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The community service activities aim to improve business financial management skills and student readiness in facing the 2026 Indonesian Student Innovation and Entrepreneurship Festival (FIKSI). The program is implemented by lecturers of the Digital Business Study Program at Al-Irsyad University Cilacap together with supervising teachers and 26 FIKSI finalist students from SMA Negeri 2 Cilacap, SMA Negeri 3 Cilacap, and SMA Negeri 1 Maos. The main problem faced by partners is the low ability to prepare business financial reports and the use of digital technology in business development. The method used is Participatory Action Research (PAR) through stages of socialization, training, technology implementation, mentoring, evaluation, and program sustainability. The results of the activity show an increase in student understanding and skills in recording transactions, calculating the cost of production, preparing profit and loss and cash flow reports, and utilizing digital financial applications and Artificial Intelligence (AI) to support business development. In addition, supervising teachers received capacity building in assisting students in aspects of financial management and preparing business proposals. The establishment of the Smart Fintech Young Entrepreneur Community is a sustainable strategy for the program to support the development of digital entrepreneurship in schools. This program has proven effective in improving the quality of business and improving students' readiness for entrepreneurship competitions.

This study examines the transformation of business education curricula in response to the rapid expansion of the digital economy. The increasing integration of artificial intelligence, big data analytics, cloud computing, and digital platforms has significantly reshaped industrial demands and professional competencies. Using a qualitative research approach and content analysis, this study explores the challenges and strategic opportunities associated with curriculum transformation in higher education institutions. The findings reveal that universities face critical challenges related to technological infrastructure, faculty readiness, curriculum relevance, and industry alignment. However, digital transformation also provides opportunities for interdisciplinary learning, experiential education, global collaboration, and technology-driven innovation. The study emphasizes the importance of adaptive leadership, faculty development, industry partnerships, and student-centered pedagogies in supporting sustainable curriculum reform. Ultimately, transforming business education curricula is essential for preparing graduates with digital competencies, critical thinking abilities, and innovative skills necessary to compete effectively in the global digital economy.

This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management

The development of Artificial Intelligence (AI) technology has created various digital innovations, but it has also generated new forms of crime through the misuse of deepfake technology. This study aims to analyze the legal liability of social media platforms for the dissemination of AI-based deepfake content and the forms of legal protection for victims of digital fraud, particularly elderly groups, in the case of the “magical money ritual” scam using the identity of Ujang Busthomi. This research employs normative legal research methods using statutory and case approaches. The results show that perpetrators of deepfake fraud can be held criminally liable under Article 28 paragraph (1) in conjunction with Article 45A paragraph (1) of the Electronic Information and Transactions Law and Article 378 of the Indonesian Criminal Code concerning fraud. In addition, social media platforms as Electronic System Providers also bear preventive and repressive responsibilities under the ITE Law, Government Regulation on Electronic Systems and Transactions, and the Personal Data Protection Law to prevent the spread of illegal content. Legal protection for victims is carried out through criminal law enforcement, personal data protection, restitution mechanisms, and the enhancement of digital literacy in society.

Digital transformation in Human Resource Management (HRM) has shifted the organizational paradigm from an administrative function to a strategic function focused on adaptive and sustainable human resource development. This study aims to systematically review the integration of digital technology in HRM practices with particular emphasis on inclusivity and organizational sustainability. The method employed is a literature review analyzing various studies related to the implementation of Artificial Intelligence (AI), big data analytics, and digital systems in recruitment, competency development, and employee performance evaluation. The findings indicate that digital transformation enhances operational efficiency, decision-making quality, and workplace flexibility. However, the adoption of digital technology also creates ethical challenges, including algorithmic bias, unequal access to technology, and concerns regarding employee data privacy. Therefore, the implementation of Equity, Diversity, and Inclusion (EDI) principles is essential in developing fair and inclusive HRM systems. Furthermore, continuous learning cultures and flexible work models have proven effective in supporting employee well-being while strengthening organizational resilience in facing global changes. This study emphasizes the importance of synergy between technological innovation, ethical leadership, and sustainability in building HRM systems that are responsive to the future of work.

The rapid advancement of artificial intelligence (AI) has significantly altered the landscape of business decision-making, particularly for Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. Despite their critical role in economic growth and employment generation, MSMEs frequently encounter substantial barriers related to technological adoption, digital literacy, and resource allocation. This research systematically investigates the utilization of artificial intelligence as a responsive innovation mechanism designed to optimize decision-making processes within the MSME sector. By employing a comprehensive systematic literature review methodology, analyzing peer-reviewed publications from globally recognized academic databases between 2018 and 2024, this study delineates the multifaceted benefits, complex challenges, and contextualized adoption strategies associated with AI integration. The findings reveal that artificial intelligence holds transformative potential for enhancing operational efficiency, refining predictive analytics, and sustaining long-term competitiveness. Conversely, critical challenges, including inadequate digital infrastructure, financial constraints, and organizational resistance, remain pervasive obstacles. Consequently, the study advocates for a gradual, responsive innovation approach that aligns technological adoption with specific business needs and environmental pressures. The insights derived from this research offer substantial theoretical and practical implications, providing a strategic framework for policymakers and MSME owners to accelerate digital transformation inclusively.

Digital transformation has positioned artificial intelligence (AI) as a major driver of organizational change and innovation. This study aims to analyze the influence of AI implementation on transformational leadership dynamics and the shifting role of leaders in managing human resources through a Systematic Literature Review of reputable studies published within the last five years. The findings indicate that AI acts as a catalyst in strengthening the dimensions of intellectual stimulation and individualized consideration through predictive analytics and talent personalization. The automation of administrative and repetitive tasks enables leaders to focus more on strategic vision, organizational innovation, decision-making, and emotional engagement with employees. However, the effectiveness of AI implementation is highly dependent on leaders’ digital literacy, adaptive capabilities, and readiness to integrate technology into organizational processes. This study contributes by proposing a hybrid leadership framework that combines artificial intelligence with human emotional intelligence to support more effective leadership practices. The practical implications emphasize the importance of leadership development that prioritizes empathy, ethical awareness, and algorithmic transparency in order to maintain trust, encourage sustainable innovation, and strengthen organizational resilience in increasingly dynamic and volatile environments.

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 describe the transformation of Biology learning through the integration of Artificial Intelligence (AI) to strengthen 21st-century skills at a State Senior High School in Waingapu, East Sumba. Amidst the limitations of physical laboratory facilities, AI emerges as an innovative solution to visualize abstract biological concepts. This research employs a qualitative approach, with data collection techniques involving observation, interviews with teachers and students, and documentation studies. The results indicate that the utilization of AI platforms, such as Generative AI and virtual simulations, significantly shifts the student learning paradigm from rote memorization to active inquiry. The integration of AI has proven effective in reinforcing the 4C skills (Critical Thinking, Creativity, Collaboration, and Communication). Students have become more critical in validating information, creative in designing science projects, and more collaborative in classroom discussions. Furthermore, AI assists teachers in streamlining instructional time, allowing for deeper conceptual exploration. Despite challenges regarding local internet stability, this transformation represents a strategic step in narrowing the educational quality gap between peripheral and urban areas. In conclusion, the implementation of AI, coupled with adaptive teacher guidance, is highly effective in developing competitive students in the digital era.

Digital transformation has brought fundamental changes to the structure and dynamics of modern industrial economics. Technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and big data not only modify production and distribution processes but also revolutionize marketing strategies and patterns of industrial competition. This study is motivated by the need to understand how digital marketing transformation influences the development of competitive advantage through changes in digital market structure from an industrial economics perspective. In this context, digital marketing functions as a strategic instrument that integrates technology, data, and consumer behavior into market mechanisms. The analysis shows that digitalization creates a network-based market structure characterized by the concentration of economic power in major digital platforms and dominance in data control. This structure affects the intensity of competition, the direction of innovation, and patterns of industry differentiation. Digital marketing transformation enhances efficiency, expands market access, and lowers entry barriers for new players, yet it also creates competitive imbalances due to the dominance of large platforms.Through a digital Structure–Conduct–Performance (SCP) approach, the study finds that market structure acts as an intermediary variable that channels the impact of digitalization on competitive advantage. Digitalization significantly promotes industrial efficiency, innovation, and profitability. Proposed strategic solutions include strengthening digital literacy, developing adaptive regulations, and fostering cross-sector collaboration to create an inclusive, competitive, and sustainable digital industrial ecosystem

This research investigates how digital transformation contributes to innovation in public services as part of the move toward smart governance. The study employs a literature review approach by evaluating a variety of pertinent materials, which include global journals, scholarly books, and official publications from the years 2018 to 2025. Results show that digital transformation notably enhances the quality of public services regarding their efficiency, effectiveness, openness, and ease of access. The incorporation of technologies like e-government platforms, mobile apps, artificial intelligence, and big data analysis allows governments to provide services that are quicker and more responsive. Additionally, digital platforms foster public involvement by offering means for communication and participation in decision-making activities. Despite these advancements, there are still several obstacles to overcome, such as the digital divide, insufficient infrastructure, low levels of digital skills, and resistance to change within bureaucracy. These issues emphasize the need for cohesive strategies that include investment in technology, development of human resources, and regulatory assistance. The study concludes that digital transformation is vital for achieving smart governance; however, its effectiveness relies on the preparedness of infrastructure, institutions, and society to embrace digital advancements.

This study aims to develop and implement an artificial intelligence-based reading learning application using Deep Learning technology to enhance the literacy skills of eighth-grade junior high school students. The research employed the Kemmis & McTaggart Classroom Action Research model combined with a mixed-methods approach. Data collection involved pretests and posttests, complemented by observations, interviews, and questionnaires. The findings revealed that the use of this application significantly improved students' reading comprehension, question-answering skills, and overall engagement in the learning process. Key features of the application, such as adaptive learning technology, allowed for real-time adjustments to the difficulty level of the material, which catered to each student’s individual learning pace. Additionally, the provision of instant feedback enhanced the learning experience by helping students understand their progress and areas for improvement. These results suggest that the application is an effective tool in fostering literacy development and aligns with the goals of the Independent Curriculum. Consequently, this Deep Learning-based application offers a promising innovation for improving student literacy skills in the digital age. 

The rapid development of digital technology in the 21st century has brought significant changes to various aspects of life, including education. One of the emerging innovations in the educational field is the use of Artificial Intelligence (AI) as a tool to support the learning process. The integration of AI in history education offers new opportunities to create more interactive, adaptive, and contextual learning experiences through access to various digital historical sources. This study aims to analyze the integration of Artificial Intelligence in history learning and its implications for improving students’ digital historical literacy. This research uses a qualitative approach with a descriptive method through a literature study by reviewing various scientific articles related to the use of AI in education and digital literacy in history learning. The findings indicate that the use of Artificial Intelligence can assist students in accessing, analyzing, and understanding various digital historical sources more broadly through interactive media such as online archives, historical simulations, and technology-based learning platforms. In addition, the integration of AI can increase student engagement in the learning process, encourage critical thinking skills, and support more personalized learning based on students’ needs and abilities. However, the implementation of this technology must be accompanied by the strengthening of digital historical literacy as well as the application of academic integrity, ethical principles, and responsible use of technology. Therefore, the proper integration of Artificial Intelligence can serve as an innovative strategy to enhance the quality of history education in the digital era.

This study aims to analyze the implementation of Artificial Intelligence (AI)-based learning media and its implications for student learning motivation in Islamic Religious Education (PAI). This study uses a systematic literature review approach by examining various reputable scientific articles discussing the integration of AI in education and the dynamics of learning motivation in the context of PAI. The results of the study indicate that the use of AI through adaptive learning systems, educational chatbots, gamification, and learning analytics can increase the effectiveness, personalization, and interactivity of learning. This implementation has a positive impact on cognitive motivation through increased conceptual understanding, affective motivation through active participation and emotional engagement, and spiritual motivation through strengthening reflection and internalization of Islamic values. However, ethical challenges, the risk of depersonalization of the teacher's role, and inequality in digital access are crucial issues that require policy attention and human-centered pedagogical design. Theoretically, this study offers an integrative conceptual framework that combines technological innovation with Islamic educational epistemology. Practically, the results of this study provide recommendations for teachers, schools, and policymakers to develop AI-based PAI learning models that are adaptive, ethical, and oriented towards character building.

Open-pit mining activities in Indonesia contribute significantly to the national economy but require stringent monitoring to mitigate environmental degradation. Conventional monitoring methods relying on terrestrial surveys are often constrained by vast coverage areas, high operational costs, and limited field accessibility. This study aims to develop an artificial intelligence model capable of automatically detecting and mapping mining areas to enhance surveillance efficiency. The applied method is Deep Semantic Segmentation utilizing the U-Net Convolutional Neural Network (CNN) architecture. The model was trained using Sentinel-2 satellite imagery, focusing exclusively on Red, Green, and Blue (RGB) spectral channels to replicate human visual perception. Experimental results demonstrate that the proposed model performs reliable segmentation of mining areas, achieving an Accuracy of 93.58% and a Global Intersection over Union (IoU) of 0.8067. These findings indicate that the U-Net architecture can effectively extract spatial features of mines even when utilizing standard visual data. This research contributes to the development of an efficient, cost-effective, and scalable digital monitoring prototype to support innovation in sustainable environmental governance.

The rapid development of Artificial Intelligence (AI) technology presents significant opportunities to improve the quality of learning; however, its utilization in school settings is still constrained by teachers’ limited competencies. This community service program aims to enhance teachers’ competencies in utilizing AI-based learning technologies in a pedagogical, ethical, and practical manner. The implementation method consisted of preparation, implementation, and evaluation stages. The activities were carried out through interactive workshops, demonstrations of AI-based educational tools, hands-on practice with mentoring, and evaluation using pre-tests and post-tests. The results indicate a significant improvement in teachers’ understanding and skills in using AI for lesson planning, instructional media development, and learning assessment. Teachers also demonstrated more positive attitudes and greater confidence in integrating AI into classroom practices. Nevertheless, challenges such as varying levels of digital literacy and limited technological infrastructure were still identified. Overall, this community service activity proved effective in improving teachers’ competencies and has the potential to support more innovative and adaptive learning transformation in the digital era.

The advancement of Artificial Intelligence (AI) presents substantial potential for improving the quality of learning in elementary education, particularly through the application of AI prompts as instructional support in lesson planning and classroom implementation. Nevertheless, many teachers at Integrated Islamic Elementary Schools (Sekolah Dasar Islam Terpadu/SDIT) experience limited AI literacy and insufficient competence in designing pedagogically appropriate and effective AI prompts. This community service program aims to enhance AI literacy and strengthen the professional competence of teachers at SDIT Lukmanul Hakim Puring, Kebumen, in utilizing AI prompts to support instructional design, teaching materials development, and learning assessment. The program employed participatory methods, including socialization sessions, hands-on training, guided practice, and continuous mentoring. The results demonstrate a measurable improvement in teachers’ understanding and practical skills in constructing AI prompts aligned with pedagogical objectives. Furthermore, the integration of AI prompts contributes to increased instructional efficiency and pedagogical creativity. This program is expected to provide a sustainable model for supporting digital transformation in elementary school education.

The rapid advancement of Artificial Intelligence (AI) is reshaping public governance, including legislative processes. In the United Arab Emirates (UAE), AI is being actively utilized to enhance law-making through faster drafting, improved consistency, and greater transparency. This study examines the role of AI in the UAE’s legislative functions, focusing on how AI tools assist in analyzing legal data, formulating policy recommendations, and drafting legislation. It explores how AI impacts the speed, accuracy, and legitimacy of law-making, while also addressing the ethical and legal challenges of delegating legislative tasks to intelligent systems. Using a qualitative case study method, the paper evaluates government initiatives, expert insights, and regulatory structures that frame AI's integration into the UAE’s law-making system. While AI offers opportunities for data-driven governance and increased legislative productivity, it also presents risks such as algorithmic bias, reduced human oversight, and accountability gaps. The study emphasizes that AI must be governed by strong regulatory frameworks to safeguard democratic values, fairness, and legal integrity. By analyzing a pioneering national model, this research contributes to global discussions on AI in governance and offers key insights for policymakers, technologists, and legal scholars seeking to balance innovation with ethical and legal standards.

This research investigates the integration of Smart Production Systems (SPS) within the framework of Industry 5.0, emphasizing how such integration redefines operational efficiency and human–machine collaboration. The study aims to identify the contributions of smart technologies to productivity, sustainability, and human value in modern production systems. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines, drawing from international databases including Elsevier, Springer, IEEE Xplore, Wiley, Taylor & Francis, ACM, and SAGE, as well as national sources. Publications from 2023–2025 were screened using keywords such as “Industry 5.0,” “Smart Production Systems,” “Human–Machine Collaboration,” and “Operational Efficiency.” Thematic analysis categorized findings into four dimensions: operational efficiency, human–machine collaboration, industrial sustainability, and socio-ethical aspects. Results indicate that SPS integration significantly enhances operational efficiency while fostering adaptive and creative collaboration between humans and machines. The combination of Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and human creativity establishes a resilient, sustainable, and innovative production paradigm. Successful implementation of Industry 5.0 requires harmonizing technological advancement, human skills, and ethical principles. Practically, the study offers insights for industry stakeholders and policymakers in designing human-centered digital transformation strategies, strengthening supply chain resilience, workplace safety, and innovation. This research contributes conceptually by highlighting ethical and sustainable human–machine interactions in future production systems.

The rapid development of generative Artificial Intelligence (AI) technology offers significant efficiency opportunities across various sectors; however, empirical research within the local Indonesian context, particularly in Batam City, remains scarce. This exploratory study aims to analyze the influence of positive perception, negative perception, and AI regulation understanding on technology adoption trends, as well as productivity and product innovation opportunities among creative industry players. The creative industry is a focal point due to the inherent tension between technological efficiency and the preservation of human originality in the creative process. This research employs a quantitative causal approach, utilizing a sample of 30 respondents reached through snowball sampling techniques. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The findings reveal that only positive perception has a significant direct impact on product innovation (p=0.004), while AI regulation and technical adoption do not show significant effects. This suggests that a positive technology mindset is a more decisive factor for innovation than technical mastery or current regulatory compliance. These results underscore the urgent need for local government socialization of AI policies and enhanced digital literacy for Batam's creative practitioners to transform them from mere users into strategic AI-driven innovators.