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The field of education, especially Islamic Religious Education (PAI), has seen substantial changes as a result of the advancement of digital technology and artificial intelligence (AI). The existence of digital media and AI offers numerous opportunities to improve the effectiveness, efficiency, and quality of education through interactive, flexible, and easily accessible learning resources. The purpose of this article is to analyze how artificial intelligence (AI) and digital media are used in Islamic Religious Education. This includes the idea of AI and digital media, AI-based learning materials, the use of AI in educational activities, ethical considerations of AI use, the effects and difficulties of integrating AI, and the Islamic viewpoint on technological advancement. This study employed a library research method by collecting data from relevant journals, books, and other scholarly sources. The findings indicate that the use of AI and digital media in PAI learning can enhance access to information, personalize learning experiences, improve evaluation effectiveness, and increase student engagement in the learning process. However, the implementation of AI also presents several challenges, such as limited digital literacy among teachers, inadequate facilities and infrastructure, ethical concerns, and the potential decline of direct educational interaction between teachers and students. Therefore, the utilization of AI in Islamic Religious Education should be carried out wisely while maintaining Islamic values, ethics, and the primary goal of Islamic education in shaping students’ character.

In the era of the Industrial Revolution 4.0 and Society 5.0, digital technology is developing rapidly. This has prompted the world of education to make major changes in learning methods, including in Islamic Religious Education (PAI). Until now, PAI has used outdated methods. These methods are inadequate to meet the needs of children who are accustomed to technology. Therefore, there is a need for technology integration in the learning process. This study aims to determine how to use E-Learning, Learning Management Systems (LMS), and Artificial Intelligence (AI) in PAI learning. This study also aims to determine the benefits, challenges, and strategies for implementing these technologies. This study used a qualitative approach with a literature review type. Data were obtained from various sources, such as books, scientific articles, journals, and relevant documents. The results show that the use of E-Learning, LMS, and AI can improve the quality of PAI learning. E-Learning makes learning easier and more flexible. LMS helps manage learning more systematically. AI helps make learning more personalized and tailored to students' needs. However, the implementation of these technologies still faces several challenges, such as limited infrastructure and low digital skills of teachers and students. Therefore, a strategy is needed to address these challenges. This strategy includes enhancing digital capabilities, strengthening technological infrastructure, developing innovative learning media, and monitoring the use of technology based on Islamic values. This will ensure optimal integration of technology into Islamic Religious Education learning.

The rapid growth of digital commerce has encouraged companies to integrate digital and physical marketing channels to create seamless and consistent customer experiences. This study aims to analyze the role of integrated marketing channels through omnichannel strategies, the utilization of Artificial intelligence (AI), and their impact on customer experience in the context of digital commerce. The study employs a Systematic literature review (SLR) approach by examining relevant scholarly articles related to omnichannel marketing, AI technologies, and customer experience. The findings indicate that integrated marketing channels supported by AI enhance service personalization, customer engagement, operational efficiency, and the quality of interactions between companies and customers. Furthermore, the implementation of omnichannel strategies contributes to higher customer satisfaction and loyalty by providing a more connected experience across multiple customer touchpoints. However, the implementation of integrated marketing channels still faces several challenges, including fragmented channel integration, technological complexity, high investment requirements, and concerns regarding customer data privacy and security. Therefore, effective management of integrated marketing channels is essential for improving customer experience while creating sustainable competitive advantages for companies in an increasingly dynamic digital era.

Bullying is a serious problem that can disrupt the learning process and mental development of students, including in Islamic boarding schools. Early detection of bullying is essential to creating a safe and conducive learning environment. This study aims to apply the You Only Look Once (YOLO) algorithm to automatically detect bullying through video recordings in the environment of the SMK Skill Village Islamic School Business Boarding School. The method used involves collecting a video dataset representing various types of bullying behavior, labeling the data, and training an object detection model using the YOLOv5 algorithm. The developed system is capable of detecting and classifying bullying behavior in real- time with detection accuracy reaching [accuracy value if known]. The implementation of this system is expected to assist school authorities and boarding school administrators in monitoring, preventing, and addressing bullying incidents more quickly and effectively, while also serving as an initial step in leveraging artificial intelligence technology to create a safer and more comfortable educational environment.

The rapid development of Artificial Intelligence (AI) has transformed various sectors of human life, including church ministry and religious organizational management. This study aims to analyze Christian leadership ethics in the use of AI within modern church ministry. The research employs a qualitative descriptive method through theological literature review and analysis of recent studies concerning digital technology and pastoral ministry. The findings indicate that AI provides significant benefits for church administration, digital communication, congregational data management, and online evangelism. Nevertheless, ethical challenges also emerge, such as the weakening of pastoral relationships, data privacy concerns, algorithmic bias, and the risk of dehumanization in ministry practices. From a Christian theological perspective, ministry is fundamentally relational and incarnational, reflecting the example of Jesus Christ who ministered through personal presence, compassion, and direct interaction with people. Therefore, AI should be understood as a supportive instrument rather than a substitute for spiritual authority and pastoral presence. Christian leadership in the digital age must be grounded in integrity, transparency, spiritual discernment, and respect for human dignity as the image of God (imago Dei). This study contributes to the development of ethical guidelines for churches in utilizing AI responsibly while maintaining theological integrity and Christian spiritual values.

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.

.This study aims to analyse the role of Financial Information Systems (FIS) in supporting risk management, decision-making, and organisational performance in the digital transformation era. This study employs the Systematic Literature Review (SLR) method to examine articles indexed in Scopus from 2016 to 2026. The PRISMA framework is used to ensure a systematic, transparent article selection process, resulting in the selection of 37 relevant articles for further analysis. The results of the study show that Financial Information Systems make a major contribution to improving financial transparency, operational efficiency, the quality of strategic decision-making, and organisational risk mitigation. In addition, the integration of emerging technologies such as Artificial Intelligence (AI), FinTech, big data analytics, and cloud computing further strengthens the effectiveness of financial information systems in modern organisations. This study contributes theoretically by mapping research trends and identifying research gaps, while providing practical benefits for organisations seeking to increase competitiveness through digital financial systems. For future research, it is recommended to develop a more predictive and intelligent Financial Information Systems model to address future business dynamics.

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.

In the field of education, cheating remains a critical issue of academic dishonesty. This phenomenon does not merely affect students' grades but also obstructs the development of core character values, including integrity, responsibility, and independence in the pursuit of knowledge. This article aims to analyze the factors influencing cheating behavior and evaluate various forms of intervention from the perspective of early detection of problematic behavior. This study employs a literature review method, examining 20 relevant scientific articles published between 2021 and 2026. The findings reveal that cheating behavior is influenced by internal factors such as self-efficacy, self-control, self-confidence, religiosity, and self-esteem as well as external factors, including peer conformity, parental pressure, the learning environment, and evaluation systems. Effective interventions include group counseling services, classical guidance, modifications to evaluation systems, and the utilization of Artificial Intelligence-based technology to detect potential academic fraud. Consequently, efforts to prevent cheating behavior require a multidimensional approach involving students, teachers, parents, and school policies to cultivate an academic culture of integrity.

The development of digital technology and artificial intelligence (AI) has increased youth interaction in cyberspace, while also elevating the risk of digital crimes, both as perpetrators and victims. This community service program AIms to strengthen legal awareness and AI-based self-protection skills among students of SMKN 1 Kaligondang, \Purbalingga Regency. The implementation methods include interactive workshops, digital security trAIning, case simulations, and the use of a mini AI assistant as a preventive educational tool. Evaluation was conducted through pre-test and post-test assessments, participatory observation, and participant reflection. The results indicate an improvement in participants’ understanding of digital law, particularly regarding the provisions of the Law on Electronic Information and Transactions and its relevance to the Indonesian Criminal Code. In addition, participants’ technical skills in securing digital accounts, identifying phishing attempts, and responding to cyber risks have also improved. The use of AI has proven to enhance participation and contextual understanding. Overall, the program is effective in fostering legal awareness, improving digital protection capabilities, and shaping responsible behavior in cyberspace.

The advancement of Artificial Intelligence (AI) has brought significant changes to various aspects of life, including the field of education, particularly Islamic Education. This study aims to explore various AI-based learning strategies that can be implemented to create a more effective, interactive, and contemporary learning process. The method employed in this study is a literature review by examining various scholarly sources, such as journals, books, and academic articles discussing the implementation of AI in education. The findings indicate that the integration of AI can be realized through personalized learning tailored to students’ needs, the use of chatbots as learning assistants, the analysis of students’ progress and learning outcomes, as well as the utilization of technology-based learning media. These strategies are not only capable of improving students’ cognitive aspects but can also strengthen the internalization of Islamic values when applied appropriately and systematically. Furthermore, this study emphasizes that teachers’ technological competence, infrastructure readiness, and the development of an adaptive curriculum are crucial factors in the successful implementation of AI-based learning within the context of Islamic Education.

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.

The advancement of digital technology has significantly transformed organizational decision-making, particularly in modern leadership contexts that demand rapid and data-driven responses. Artificial Intelligence(AI) has emerged as a strategic technology capable of enhancing accuracy, speed, and effectiveness in decision-making through comprehensive data analysis. This study aims to analyze the role of AI in supporting leadership decision-making and its implications for organizational effectiveness using a narrative literature review approach. Secondary data comprising peer-reviewed national and international journal articles were analyzed to identify patterns, themes, and interactions between AI, leadership, and decision-making processes. The findings indicate that AI functions not only as a data analysis tool but also as a strategic element that strengthens leaders’ capabilities in evidence-based decision-making, improves team coordination, and optimizes organizational processes. Thematic synthesis identified three main domains analytics and predictive capabilities, leadership strategies, and implementation challenges that form the basis for integrating AI into managerial practice. This study contributes theoretically by expanding the digital leadership and technology-based decision-making framework and practically by providing guidance for organizations to optimize AI utilization to enhance decision quality and efficiency. The research also offers directions for future empirical studies to explore AI-leadership interactions across various organizational sectors, supporting more adaptive, effective, and data-driven decision-making in the digital era.

Algorithmic technologies are widely used in contemporary marketing strategies due to the growth of the digital economy. Digital companies can evaluate consumer activity data in real time and provide highly personalized digital experiences thanks to artificial intelligence-based solutions, especially machine learning. In addition to examining how algorithmic governance and surveillance capitalism affect algorithmic personalization, this study looks into how these mechanisms affect consumer engagement, purchase intention, and perceptions of hyperreality within the digital market ecosystem. 356 active users of digital platforms, such as social media and e-commerce, were surveyed as part of this study's quantitative methodology. The links between the constructs in the suggested conceptual model were examined through data analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that the development of algorithmic personalization systems is strongly influenced by data-driven capitalism practices and algorithmic governance. Additionally, it has been demonstrated that algorithmic personalization improves customers' sense of hyperreality and increases their interaction with digital platforms. Additionally, the study shows that the most powerful factor influencing purchase intention is consumer interaction. By combining viewpoints from technology, the political economics of data, and hyperreality theory into a thorough empirical framework, these findings add to the body of knowledge on digital marketing.

This study aims to examine the impact of academic burnout on students’ mental health in the context of hybrid learning through a literature review approach. The rapid transformation of learning systems in higher education, particularly the integration of online and offline methods, has increased academic demands and adaptation challenges for students. This condition potentially triggers academic burnout, which is characterized by emotional exhaustion, depersonalization, and decreased academic achievement. This research employs a literature review method by analyzing relevant scientific articles published between 2019-2025 obtained from indexed national journals and open-access sources. The findings indicate that academic burnout is still commonly experienced by students, generally at a moderate level, and has a significant impact on mental health, including increased stress, emotional fatigue, and decreased academic performance. The study also identifies several influencing factors, including internal factors such as self-efficacy and hardiness, as well as external factors such as social support, learning environment, and academic workload. Furthermore, technological developments, particularly Artificial Intelligence, have the potential to be utilized as an early detection and prevention tool for academic burnout. This study implies the importance of developing adaptive learning strategies and psychological interventions to support students’ well-being in hybrid learning environments.

This study examines the role of Artificial Intelligence (AI) in enhancing student collaborative learning, with a particular emphasis on AI-driven feedback mechanisms and patterns of student interaction in developing effective collaborative skills. Unlike prior studies, this research highlights the mediating effect of AI-driven feedback on teamwork efficiency and overall learning outcomes in collaborative environments. An explanatory quantitative approach was applied using Partial Least Squares Structural Equation Modeling (PLS-SEM) to ensure robust data analysis. Data were collected from 112 university students who were actively engaged in AI-assisted collaborative learning activities, using a structured online survey instrument. The data were subsequently analyzed using SmartPLS software. The results reveal that AI significantly enhances student interaction (β = 0.534, p < 0.000) and improves problem-solving feedback (β = 0.620, p < 0.000), both of which contribute to significantly strengthening collaborative skills (β = 0.716, p < 0.000). However, the findings also indicate that AI alone does not directly improve collaboration without the support of structured pedagogical design and guidance. Therefore, universities should strategically integrate AI-driven feedback into Learning Management Systems (LMS) and strengthen digital literacy initiatives to optimize the effectiveness and sustainability of AI in collaborative learning contexts.

The development of Artificial Intelligence (AI) has transformed how business organizations manage operations, process information, and make strategic decisions, thereby creating a need for leadership patterns that are more adaptive, visionary, and responsive to digital transformation. This study aims to explain the concept of AI Leadership in the business context, identify why modern leadership must adapt to the advancement of AI, and analyze the leadership strategies that are relevant for navigating the era of AI-driven business. The study employs a Systematic Literature Review (SLR) approach with a narrative-thematic synthesis of relevant open-access scholarly literature on AI Leadership, digital leadership, human–AI collaboration, business transformation, and AI ethics. The findings show that AI Leadership represents a modern form of leadership that emphasizes not only technological understanding but also the ability of leaders to direct organizational change, foster data-driven decision making, manage collaboration between humans and technology, and implement responsible AI governance. The study also finds that the main strategies required by leaders in the AI era include strengthening digital literacy, developing adaptive managerial capabilities, enhancing human–AI collaboration, and integrating ethical principles into technology implementation. This article contributes conceptually by reinforcing AI Leadership as a leadership framework that is highly relevant to modern organizations and offers practical implications for the development of business leadership in the era of digital transformation.

The development of artificial intelligence (AI) has transformed organizational landscapes and driven fundamental changes in leadership practices and strategic management. This article aims to critically examine AI-based leadership by highlighting its opportunities, risks, and implications for strategic management. The study employs a qualitative literature-based approach using an integrative literature review strategy. The data consist of secondary scholarly literature relevant to AI, leadership, governance, innovation, and strategic management, which were analyzed through qualitative thematic analysis and conceptual content analysis. The findings show that AI-based leadership creates opportunities in the form of improved decision quality, faster strategic analysis, operational efficiency, stronger innovation, and enhanced organizational agility. However, AI integration also presents risks, including algorithmic bias, limited decision transparency, technological dependency, accountability challenges, and ethical concerns. This study confirms that AI does not fully replace human leaders; rather, it fosters a hybrid leadership model that requires technical, adaptive, transformational, and ethical capabilities. The study implies that the effectiveness of AI-based leadership depends on responsible governance, organizational cultural readiness, and balanced human–machine collaboration in supporting strategic management.

Predictive maintenance (PdM) plays a crucial role in modern industrial systems by minimizing downtime, reducing maintenance costs, and optimizing asset performance. However, many predictive models operate as “black box” systems, limiting transparency and making it difficult for operators to interpret their outputs. This study aims to integrate Explainable Artificial Intelligence (XAI) techniques with Remaining Useful Life (RUL) prediction models to improve both accuracy and interpretability. Various machine learning and deep learning approaches, including Support Vector Machines (SVM), Random Forest (RF), XGBoost, Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN), are employed to predict RUL using real-time sensor data from rotating machinery. XAI methods such as SHAP, LIME, and attention mechanisms are applied to provide human-understandable explanations of model predictions. The models are evaluated based on accuracy, Root Mean Square Error (RMSE), and interpretability scores. The results show that XAI-enhanced models outperform traditional approaches in predictive performance while offering greater transparency. These explanations help maintenance engineers better understand the factors influencing predictions, thereby improving decision-making and trust in the system. Nevertheless, the integration of XAI introduces additional computational complexity, which may pose challenges for large-scale industrial implementation. Overall, this study highlights the potential of combining XAI with RUL prediction to develop more reliable, transparent, and effective predictive maintenance solutions.

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.