The transformation to digital accounting in Aceh faces greater challenges than other regions due to limited internet access, low stakeholder awareness, uneven training distribution, and varying levels of digital competence among human resources (HR). These factors hinder the effective implementation of digital accounting despite existing government regulations promoting digitalization. This study aimed to analyze the influence of technological developments, the need for efficiency, regulations, and HR competence on implementing digital accounting, with digital competence as an intervening variable, in districts and cities in Aceh. This study used a quantitative approach with a survey method involving respondents from the government and private sectors who have adopted digital accounting technology. The study indicates that technological developments, the need for efficiency, regulations, and HR competence significantly influence digital accounting implementation. Digital competence also strengthens the relationship between these factors and successful adoption of digital accounting. The synergy of these elements can accelerate a more effective adoption of digital accounting. This study provides strategic recommendations for local governments and organizations to develop training programs and regulations that support digital transformation in the accounting sector.
The advent of Industry 5.0, with its focus on humanmachine collaboration, has amplified the complexity of designing ergonomic work environments. This presents a significant challenge for industrial engineering education, particularly in teaching ergonomic principles that account for human fatigue, operational continuity, and safety in shared workspaces. Traditional ergonomic risk assessments are often slow, subjective, and isolated from the broader production system, hindering their effectiveness and scalability in educational settings where direct exposure to real production lines is impractical. To address these limitations, this study introduces an AI-driven ergonomic automated risk assessment system designed for educational use in simulated Human-Integrated Production Lines (HIPLs). This innovative tool provides students with real-time, objective, and automated posture-based risk evaluations within virtual environments. The core of the system is an AI-based posture classification model, developed using Random Forest, XGBoost, Support Vector Machine, and a Hard Voting ensemble, achieving 94.02% classification accuracy. Integrated into a software platform, the system offers immediate feedback on ergonomic safety and productivity through a timing and monitoring module. It records ergonomic scores, risk levels, performance statistics, and visual data for traceability and personalized feedback. An experimental study involving fifteen participants performing VR-based assembly tasks demonstrated an average learning rate of 95.61%, confirming the system’s effectiveness in enhancing participants’ understanding of ergonomic risk assessment and the impact of work environment design on human performance and safety. The System Usability Scale (SUS) yielded an average score of 75.33, indicating good usability and a high level of learner engagement.
The study investigates library users’ trust in Artificial Intelligence (AI)-powered library services. It aims to comprehend the factors that affect user trust, perceptions, and attitudes on AI. Furthermore, the research delves into the ethical ramifications of using AI in libraries, emphasizing equity, algorithmic biases, and data privacy concerns. The research attempts to uncover essential characteristics contributing to positive user experiences and successful implementation techniques by analyzing successful case studies and best practices. The intention is to offer knowledge that will assist libraries in integrating AI technology responsibly and efficiently, building user trust, improving services, and satisfying the changing demands of various user communities. The technology–organisation–environment framework (TOE) and the Interactionist Model of Ethical Decision-Making (IMEDM) shed more light on the investigation. Using a quantitative cross-sectional survey design, data were collected from various stakeholders in a developing country context. Simple random, stratified, and purposeful sampling were used. The survey employed a 5-point Likert scale to gauge respondents’ perspectives on AI-enabled library services, emphasizing ethical issues and implementation obstacles associated with user trust. Younger users showed high trust in AI, while privacy, accountability, and transparency were identified as the three main areas of concern. AI’s beneficial effects on user experience and important ethical issues were all shown to be critical, with implications for theory and practice. The study’s originality lies in the insightful information it provides librarians and other critical stakeholders. It enhances user community experiences and emphasizes the key ethical principles in AI implementation.
