error (RMSE) metric. The results show that using the same-day price feature has the potential to cause target leakage, resulting in invalid prediction accuracy. In testing using pure historical data without data leakage, the XGBoost model performed better than TFT with an RMSE of 4.27, while TFT produced an RMSE of 18.59. Furthermore, the integration of network fundamentals data in the form of TVL did not improve prediction accuracy and even caused a decrease in performance for the XGBoost model with an RMSE of 7.10. The results of this study show that the use of historical price action features is more effective than fundamental network indicators for short-term daily Solana price predictions.