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The integration of artificial intelligence (AI) in forensic investigation has significantly transformed the analysis and authentication of digital evidence. This paper explores the role of AI technologies, specifically machine learning and deep learning algorithms, in examining digital evidence from various sources, including computers, mobile devices, and network systems. We provide an in-depth analysis of current AI-based forensic tools, their efficiency in evidence authentication, and the challenges they face regarding legal admissibility. Our findings indicate that AI-powered forensic systems can detect digital evidence tampering with 94.7% accuracy, drastically reducing analysis time from weeks to hours. However, challenges remain, particularly in areas such as algorithmic transparency, bias prevention, and ensuring the integrity of the chain of custody. This research offers a framework for incorporating AI in forensic laboratories, while also addressing crucial legal and ethical concerns to ensure the admissibility of AI-analyzed evidence in court. These considerations are essential for the widespread acceptance and use of AI in forensic investigations.

The development of artificial intelligence has revolutionized higher education by increasing the efficiency and personalization of learning, but it has also posed a major challenge in the form of a decline in students' critical thinking skills due to their dependence on technology. Therefore, an in-depth philosophical study through the post-positivism, critical theory, and constructivism paradigms is needed to understand its impact on cognitive and epistemological processes. This study aims to analyze how these three paradigms guide the development of critical thinking in the context of AI. It uses a descriptive-analytical method based on secondary data from academic literature such as journals and books that have been critically synthesized. The findings show that post-positivism views AI as a tentative critical realism tool for empirical verification. Critical theory critiques power relations, ideology, and the ethics of technological domination. Constructivism emphasizes the construction of social knowledge through human-centered design that supports creativity and collaboration. The positive impacts of AI include instant feedback and content adaptation, while the negative impacts include social isolation, weak digital literacy, and data privacy. Therefore, the implication is the wise use of AI with the assistance of teaching staff to strengthen reflective analysis, ethical literacy, and paradigm adjustments in accordance with the exact or social sciences to create multidimensional learning in the digital era.

The integration of Artificial Intelligence (AI) into educational settings, particularly in formative assessments, offers significant benefits in terms of personalized learning, real time feedback, and increased efficiency. However, the successful implementation of AI driven formative assessments depends not only on technological capabilities but also on socio cultural and organizational factors that shape its adoption. This study explores the socio technical factors influencing the use of AI in formative assessments, emphasizing the importance of considering cultural diversity, institutional culture, and educators' beliefs. AI technologies, while powerful in automating grading and providing personalized assessments, often face limitations in addressing complex student responses that require human judgment. Furthermore, cultural factors, such as students' prior exposure to technology and different cultural attitudes towards AI, play a critical role in the acceptance and effectiveness of these tools. Organizational factors, including leadership support, digital literacy, and the readiness of institutions to adopt AI, are also key determinants in the successful implementation of AI systems in education. Teachers’ beliefs about assessment influence their acceptance and use of AI tools, highlighting the need for professional development and training to ensure that AI enhances pedagogical goals rather than replacing human expertise. The study concludes that the alignment of technology, culture, and assessment beliefs is essential for the effective use of AI driven formative assessments in educational settings. Recommendations for educational institutions include adopting a socio technical approach to AI integration, with a focus on providing resources, training, and fostering a culture of innovation. Future research directions should focus on expanding studies to diverse educational contexts, conducting longitudinal research on AI’s impact on learning outcomes, and exploring additional socio technical frameworks to guide AI adoption in education.

This quasi-experimental study examines the effectiveness of Artificial Intelligence (AI)-assisted learning in enhancing critical thinking skills among undergraduate history students. The study involved 60 students divided into experimental and control groups. The experimental group received AI-supported instruction integrating adaptive learning modules, scaffolded source-analysis prompts, and guided argumentative discussions facilitated by conversational AI tools, while the control group followed conventional lecture-based instruction. Data were collected using a validated critical thinking test, classroom observation protocols, and semi-structured interviews. Quantitative data were analyzed using paired and independent sample t-tests, while qualitative data were examined through Miles and Huberman’s interactive analysis model. Results indicate statistically significant improvements in critical thinking scores in the experimental group compared to the control group. Thematic findings reveal enhanced sourcing, contextualization, corroboration, and evidence-based argumentation skills. However, minor risks of over-reliance on AI highlight the need for instructional scaffolding and ethical guidance. The findings suggest that AI can function as a cognitive scaffold that strengthens historical thinking and metacognitive awareness when implemented within a structured pedagogical framework.

This paper reviews the role of Artificial Intelligence (AI) in Islamic education within secondary schools, emphasizing both its practical uses and the ethical challenges it presents. The review looks into the current trends, tools, and the impact of AI on the learning experience, as well as its ethical implications from an Islamic perspective. The study follows a systematic literature review (SLR) approach based on the PRISMA guidelines and includes research from 2022 to 2025, sourced from platforms like Google Scholar. After a thorough selection process, 15 articles were included in the review, offering valuable insights into the technological and ethical aspects of AI in Islamic secondary education. The use of AI has notably enhanced learning outcomes in Islamic education by allowing personalized learning, boosting student engagement, and streamlining feedback mechanisms. Tools like intelligent tutoring systems and educational chatbots have been widely adopted. However, challenges around data privacy, algorithmic bias, and technology access persist. Additionally, incorporating Islamic ethical values into AI-driven educational platforms presents both opportunities and challenges. Addressing these ethical implications is vital, requiring frameworks that align with Islamic principles such as maṣlaḥa (public welfare), justice, and human dignity. Education policies and teacher training programs should concentrate on promoting the responsible use of AI, ensuring it improves educational experiences while preserving ethical and cultural integrity.

Background: In the domain of corporate governance, the separation of ownership and control generates significant agency conflicts, primarily manifesting as Earnings Management (EM). Traditional reactive auditing methods fail to detect manipulation concealed within unstructured data, leading to high agency costs and diminished stakeholder trust. Objective: This study proposes an "AI Proactive Monitoring Model" utilizing Generative Artificial Intelligence to fundamentally enhance the monitoring mechanisms of Agency Theory. Methods: The research employs a qualitative conceptual framework analysis. It synthesizes Agency Theory with the Technology Acceptance Model (TAM) and Systemic Risk Theory to construct a novel strategic governance model. Results: The proposed model shifts governance from periodic sampling to real-time, continuous analysis of total data populations. By cross-referencing structured financial data with unstructured communications (e.g., emails, contracts), the system generates "Risk Narratives" that contextualize anomalies and flag opportunistic behavior immediately. Conclusion: The integration of AI significantly reduces information asymmetry and moral hazard by creating a "panopticon" effect. However, successful implementation requires distinct regulatory frameworks to manage the systemic risks associated with algorithmic reliance.

The integration of Artificial Intelligence (AI) in higher education has led to the increasing use of AI-powered adaptive learning models that support personalized and data-driven learning. However, studies examining preservice teachers’ perceptions of these models remain limited, despite their important role in future classroom implementation. This study aims to explore preservice teachers’ perceptions of AI-powered adaptive learning in higher education, focusing on perceived usefulness, learning adaptivity, learning experience, and perceived concerns. A descriptive qualitative research design was employed involving 53 preservice teachers from various universities. Data were collected using a Likert-scale questionnaire and open-ended questions. Quantitative data were analyzed descriptively using percentage distributions, while qualitative data were examined through simple thematic analysis. The findings reveal that preservice teachers generally demonstrate positive perceptions of AIpowered adaptive learning, particularly in terms of learning effectiveness, adaptability, and engagement. Nevertheless, concerns related to over-reliance on AI, ethical issues, and data privacy were also identified. These results indicate that preservice teachers show readiness to engage with AI-supported learning, while highlighting the need for teacher education programs to promote responsible and pedagogically informed AI integration.

The development of Artificial Intelligence (AI) technology has provided new opportunities to enhance the quality of learning, particularly in elementary science education. One form of AI utilization is chatbots, which function as interactive learning media capable of encouraging students’ active participation. In science learning, questioning behavior is an important indicator of students’ cognitive engagement; however, many elementary school students tend to be passive in asking questions. This study aimed to examine the effect of using AI chatbots in science learning on students’ questioning behavior in Grade V of SDN Plalangan 03 Gunungpati, Semarang City. This study employed a quantitative approach with a quasi-experimental design. Data were collected through observation, questionnaires, and documentation. The data were analyzed to identify changes in students’ questioning behavior before and after the implementation of AI chatbots in science learning. The results indicated that the use of AI chatbots improved students’ questioning behavior in terms of frequency, confidence, and activeness in asking questions. AI chatbots provided a comfortable and flexible interaction space for students, which helped reduce psychological barriers in questioning. It can be concluded that the use of AI chatbots has a positive effect on students’ questioning behavior in elementary school science learning.

This study examines the integration of Artificial Intelligence (AI) in Christian Religious Education (PAK), using four Biblical principles love, justice, truth, and stewardship as a framework. Employing a qualitative approach with thematic triangulation through interviews with leaders, lecturers, and students, the research aims to understand how AI can be used ethically in PAK. The findings indicate that AI, when applied thoughtfully and ethically, can significantly enhance the learning process. The principle of love emphasizes the importance of honesty, empathy, and a compassionate approach in the use of AI. Justice calls for equitable access to AI tools, ensuring that all learners can benefit regardless of their backgrounds. The principle of truth encourages theological discernment in the application of AI, ensuring that it aligns with Christian teachings. Stewardship highlights the responsibility to manage AI technologies wisely, using them to serve God's purposes. AI is viewed not as a replacement for human educators but as a tool to serve and glorify God in the educational process. The study suggests that theological institutions should create ethical AI guidelines to ensure responsible use and should focus on enhancing faith-based digital literacy among students, preparing them for the digital age while remaining rooted in their faith.

Arabic grammar (nahwu) instruction has long been dominated by rule-based approaches that emphasize memorization and formal analysis, often resulting in rigid learning structures and limited responsiveness to learners’ cognitive diversity. While such approaches play an important role in preserving grammatical accuracy, they frequently overlook individual learning trajectories, cognitive readiness, and adaptive instructional needs. In the era of artificial intelligence (AI), language education is increasingly shaped by adaptive learning systems that personalize content, pacing, and instructional strategies based on learners’ profiles. This study aims to reconceptualize Arabic grammar instruction by proposing a conceptual framework that integrates traditional nahwu principles with adaptive learning systems informed by AI. Using a qualitative conceptual analysis, this paper synthesizes classical Arabic grammar pedagogy, contemporary theories of adaptive learning, and recent developments in AI-supported language instruction. The proposed framework highlights key components, including learner profiling, cognitive-level alignment, hierarchical nahwu content structuring, and AI-assisted scaffolding mechanisms. The findings suggest that adaptive learning systems offer significant pedagogical potential to transform nahwu instruction from a static, rule-centered model into a flexible, learner-centered process. This reconceptualization is expected to enhance grammatical comprehension, reduce cognitive overload, and promote learner autonomy in Arabic language education, particularly in Islamic higher education contexts. The study concludes by discussing pedagogical implications and directions for future empirical research on AI-assisted Arabic grammar learning.

The rapid advancement of digital technologies and Artificial Intelligence (AI) has fundamentally reshaped the management and development of the tourism industry. Digital transformation strategies offer substantial opportunities to enhance destination competitiveness while simultaneously supporting economic, social, and environmental sustainability. This study aims to systematically examine the role of digital transformation and AI in strengthening sustainable tourism competitiveness through a literature review approach. A total of 42 peer-reviewed journal articles published between 2019 and 2025 were analyzed, drawing from Scopus, Web of Science, and Google Scholar. The analysis employed thematic synthesis to identify dominant patterns, conceptual relationships, and emerging themes across the literature. The findings indicate that AI-driven digital transformation enhances operational efficiency, enables personalized tourist experiences, supports data-informed resource management, and facilitates the development of smart tourism destinations. Nevertheless, persistent challenges related to human resource readiness, digital inequality, data governance, and ethical considerations remain evident. This review provides an integrated conceptual perspective on digital transformation and AI in sustainable tourism competitiveness and offers insights for policymakers, practitioners, and future research.

This study aims to analyze the effect of the implementation of the Intelligent Tutoring Sistem (ITS) based on Artificial Intelligence (AI) on improving the understanding of mathematical concepts, especially in fractional and basic geometry materials, in Class V students of SD Negeri 2 Badran, Temanggung Regency. The research method used was a quasiexperimental experiment with a Non-equivalent Control Group Design. The research sample consisted of 48 students who were divided into two groups, namely the experimental group (n=24) who received learning with the help of AI-based ITS, and the control group (n=24) who received conventional learning with lecture methods and practice questions. The research instrument is in the form of a test of understanding of mathematical concepts that has been validated by experts and tested for reliability. Data were analyzed using parametric statistical tests of the Independent Sample t-test and N-Gain Score to measure the improvement. The results showed that there was a significant difference in understanding of mathematical concepts between the experimental group and the control group. The average post-test score of the experimental group (82.45) was significantly higher than that of the control group (70.12) with a p< value of 0.05. N-Gain analysis showed that the improvement in conceptual understanding in the experimental group was in the "moderate" category (g=0.56), while the control group was in the "low" category (g=0.32). These findings indicate that AI-based ITS is effective in improving students' understanding of mathematical concepts. The advantages of the system lie in its ability to provide instant feedback, personalize materials according to learning pace, and present interactive materials, thus helping to better construct students' conceptual understanding. It is recommended that schools consider the integration of ITS technology as a supplementary tool in mathematics learning at the elementary level.

The use of artificial intelligence technology in elementary education is becoming increasingly relevant as teachers demand to develop creative and efficient teaching materials. Problems faced by fifth-grade elementary school teachers include limited time, a variety of ideas, and reliance on conventional methods in developing teaching materials, resulting in suboptimal learning creativity. This study aims to describe the use of ChatGPT by fifth-grade elementary school teachers in developing creative teaching materials and to identify the benefits and constraints of its use in the learning process. The research method used is a descriptive qualitative approach with data collection techniques through literature studies and online questionnaires based on Google Forms. The research respondents were fifth-grade elementary school teachers who were familiar with and used ChatGPT in lesson planning. The data obtained were analyzed using qualitative descriptive analysis techniques through the stages of data reduction, data presentation, and drawing conclusions. The results of the study are expected to provide a comprehensive picture of the role of ChatGPT as a digital assistant for teachers in increasing the efficiency and creativity of teaching material development in elementary schools.

The emergence of ChatGPT and other large language models has introduced unprecedented opportunities and challenges in educational settings. This study examines the dual nature of ChatGPT's integration into classroom environments, analyzing both its potential as an educational tool and the ethical concerns it raises regarding academic integrity. Through a mixed-methods approach combining surveys, interviews, and content analysis, this research investigates how educators and students perceive and utilize ChatGPT, the implications for learning outcomes, and the effectiveness of current academic integrity policies. Results indicate that while ChatGPT offers significant pedagogical benefits including personalized learning support and enhanced accessibility, it simultaneously poses risks to traditional assessment methods and raises questions about authorship and original thought. The study proposes a framework for responsible AI integration in education that balances innovation with academic integrity, emphasizing the need for updated policies, enhanced digital literacy, and redesigned assessment strategies. These findings contribute to the ongoing discourse on AI in education and provide practical recommendations for educators, administrators, and policymakers navigating this transformative technology.

The integration of artificial intelligence chatbots as virtual teaching assistants (VTAs) represents a transformative shift in student support services within higher education. This study investigates the implementation, effectiveness, and impact of AI-powered chatbots in providing academic support, administrative assistance, and personalized guidance to university students. Employing a longitudinal mixed-methods approach over 18 months, this research analyzed data from 2,347 students across 15 universities that deployed VTA systems, examining interaction patterns, student satisfaction, learning outcomes, and cost-effectiveness. Quantitative analysis of 487,392 chatbot interactions revealed that VTAs successfully handled 78.4% of student queries without human intervention, with response times averaging 3.2 seconds compared to 4.7 hours for traditional support channels. Qualitative findings from focus groups and interviews highlighted students' appreciation for 24/7 availability, immediate responses, and non-judgmental interactions, while also revealing concerns about empathy limitations, complex query handling, and the desire for human connection in critical situations. The study demonstrates that VTAs significantly improve support service accessibility and efficiency while reducing operational costs by an average of 43%. However, optimal implementation requires careful integration with human support staff, continuous training of AI systems, and attention to equity issues in digital access. This research contributes to understanding how AI can augment rather than replace human educators, offering evidence-based recommendations for implementing VTA systems that enhance student success while maintaining the human elements essential to quality education.

This study aims to examine the use of artificial intelligence (AI) in transforming Buddhist Sunday School education at the Shimakalingga Temple in Jepara in the digital era. Using a qualitative descriptive approach, data were collected through observation, interviews, and documentation studies. The results show that AI technology is beginning to be utilized in the learning process, such as the use of interactive visual media, Dharma quiz applications, and digital platforms for distance learning. The use of AI has been proven to increase student interest and understanding of Buddhist teachings, as well as support more inclusive and adaptive learning. However, challenges remain, including limited resources, lack of teacher training, and the need for ethical guidelines for the use of AI in the context of religious education. This study concludes that AI plays a significant role in supporting the transformation of Buddhist education, but its use must remain balanced with spiritual values and the role of teachers as moral guides. Therefore, collaboration between the temple, educators, and technology is needed to create a sustainable learning system based on Dharma values.

Objective– This article aims to comprehensively examine the main types of food crop pests and their attack patterns through a systematic literature review approach. The research focuses on the dynamics of pest attacks, changes in ecological patterns due to climate change, and advances in modern identification technology that enable more accurate early detection. This study also highlights the significance of new paradigms of pest identification based on artificial intelligence (AI), genomics, and landscape mapping in supporting food security at the regional and national levels. Design/methodology/approach– This study used the Systematic Literature Review (SLR) method for scientific publications from 2015–2025 from reputable sources such as Scopus, Web of Science, PubMed, ScienceDirect, SpringerLink, Taylor & Francis, Wiley, AGRIS, and Google Scholar. Of the 326 articles identified in the initial stage, 30 articles in English and Indonesian were selected through a screening process based on strict inclusion–exclusion criteria. All articles were then analyzed using thematic coding techniques to produce an in-depth, evidence-based synthesis. Findings– The study produced four key findings: (1) there are five dominant pests in global food crops, namely Thrips tabaci, Spodoptera exigua/frugiperda, Helicoverpa armigera, Nilaparvata lugens and Sitophilus oryzae; (2) attack patterns are strongly influenced by temperature, humidity, pesticide resistance, and monoculture; (3) modern identification technology AI, drone imagery, multispectral sensors, and DNA Barcoding have increased detection accuracy to 94–98%; and (4) community-based early warning systems accelerate field response and reduce the risk of crop failure. Practical implications– These findings provide a scientific basis for local governments, agricultural extension workers, and farmers to gradually adopt pest identification technology and strengthen integrated monitoring systems at a regional scale. Authenticity/value– This article offers a new conceptual model of “Pest Identification Pyramid – Attack Pattern – Early Warning System” that integrates pest biology, digital technology, and community response to improve national food security.

This study examines the readiness of elementary school teachers to implement AI-based learning in the era of artificial intelligence, as technological advancements increasingly influence instructional practices in basic education. Despite the growing potential of artificial intelligence to support teaching and learning processes, empirical evidence regarding teachers’ preparedness at the elementary level remains limited. This study employed a descriptive quantitative research design involving 18 elementary school teachers. Data were collected using a structured questionnaire consisting of 15 Likert-scale items measuring technological skills, knowledge of artificial intelligence, attitudes toward AI, pedagogical readiness, and infrastructure support. Descriptive statistical analysis revealed that the overall mean score of teachers’ readiness was 4.08, indicating that teachers are generally ready to adopt AI-based learning. Technological skills emerged as the strongest aspect of readiness, reflecting teachers’ familiarity with digital tools and instructional technologies, while infrastructure and institutional support obtained the lowest mean score, highlighting challenges related to facilities, access to technology, and policy support. These findings suggest that although elementary school teachers demonstrate positive readiness and attitudes toward AI-based learning, effective and sustainable implementation requires strengthened institutional support, improved infrastructure, and continuous professional development to maximize the educational benefits of artificial intelligence in elementary education.

In the current era of digital transformation, organizations are increasingly turning to Artificial Intelligence (AI) to enhance the precision and agility of managerial decisions. This study investigates how AI adoption within management accounting systems influences decision-making efficiency and managerial performance. Using survey data collected from managers and accountants in medium-to-large firms across Central Java, the research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the hypothesized relationships. The results reveal that AI adoption significantly improves decision-making efficiency, which in turn enhances managerial performance. Furthermore, leadership support strengthens the relationship between AI adoption and decision-making efficiency, indicating that human and organizational factors remain critical for realizing technological benefits. The findings contribute to management accounting literature by elucidating the mechanism through which AI technologies create managerial value specifically, by accelerating analytical processes and improving the quality of managerial judgments. Practically, the study suggests that firms should focus on leadership involvement, data governance, and employee training to ensure that AI systems complement, rather than replace, human judgment. Overall, this study highlights that successful AI adoption in management accounting is not merely a technical transition but a strategic and cultural evolution toward evidence-based decision-making.

This community service program aims to implement a technology-based digital marketing mix strategy to promote the education program of the Barisan Mujahid Matita (BMM) Da'wah House to teenagers in the Titipapan area, Medan. The methods used include digital audience analysis to identify the characteristics of Generation Z, planning data-driven content strategies using artificial intelligence (AI) tools, and implementing integrated digital campaigns through various social media platforms such as Instagram, TikTok, and YouTube. The activities also include intensive mentoring and practical training for adolescents in creative content creation, da'wah copywriting, social media management, and digital campaign performance evaluation. The results of the program showed an increase in adolescent participation in BMM's education program by 65%, a growth in social media engagement by 200%, and the formation of an independent and sustainable adolescent digital content team. This program proves that the integration of digital technology in religious education marketing strategies is not only effective in reaching adolescents, but also encourages active engagement, creativity, and positive digital literacy in the community.