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The acceleration of digitalization in recent years has shaped a new socio-economic landscape in Indonesia. Access to app-based financial services and online entertainment has increased rapidly, but at the same time, illegal online lending and digital gambling, targeting adolescents, have flourished. This paper explores a Community Service intervention model that combines preventative digital literacy and artificial intelligence (AI) optimization within the La Tansa Islamic Boarding School in Palembang. The research was conducted using a qualitative approach with participant observation, in-depth interviews, focus group discussions, and written reflection analysis. Findings indicate that strengthening digital literacy based on critical awareness not only improves risk understanding but also deepens self-control integrated with religious values. AI training for educators also encourages changes in learning practices to be more adaptive and reflective of the dynamics of the digital era. This model offers a digital resilience approach that can be replicated in other educational institutions with similar characteristics.

This community service program addressed the limited capacity of educators to use artificial intelligence in a structured and pedagogically responsible way for textbook development. The program focused on empowering educators through NotebookLM in the Ngabuburit AI 2026 activity. Its objective was to improve participants’ understanding and practical skills in organizing sources, designing textbook structures, developing chapter content, and generating interactive learning media. The program used a participatory training approach consisting of presentation, demonstration, guided practice, discussion, and feedback-based evaluation. The results showed that participants gained a clearer understanding of AI-assisted academic writing workflows and recognized NotebookLM as a useful tool for integrating source analysis, textbook writing, and learning media preparation. The activity also fostered new awareness that artificial intelligence can strengthen, rather than replace, educators’ academic roles in producing more systematic and interactive teaching materials.

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.

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 rapid development of Artificial Intelligence (AI) technology requires an improvement in digital literacy and skills among students, particularly at the vocational high school level. However, many students still lack sufficient understanding of the basic concepts and practical applications of generative AI in learning. This Community Service Program (Pengabdian kepada Masyarakat/PKM) aims to enhance students’ understanding of AI technology through generative AI training at SMK Al-Muhajirin Depok. The methods used in this program include interactive lectures, demonstrations of generative AI applications, and hands-on practice sessions. The activity was attended by 30 students and supported by the school management. The results indicate a significant improvement in students’ understanding of generative AI concepts and their ability to apply the technology in a simple learning context. In addition, students gained awareness of the ethical use of AI in an appropriate and responsible manner. Therefore, this PKM activity contributes positively to improving students’ digital literacy and readiness to face technological advancements in the modern 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 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 development of artificial intelligence (AI) has brought about significant changes in higher education, particularly in how students acquire, understand, and manage academic information. This study aims to deeply understand students' experiences using AI as a learning tool and explore how they interpret the technology's role in supporting academic activities. A qualitative phenomenological approach was used, with three informants selected purposively from various study programs actively using AI. Data were collected through semi-structured interviews, observation, and documentation, then analyzed using data reduction, data presentation, and conclusion drawing. The results show that students view AI as an effective tool for improving learning efficiency, deepening conceptual understanding, and motivating them to be more independent and creative. However, challenges were also identified, including dependence on technology, doubts about the accuracy of information, and concerns about academic ethics violations such as digital plagiarism. Student experiences also demonstrate that AI plays a dual role as both a learning tool and a cognitive partner in the modern learning process. Therefore, the use of AI needs to be directed wisely and accompanied by strong digital literacy to balance technological convenience and the development of critical thinking skills. These findings emphasize the importance of adaptive, humanistic, and ethical learning strategies in the era of digital higher education transformation.

The rapid advancement of digital technology in higher education has transformed learning and assessment systems, particularly through the adoption of Learning Management Systems (LMS) and Computer-Based Tests (CBT). However, many university students still face challenges in adapting to digital examination environments due to limited technical experience and digital literacy. This Community Service Activity (PKM) aims to enhance students’ academic readiness and digital competence through the implementation of a Moodle-based LMS at Universitas Murni Teguh. The activity was conducted in the form of an interactive workshop, including system introduction, simulation of CBT, guided practice, and discussion sessions involving university students and lecturers. The results showed a significant improvement in students’ understanding of LMS features, confidence in using CBT systems, and ability to manage digital-based examinations effectively. Active participation and engagement during the sessions reflected high enthusiasm and adaptability toward digital learning transformation. This activity demonstrates that the implementation of LMS Moodle is effective in improving academic preparedness and digital literacy among students, and can serve as a sustainable model for strengthening technology-based learning in higher education institutions.

The rapid advancement of digital technology in higher education has transformed learning and assessment systems, particularly through the adoption of Learning Management Systems (LMS) and Computer-Based Tests (CBT). However, many university students still face challenges in adapting to digital examination environments due to limited technical experience and digital literacy. This Community Service Activity (PKM) aims to enhance students’ academic readiness and digital competence through the implementation of a Moodle-based LMS at Universitas Murni Teguh. The activity was conducted in the form of an interactive workshop, including system introduction, simulation of CBT, guided practice, and discussion sessions involving university students and lecturers. The results showed a significant improvement in students’ understanding of LMS features, confidence in using CBT systems, and ability to manage digital-based examinations effectively. Active participation and engagement during the sessions reflected high enthusiasm and adaptability toward digital learning transformation. This activity demonstrates that the implementation of LMS Moodle is effective in improving academic preparedness and digital literacy among students, and can serve as a sustainable model for strengthening technology-based learning in higher education institutions.

Financial distress is a condition of declining financial health of a company that can develop gradually and lead to business failure if not detected early. With the increasing complexity of the business environment and the limitations of conventional statistical methods, Artificial Intelligence/AI is increasingly being adopted in the development of early warning systems (EWS) to predict financial distress. This study aims to examine the development of AI-based EWS research, identify the most widely used algorithms, and evaluate the effectiveness of AI models compared to conventional methods in predicting financial distress. The method used is a comprehensive systematic literature review of 15 relevant scientific articles. The results show that the paradigm has shifted from statistical models to machine learning and deep learning. Random Forest and Artificial Neural Network are the most widely used algorithms and have better predictive performance. This study offers a conceptual synthesis of the progress, effectiveness, and challenges of applying AI in predicting financial distress and opens opportunities for further research on the development of contextual and interpretative EWS.

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 development of Artificial Intelligence (AI) technology has opened significant opportunities to support maritime monitoring systems, particularly in detecting anomalies in ship movements that may indicate illegal or abnormal activities. However, the understanding and utilization of this technology among the general public and maritime stakeholders remain limited. This Community Service Program aims to conduct socialization and dissemination of knowledge on AI-based ship anomaly detection through the development and utilization of an interactive and informative web-based socialization platform. This activity is the result of collaboration between a team of lecturers from the Faculty of Communication and Informatics Technology (FTKI) and the National Research and Innovation Agency (BRIN). The implementation methods include the design of web-based educational content, presentation of fundamental AI concepts and ship anomaly detection, as well as visual simulations of ship movement data analysis results. The web-based socialization platform serves as an educational medium to enhance users’ understanding of the benefits, working mechanisms, and potential applications of AI technology in maritime surveillance. The results indicate an improvement in participants’ understanding of ship anomaly detection concepts and the role of artificial intelligence in supporting maritime security and safety. This PKM activity is expected to promote technological literacy, strengthen synergy between academia and research institutions, and serve as a model for practical and sustainable web-based technology socialization

This study aims to analyze the transformative impact of digitalization and technology in the manufacturing sector on improving operational efficiency, particularly in budgeting and resource utilization, as well as to identify the main barriers to technology adoption. Using a Literature Review and Case Study Analysis of secondary data (journals, company reports, and industry publications), it was found that digitalization and Automation supported by Artificial Intelligence (AI) fundamentally transform budgeting functions. This transformation has been shown to improve budget accuracy by up to 50% (reducing human errors) and process efficiency by up to 25%, turning budgets from static documents into adaptive and predictive control tools. Positive impacts are also observed in operations through increased production capacity (revenue surge) and the implementation of Predictive Maintenance, which reduces expenditure and asset downtime, in line with the principles Cost Efficiency and Lean Manufacturing. Nevertheless, the adoption of advanced technology faces significant obstacles, namely high initial capital investment and skill gaps among the workforce. It is concluded that the success of digitalization heavily depends on strategic budget planning to overcome capital barriers and adequate allocation of funds for Human Resource (HR) training to support effective collaboration between humans and machines.

This research was designed not only to measure the direct impact of Artificial Intelligence (AI)-based digital teaching materials on motivation and learning outcomes but also to identify the factors influencing the effectiveness of their implementation in the context of a high school in an island area. The objectives of this study are: (1) To determine the significant effect of using Artificial Intelligence (AI)-based digital teaching materials on the learning motivation of Class XII students at SMAN 1 Kepulauan Selayar. And (2) To determine the significant effect of using Artificial Intelligence (AI)-based digital teaching materials on the learning outcomes of Class XII students at SMAN 1 Kepulauan Selayar. This study uses a quantitative approach through an experimental design to test the hypothesis regarding the significant effect of using Artificial Intelligence (AI)-based digital teaching materials on student motivation and learning outcomes in Economics. A sample of 30 Class XII students will be randomly selected. Data collection techniques include Questionnaires, Tests, observation, and documentation. The results of this study indicate (1) A significant and positive effect of the use of Artificial Intelligence (AI)-based digital teaching materials on the learning motivation of Class XII students at SMAN 1 Kepulauan Selayar. (2) The use of Artificial Intelligence (AI)-based digital teaching materials (X) significantly influences Economics learning outcomes (Y2).

The use of Artificial Intelligence (AI) in higher education learning has increased significantly, particularly among Informatics Engineering students. Although AI provides various benefits in supporting the learning process, its utilization also raises ethical concerns, especially related to algorithmic bias and responsible use of technology. This study aims to analyze the perceptions of Informatics Engineering students regarding bias and ethics in the use of artificial intelligence in learning. The research employed a quantitative descriptive approach. Data were collected through a Likert-scale questionnaire distributed to 80 Informatics Engineering students who had experience using AI in learning activities. Descriptive statistical analysis was conducted using mean scores and percentages. The results indicate that students demonstrate a high level of ethical awareness and responsibility in using AI; however, their perception of potential bias in AI systems remains at a moderate level. These findings reveal a gap between normative ethical awareness and critical understanding of algorithmic bias. This study recommends strengthening contextual and applied AI ethics literacy within the Informatics Engineering curriculum to promote responsible and ethical use and development of artificial intelligence technologies.

The need for learning materials that can adapt to students’ abilities and characteristics has made the development of AI-based adaptive learning resources increasingly important in elementary education. However, limited digital literacy and high workloads among teachers hinder optimal implementation. This Community Service Program aimed to enhance the competencies of teachers at Sekolah Alam Ananda Mandiri Slawi through workshops, guided practice, and hands-on development of AI-supported adaptive materials. The method included preparation, conceptual presentation, technology demonstration, guided practice, pre–post evaluation, and follow-up support. The results showed a significant improvement, with teachers’ competence in the “good” category increasing from 22.5% to 82.5%, and all participants (100%) successfully producing at least one adaptive module and one deep-learning-based material component. Furthermore, 92% of participants reported that the program greatly improved their digital literacy and pedagogical understanding. Thus, this activity effectively strengthened teachers’ competencies and provided a strong foundation for the sustainable integration of AI-based adaptive learning materials in elementary classrooms.

Digital transformation and advances in artificial intelligence (AI) have fundamentally changed the demands of the workplace, creating a gap between graduate competencies and industry needs. This study aims to evaluate the effectiveness of AI Agent-based career adaptability psychoeducation as a community empowerment strategy to improve the work readiness of high school/vocational school and university graduates. The study design used a descriptive-interventional approach with 27 participants who participated in a four-week online training. Data were collected through a pre-post survey using the Career Adapt-Abilities Scale (CAAS) and qualitative observations during the training. The results of the Wilcoxon Signed-Rank test showed a significant increase in career adaptability scores (Z = –4.543, p < .001), with all participants experiencing increased career adaptability. Observations showed that participants became more confident, reflective, and proactive in designing their career directions after interacting with the AI ​​Agent. These findings indicate that psychoeducational interventions integrated with intelligent technology can strengthen the adaptive capacity and work readiness of the younger generation. Theoretically, this study expands the application of the career adaptability concept in the context of AI-based learning; In practice, the results provide a relevant community empowerment model for educational and employment institutions in the era of digital disruption.

Digital transformation and advances in artificial intelligence (AI) have fundamentally changed the demands of the workplace, creating a gap between graduate competencies and industry needs. This study aims to evaluate the effectiveness of AI Agent-based career adaptability psychoeducation as a community empowerment strategy to improve the work readiness of high school/vocational school and university graduates. The study design used a descriptive-interventional approach with 27 participants who participated in a four-week online training. Data were collected through a pre-post survey using the Career Adapt-Abilities Scale (CAAS) and qualitative observations during the training. The results of the Wilcoxon Signed-Rank test showed a significant increase in career adaptability scores (Z = –4.543, p < .001), with all participants experiencing increased career adaptability. Observations showed that participants became more confident, reflective, and proactive in designing their career directions after interacting with the AI ​​Agent. These findings indicate that psychoeducational interventions integrated with intelligent technology can strengthen the adaptive capacity and work readiness of the younger generation. Theoretically, this study expands the application of the career adaptability concept in the context of AI-based learning; In practice, the results provide a relevant community empowerment model for educational and employment institutions in the era of digital disruption.