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COGNITIVE ABILITY, INTRINSIC MOTIVATION, AND SELF EFFICIENCY TOWARDS EMPLOYEE PERFORMANCE Syamsuri, Abd. Rasyid; Halim, Abd.; Ikhlash, Muhammad; Setiani, Cindy; Esmeralda, Angel II P.
Journal of Applied Business Administration Vol 6 No 1 (2022): Journal of Applied Business Administration - Maret 2022
Publisher : Pusat P2M Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaba.v6i1.3591

This study aimed to analyze cognitive abilities, intrinsic motivation, and self-efficacy towards the employees performance of PT. Bank Danamon Sub Branch Office Sutomo, Medan. This study used quantitative methods with several tests namely classical assumption test, multiple linear regression, hypothesis testing and R2 test. Based on the results of the regression obtained the equation: Y = 0.948 + 0.425 X1 + 0.470 X2 + 0.668 X3. Partially, the tcount value of this study is 3.28 and it is known that the cognitive ability variable (X1) has a ttable of 1.70. When compared with tcount, the result was 3.28> 1.70, so it can be concluded that the cognitive ability variable (X1) has a positive and significant effect on the employee performance variable (Y). The intrinsic motivation variable (X2) has a tcount of 2.53. When compared with ttable, the results were 2.53> 1.70, so it can be concluded that the intrinsic motivation variable (X2) has a positive and significant effect on the employee performance variable (Y). The self-efficacy variable (X3) has a tcount of 4.63 and when compared with ttable the results were 4.63> 1.70, so it can be concluded that the self-efficacy variable (X3) has a positive and significant effect on the employee performance variable (Y). Simultaneously, the variables of cognitive ability, intrinsic motivation, and self-efficacy have a positive and significant influence on employee performance. This means that the hypothesis in this study is accepted, as evidenced by the value of Fcount > Ftable (13,837>2,93). Cognitive ability, intrinsic motivation, and self-efficacy have an influence on employee performance variables by 55.4%, while the remaining 44.6% was influenced by other variables not examined in this study

Propose Measures for Enhancement: Multiple Intelligence Based Instructional Strategies Esmeralda, Angel II P.
Educational Studies and Research Journal Vol. 1 No. 3 (2024): Educational Studies and Research Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/4nt0w594

This study explores the effectiveness of multiple intelligence-based instructional strategies in enhancing the learning experiences and development of secondary high school students. Rooted in Howard Gardner’s theory of multiple intelligences, the research aims to identify how various teaching approaches can cater to diverse learner profiles, including mastery, interpersonal, understanding, and self-expressive styles. The study also investigates the impact of these strategies on developing students’ logical-mathematical, verbal-linguistic, and spatial intelligences. Utilizing a descriptive research design, data were collected from teachers at the International Bureau of Management through questionnaires and analyzed using mean scores and weighted averages. Findings reveal that instructional strategies aligned with multiple intelligences significantly contribute to students’ cognitive, affective, and psychomotor development. Mastery and interpersonal teaching styles were particularly effective in fostering engagement and comprehension, while self-expressive approaches promoted creativity and personal insight. Despite the overall positive outcomes, challenges such as managing classroom behavior and facilitating critical thinking were identified as obstacles to optimal intelligence development. The study recommends that educators integrate diverse instructional methods tailored to multiple intelligences and continuously refine their teaching practices to address these challenges. Ultimately, adopting multiple intelligence-based strategies promotes holistic learning, enabling students to realize their full potential across varied intellectual domains.

E-Payment in The Eyes of Students: Analyzing the Impact of Trust, Risk, Benefits and Income Akbar, Hardhan Syaifullah; Ikhlash, Muhammad; Halim, Muhammad Irsyad; Esmeralda, Angel II P.
Social Sciences Insights Journal Vol. 1 No. 3 (2023): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/ssijvol1iss3art2

This research aims to determine the influence of a person's beliefs, risks, benefits, and income on interest in using e-payment, especially for Politeknik Negeri Batam students. This is quantitative research that uses non-probability sampling and collects respondent data using a Google Drive form, which will then be processed using IBM SPSS Statistics 23. The population of this research is active Politeknik Negeri Batam students who have used online payment methods or e-payments, with a total of 97 samples. The results of the tests carried out in this research show that trust has a negative effect and does not have a significant effect on a person's interest in using e-payment. Risk has a positive and significant effect on a person's interest in using e-payments. Benefits have a positive and significant influence on a person's interest in using e-payment. Income has a positive and significant effect on a person's interest in using e-payments.

Sustainable Development Reporting and Financial Performance: Systematic Literature Review 2019-2024 Esmeralda, Angel II P.
Educational Studies and Research Journal Vol. 2 No. 3 (2025): Educational Studies and Research Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/g1yhye97

This systematic literature review examines the relationship between sustainable development reporting (SDR) and corporate financial performance (CFP), synthesizing empirical evidence from studies published between 2019 and 2024. The review addresses the ongoing debate regarding whether sustainability disclosure creates or destroys shareholder value. Following PRISMA 2020 guidelines, this review analyzed 88 peer-reviewed empirical articles from Scopus, Web of Science, and Google Scholar. Studies were categorized by relationship direction, performance metrics used, reporting frameworks examined, and contextual moderators. The majority of studies (59%) report a positive relationship between SDR and CFP, supporting stakeholder theory and signaling theory. Mixed results (27%) suggest the relationship is contingent on moderating factors including firm size, industry, geographic region, and reporting quality. Negative relationships (9%) are primarily associated with short-term cost perspectives. GRI-aligned reporting and external assurance strengthen the positive SDR-CFP relationship. Market-based measures (Tobin’s Q) show stronger positive associations than accounting-based measures (ROA, ROE). This review provides a comprehensive framework integrating SDR dimensions, transmission mechanisms, and performance outcomes. It identifies critical moderating factors and offers actionable insights for practitioners while highlighting gaps for future research, including the need for longitudinal studies and investigation of SDG-specific reporting impacts.

Fraud Detection and Machine Learning in Auditing:A Systematic Literature Review Esmeralda, Angel II P.; Fadhilah , Nur Hidayah K
Educational Studies and Research Journal Vol. 3 No. 1 (2026): Educational Studies and Research Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/y8p1k791

This systematic literature review examines the application of machine learning (ML) techniques in fraud detection within the auditing domain, synthesizing findings from peer-reviewed studies published between 2019 and 2024. Following the PRISMA 2020 guidelines, this review analyzed 85 articles from Scopus, Web of Science, IEEE Xplore, and Google Scholar databases. The Kitchenham methodology was employed to ensure rigorous screening, extraction, and synthesis of relevant literature. The review reveals that ensemble methods, particularly Random Forest and XGBoost, demonstrate superior performance in fraud detection tasks. Deep learning architectures, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, show promising results for complex fraud patterns. Key challenges identified include imbalanced datasets, model interpretability, and regulatory compliance. The emergence of Explainable AI (XAI) techniques, such as SHAP and LIME, addresses transparency concerns in audit applications. This review provides a comprehensive synthesis of ML applications in fraud detection specifically within the auditing context, offering a research agenda for future investigations and practical implications for audit practitioners and regulators.

Factors influencing audit quality: A systematic literature review Esmeralda, Angel II P.
Social Sciences Insights Journal Vol. 3 No. 2 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/7rbh4p08

This systematic literature review synthesizes empirical research on factors influencing audit quality, examining studies published between 2019 and 2024. The review aims to identify key determinants of audit quality and their relative importance across different contexts. Following the PRISMA 2020 guidelines, this review analyzed 92 peer-reviewed articles from Scopus, Web of Science, and Google Scholar. Studies were categorized based on factor type: auditor-level factors, audit firm-level factors, and external/contextual factors. The review identifies auditor independence, Big 4 affiliation, audit committee effectiveness, and audit tenure as the most consistently studied factors. Big 4 auditors generally demonstrate higher audit quality, though this effect is moderated by client characteristics. Audit committee financial expertise positively influences audit quality through enhanced oversight. Time budget pressure and low audit fees negatively affect audit quality. Emerging themes include the impact of technology adoption and regulatory changes on audit quality. This review provides a comprehensive framework integrating input, process, and output factors affecting audit quality. It offers practical implications for regulators, audit firms, and corporate governance stakeholders while identifying gaps for future research.

Green human resource management and organizational performance: A systematic literature review Esmeralda, Angel II P.
Social Sciences Insights Journal Vol. 3 No. 1 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/vn9f8j26

This systematic literature review examines the relationship between green human resource management (GHRM) practices and organizational performance outcomes. The review synthesizes empirical evidence from 82 studies published between 2019 and 2024, addressing multiple dimensions of performance including environmental, financial, social, and sustainable performance. Following PRISMA 2020 guidelines, a systematic search was conducted across Scopus, Web of Science, and Google Scholar databases. Studies were analyzed using the Ability-Motivation-Opportunity (AMO) theoretical framework to categorize GHRM practices and their performance implications. The evidence strongly supports positive relationships between GHRM practices and organizational performance. Environmental performance shows the most consistent positive effects, followed by sustainable performance and green innovation. The GHRM-financial performance relationship is predominantly indirect, mediated by environmental performance and employee green behavior. Green training and development emerges as the most frequently examined and impactful practice. Employee green behavior serves as a critical mediating mechanism across all performance dimensions. This review provides an integrated framework connecting GHRM practices to multi-dimensional organizational performance through the AMO lens. It identifies critical mediating mechanisms and moderating factors, offering actionable insights for practitioners seeking to leverage human resources for environmental sustainability while maintaining competitive performance.

The role of AI in enhancing employee experience and HR effectiveness in hybrid work models: A systematic literature review Syamsuri, Abd. Rasyid; Arohman, Rifki; Saputra, Muhamad Renaldy; Esmeralda, Angel II P.
Social Sciences Insights Journal Vol. 3 No. 3 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/v4p4q169

This systematic literature review examines the role of artificial intelligence (AI) in enhancing employee experience (EX) and human resource (HR) effectiveness within hybrid work models. Following PRISMA guidelines, we systematically searched Scopus, Web of Science, and Google Scholar databases, identifying 847 initial records. After applying inclusion criteria (peer-reviewed articles, published 2019-2024, English language, focusing on AI-HR integration in flexible/hybrid work contexts), 42 studies were included in the final synthesis. The review identifies three primary AI application domains in HR: (1) operational automation (recruitment screening, scheduling, administrative tasks), (2) analytics and decision support (predictive retention modeling, performance analytics), and (3) personalized employee support (adaptive learning, well-being monitoring, conversational agents). Our synthesis reveals that AI positively influences EX outcomes—including engagement, satisfaction, and perceived HR responsiveness—when implemented with transparency, human oversight, and adequate digital infrastructure. However, significant challenges persist, including algorithmic bias in high-stakes decisions, data privacy concerns, skill gaps among HR professionals, and organizational resistance. The review proposes a conceptual framework integrating technological, organizational, and individual factors that moderate AI's effectiveness in hybrid contexts. Key moderating conditions include leadership support, data quality, employee digital literacy, and governance mechanisms. Limitations include potential publication bias, English-language restriction, and the nascent state of longitudinal research in this domain. We conclude with a specific research agenda identifying methodological approaches, contextual variables, and outcome measures warranting future investigation.

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