Abstract:Improving the quality of modern healthcare services largely depends on the effectiveness and efficiency of nursing personnel as the frontline providers of patient care. The complex and high-pressure work environment of specialized…
pecialized hospitals requires nurses to cope with emotional demands, heavy workloads, and rapid decision-making in critical situations. These conditions make emotional intelligence one of the important psychological factors influencing nursing performance quality. This study aimed to analyze the relationship between emotional intelligence and nursing work efficiency at King Fahad Specialist Hospital – Qassim Cluster, Saudi Arabia, in 2026. This study employed a quantitative approach with a cross-sectional design. The study population consisted of all active nurses working at King Fahad Specialist Hospital, Qassim Health Cluster. A total of 312 nurses were selected using stratified random sampling. Data were collected using the Emotional Intelligence Scale and Nursing Work Efficiency Scale, both of which had been tested for validity and reliability. Data analysis was conducted using Structural Equation Modeling–Partial Least Squares (SEM-PLS) with SmartPLS 4 software. The results revealed that emotional intelligence had a positive and significant effect on nursing work efficiency, with a path coefficient of 0.642, t-statistics of 9.871, and p-value < 0.001. The R-square value of 0.58 indicated that emotional intelligence explained 58% of the variance in nursing work efficiency. Emotional regulation and empathy emerged as the dominant indicators contributing to improved communication quality, clinical decision-making, and patient care effectiveness. This study concludes that emotional intelligence is an important psychological resource in improving nursing work efficiency in specialized hospitals. The findings strengthen the Job Demands–Resources (JD-R) Theory and Emotional Intelligence Theory in explaining the relationship between psychological resources and nursing performance. This study is expected to provide theoretical contributions to the development of nursing management literature and practical contributions for hospitals in designing healthcare human resource development strategies based on psychological well-being.
Abstract:This study analyzes OPPO's global expansion strategy through the optimization of its technology supply chain within the framework of the Global Value Chain (GVC). The smartphone industry has experienced rapid growth in recent…
ecent decades, with increasingly fierce competition among leading manufacturers. OPPO, a Chinese technology company founded in 2004 and part of BBK Electronics Corporation, has demonstrated significant competitiveness in the global market despite facing challenges in maintaining its market share from 2021 to 2024. This study uses a descriptive qualitative methodology, analyzing primary data from OPPO's official documents and secondary data from industry reports and academic literature. Findings show that OPPO implements production sharing in strategic geographic locations, with design and development centralized in China and manufacturing spread across countries that offer labor or infrastructure advantages. The study shows that OPPO's global expansion follows the Uppsala Model of internationalization, starting with culturally and geographically close markets such as Southeast Asia before expanding to more distant regions. Through technology-based supply chain optimization, digital integration, and the adoption of artificial intelligence (AI)-based coordination systems, OPPO has developed the ability to manage complex global networks while overcoming geopolitical challenges and supply chain disruptions. This research contributes to understanding how technology companies from developing countries leverage the Global Value Chain to enhance international competitiveness, providing insights into the relationship between supply chain strategy and the success of global expansion in the highly competitive smartphone industry.
Abstract:Digital transformation through Artificial Intelligence (AI) offers significant potential for enhancing elementary school teacher competence, yet its implementation remains largely technical and fragmented when detached from…
rom teachers’ religious and personal dimensions. This study addresses this gap by examining the integration of AI-assisted learning and Qur’anic tahsin development as a holistic model of teacher competency enhancement. Employing a qualitative case study design, the research was conducted at SD Negeri 200206 Padangsidimpuan, involving elementary school teachers, Islamic Religious Education teachers, school leadership, and facilitators of AI and tahsin training programs. Data were collected through in-depth interviews, classroom observations, and document analysis, and analyzed using an interactive analytical model with methodological triangulation. The findings reveal that the use of AI tools—such as ChatGPT, Gamma, and Canva AI—significantly improves instructional effectiveness and strengthens teachers’ pedagogical and professional competencies. Furthermore, AI-integrated Qur’anic tahsin training, particularly in makhārij al-ḥurūf and tajwīd, enhances teachers’ Qur’anic recitation quality while reinforcing their religious and personal competencies. This study contributes a value-based, integrative framework for teacher professional development that bridges digital innovation and Islamic educational values. Despite its potential, the model faces challenges related to digital literacy disparities, infrastructural readiness, and the need for sustained mentoring. The study advances scholarly discourse on ethically grounded AI integration in elementary education.
Abstract:The rapid digital transformation in education has redefined the role of teachers, necessitating the integration of Artificial Intelligence (AI) to enhance pedagogical efficiency. This study aims to analyze the needs of primary…
rimary school teachers regarding AI, describe the implementation of AI-assisted smart teaching training, and evaluate its impact on teachers' professional competence and the quality of produced instructional tools. Utilizing a descriptive qualitative approach with a field study design, the research was conducted at UPTD SD Negeri 33 Bangai. Data were collected through participatory observation, semi-structured interviews, and document analysis of teaching modules and worksheets. The subjects were selected via purposive sampling, and data were analyzed using the interactive model of reduction, display, and conclusion drawing. The results indicate that AI-assisted smart teaching training effectively shifts teachers from passive technology users to active pedagogical designers. Findings reveal a paradigm shift where teachers perceive AI as "augmenting intelligence" that strengthens rather than replaces their professional role. The instructional tools produced post-training showed significant improvements in systematic alignment and the integration of Higher-Order Thinking Skills (HOTS). Grounded in adult learning and experiential learning theories, this practice-based model fosters greater learning autonomy and reflective practice. This study contributes empirical evidence for the primary education context, suggesting that human-centered and pedagogically-driven AI integration is a vital strategy for teacher professional development in the digital era.
Abstract:Background: The position of ward head is crucial because their managerial skills play a significant role in the success of nursing services. The leader's character contributes optimally to creating quality nursing care.…
The results of this study are crucial because they discuss appropriate leadership characteristics in managing nursing wards. The past leadership characteristics of the Prophet Muhammad (peace be upon him) serve as the basis for patient management.
The purpose of this study was to conduct a literature review related to the leadership characteristics of Muslim ward heads, based on the leadership characteristics of the Prophet Muhammad (peace be upon him). The research method was a literature review of Islamic leadership character theories.
The results revealed that the leadership characteristics of the best Muslim ward heads in nursing care are honesty, trustworthiness, intelligence, fairness, preaching, responsibility, discipline, initiative, being a role model, and providing inspiration.
Conclusion: The leadership characteristics of Muslim ward heads are the foundation of good conventional leadership characteristics that can be implemented in managing patient nursing care.
Abstract:This best practice study aims to develop 21st-century soft skills in students at MAN 1 Banda Aceh through the implementation of an artificial intelligence-based collaborative learning model called KOTAK (Artificial Intelligence-Based…
ligence-Based Brain Collaboration). The study used a qualitative case study design with 39 students. Data collection was conducted through learning observations, interviews, and analysis of student activities and learning outcomes in the Integrated Economic Exploration material. The KOTAK model was designed by integrating various easily accessible AI tools, such as Google Lens, ChatGPT, and QuestionWell, to support interactive, collaborative, and problem-solving-based learning. The results showed that implementing the KOTAK model significantly improved students' critical thinking, communication, collaboration, and creativity (4C) skills. Analysis of learning outcomes indicated a 94.87% absorption rate and achievement of the curriculum objectives for the taught material. The use of the AI platform has proven to be an effective interactive medium for encouraging active student engagement, strengthening higher-order thinking, and fostering collaboration in problem-solving. This research makes an original contribution by offering and testing a contextual learning model that integrates collaborative pedagogy and AI technology in a madrasah environment, while also presenting a practical framework for developing 21st-century skills in integrated subjects such as Economics, in line with the implementation of the Merdeka Curriculum.
Abstract:Elementary education plays a strategic role in shaping students’ character, civic attitudes, and social-emotional development. Civic Education is a fundamental subject for instilling democratic values, responsibility, and…
and social awareness from an early age. Meanwhile, the advancement of digital technology, particularly Artificial Intelligence (AI)–based learning media, offers new opportunities to improve the quality of learning in elementary schools. This study aims to analyze the existence of Civic Education and the use of AI-based learning media in supporting students’ social-emotional development. This research employed a descriptive qualitative approach and was conducted at SD Negeri 0722 PTPN IV Lubuk Bunut. Data were collected through observation, interviews, and documentation. The findings indicate that Civic Education plays a significant role in fostering students’ social attitudes, empathy, and responsibility, while AI-based learning media enhance students’ learning motivation and engagement when implemented appropriately and in accordance with developmental stages. The integration of Civic Education, AI-based media, and developmental psychology perspectives contributes positively to students’ social-emotional development in elementary education.
Abstract:This study aims to investigate the integration of Artificial Intelligence (AI)-based learning media to enhance reading literacy among elementary school students. Using a descriptive qualitative approach through case study…
y and literature analysis, the research was conducted at SDN No. 100311 Palsabolas, involving teachers and students who utilized adaptive reading applications, text-to-speech tools, and intelligent learning platforms. Data were collected through observation, semi-structured interviews, and document analysis, and validated by triangulation techniques. The findings reveal that AI-assisted media significantly improve students’ reading motivation, comprehension, and fluency. Quantitative comparison between pretest and posttest results showed notable progress, with the average literacy score increasing by 16–27 points across different indicators. Students demonstrated greater engagement and independence, while teachers benefited from automated performance analytics and personalized feedback tools. However, challenges emerged related to device limitations, technical competence, and overreliance on automated features. The study concludes that AI-based learning media serve not only as technological tools but also as pedagogical instruments that personalize instruction, foster digital literacy, and transform reading classrooms into more adaptive, interactive, and student-centered environments.
Abstract:The development of artificial intelligence (AI) technology has serious implications for the criminal justice system in Indonesia. The emergence of new forms of crime such as cyber laundering, deepfakes, and digital data…
manipulation raises questions about who should be held accountable. This study aims to examine the main challenges in applying criminal law to AI-based entities and offer normative and practical solutions to ensure legal certainty. By using a normative juridical approach and a literature review of Indonesian positive legal regulations and doctrines, this study is expected to contribute to the formation of a ius constituendum that is adaptive to the digital era. The results of the study demonstrate the urgency of reforming national criminal law to accommodate the legal status and responsibilities of AI in the Indonesian justice system.
Abstract:This study explores how incorporating artificial intelligence improves institutional resilience and overcomes the rigidity of conventional, data-based methods to alter financial risk management. To find patterns in AI applications,…
applications, resilience theory, and integration pathways, a qualitative systematic literature review was carried out utilizing theme synthesis in accordance with PRISMA peer-reviewed protocols. Findings show that AI techniques, machine learning for tail-risk detection, deep learning for high-frequency forecasting, and explainable AI for transparent decisions, yield up to 28% reductions in forecasting errors and halve recovery times during crises. The hybrid CNN Transformer architectures and transformer-based NLP models significantly enhance predictive accuracy and forward-looking insights. The study suggests financial institutions adopt integrated AI frameworks, invest in data quality and human–AI collaboration, and implement principle-based governance to balance innovation with fairness and stability. Limitations include reliance on published literature and limited representation of emerging AI models, warranting future longitudinal and context-specific empirical research.