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This research aims to find out how the creativity of Gen Z influences the process of reinterpreting Arabic in the context of modern learning, and to what extent the role of AI can support this process. This research uses the literature study method by analysing relevant articles to understand the concept of AI's role in gen z creativity and Arabic language reinterpretation in the learning process. Meanwhile, this research shows that the application of Artificial Intelligence (AI) in Arabic language learning is efficient and helpful in supporting the learning process. Among them can help search for materials, references, questions, journals/articles, and digital books, increase students' learning motivation because it is fun and exciting, support language practice and understanding, help practice speaking, writing, and get grammar explanations instantly, correct errors quickly, translate Arabic texts, help data analysis and understand the context of Arabic texts, support conversation exercises, provide feedback and reference sources and learning aids with features that enrich the Arabic language learning process.

The rapid development of artificial intelligence (AI) presents new challenges and opportunities in the practice of financial auditing, especially regarding the efficiency and accuracy of audit results, which are still the main problems. This study aims to examine the impact of financial audit transformation through the application of AI using a mixed methods approach. Quantitative data were collected from 100-150 internal and external auditors in medium to large companies in East Java Province who have been using AI for at least one year, and analysed using Structural Equation Modeling (SEM) with AMOS. Qualitative data was obtained through in-depth interviews to explore perceptions and challenges of AI implementation. The results showed that AI significantly improved the efficiency of the audit process and the accuracy of risk and fraud detection, despite barriers such as change resistance and limited auditor competence. This research makes important contributions to the development of modern audit theory and offers strategic recommendations for practitioners and regulators to optimise AI integration in financial auditing. Practical implications include the need for auditor training and strengthening technology infrastructure to support sustainable digital transformation. 

This research investigates the implementation of Random Forest algorithms combined with Synthetic Minority Over-sampling Technique (SMOTE) to predict elementary school dropout rates in Indonesia, supporting the Indonesia Emas 2045 vision. A significant gap was identified in previous studies, which, despite utilizing artificial intelligence for dropout interventions, had not integrated temporal dimensions into data analysis. A temporal data-based classification model was developed using Indonesian Ministry of Education data from 2021-2023, incorporating lag features, delta calculations, and rolling statistics. Two models were implemented: one with SMOTE achieving 99% accuracy with perfect recall for high-risk regions, while the non-SMOTE model reached 100% accuracy. Temporal features were identified as crucial predictors, reflecting external fluctuations and annual changes impacting dropout decisions. This approach enables educational institutions to allocate resources more efficiently by prioritizing operational assistance for high-risk schools. The model's capacity to identify high-risk regions with 100% recall represents a strategic investment in strengthening Indonesia's human resource sustainability. To address the limitations of provincial aggregate data, expansion to include individual-level variables and model validation at district or school scales is recommended for future research.

AI has been widely used in various nations, especially in the economy, healthcare, and law. However, its current state is limited to weak AI, lacking full awareness and control. Some countries use AI to assist legal professionals in analyzing legal documents and in helping judges with research during court proceedings. Thus, exploring AI's role and regulation in making civil case decisions within Indonesian law is crucial. This study relies on secondary data and normative legal methods. Findings suggest weak AI is promising for crafting judgments in Indonesian civil cases due to its focus on formal truth. Implementing regulations, possibly Supreme Court Regulations (PERMA), is necessary for the possible use of AI in Indonesia's court proceedings. These rules should define, classify, and limit AI, ensuring legal reliability in its application.

In the era of globalization and digital transformation, organizations face new challenges in managing cultural diversity and technological complexity. Leaders are required to quickly adapt to the ever-changing global dynamics while fostering synergy within multicultural teams. This article aims to analyze how Cultural Intelligence (CQ) and digital technology can be integrated into a multiplication leadership model to enhance the effectiveness of global organizations. Using a qualitative approach based on literature studies, this research explores the three main dimensions of CQ—cognitive, motivational, and behavioral—as well as the application of digital technologies such as Artificial Intelligence (AI), Big Data, and virtual communication in leadership development. The findings indicate that leaders with high levels of CQ are more effective in leading multicultural teams and building harmonious cross-cultural connections. Meanwhile, the use of digital technology accelerates decision-making processes, mentoring, and collaboration within flexible and dynamic organizational structures. The integration of cultural intelligence and digital technology results in an adaptive, collaborative, and innovative leadership model. Examples of the implementation of this model in global companies such as Microsoft, Tesla, and Airbnb further reinforce the findings. This article provides practical contributions for organizations in designing training strategies and leadership models based on CQ and digital leadership to face global challenges more effectively and sustainably.  

The advancement of artificial intelligence (AI) has led to the emergence of new crimes, including the misuse of deepfake technology to produce and distribute pornographic content without the victim's consent. This form of digital sexual harassment has serious impacts on victims' dignity, mental health, and social life. This study aims to examine the efforts of Police in addressing sexual harassment crimes using deepfake porn and to identify the obstacles faced. Using normative and empirical legal approaches, data were collected through literature review and interviews. The findings reveal that the police efforts involve both penal (law enforcement) and non-penal (preventive) approaches, including public education, cross-institutional collaboration, and cyber patrols. However, the handling of such crimes is still hindered by regulatory gaps, limited technology, and low public awareness. Strengthening legal frameworks and police capacity is essential to effectively combat digital-based sexual crimes.

The development of digital technology, particularly deepfake, has brought negative impacts, including the protection against non-consensual pornography content. Deepfake, which uses artificial intelligence to manipulate images, videos, or audio, allows the creation of pornography without the consent of the individual whose face or identity is manipulated. This phenomenon results in violations of privacy, honor, and the psychological well-being of the victims, while also spreading false information that can damage public perception. Although Indonesia has regulations such as Law No. 11 of 2008 on Electronic Information and Transactions (ITE Law) and Law No. 44 of 2008 on Pornography, there are no specific provisions regulating the use of deepfake technology. This article identifies deficiencies in existing regulations and provides recommendations for adaptive legal measures, including legislative updates, strengthening digital platform responsibilities, enhancing law enforcement capacity, and international cooperation to address this threat. It is hoped that with these measures, protection for individuals in the digital era can be strengthened.

This research presents a personalized, context-aware recommender system to suggest Places of Interest (POIs) using a hybrid approach combining Bayesian inference and collaborative filtering. The system explicitly addresses the cold-start problem that new users face and improves recommendation accuracy by considering contextual variables such as user mood, budget, companion, and location. The system collects real-time contextual inputs for new users with no historical data and applies Bayesian inference to generate relevant POI suggestions. As users begin to interact and provide ratings, the system progressively shifts to a collaborative filtering mechanism, leveraging cosine similarity to identify similar users within comparable contexts. The recommender system focuses on three categories of POIs: restaurants, hotels, and landmarks. These locations are retrieved through the Google Maps API, and only mapped locations are considered. The system was implemented on Android devices and evaluated through a user study involving 25 participants from diverse backgrounds, including software developers, IT students, and general users. Evaluation metrics such as normalized Discounted Cumulative Gain (nDCG) and classification accuracy were used to assess recommendation quality. Results demonstrate that the system performs better than traditional methods, with nDCG improvements reaching up to 83 percent. Users reported high satisfaction regarding the recommendations' accuracy, ease of use, and contextual relevance. While the system offers significant improvements, it also has certain limitations. Its dependency on Google Maps data may restrict its scope, and using only four contextual factors limits the system’s adaptability to more complex user preferences. Future enhancements could include additional dynamic contexts such as weather, POI popularity, and time-related trends, as well as integrating more advanced models to increase personalization and flexibility in real-world applications.

This article discusses policies to improve AI literacy among college students. The development of technology in the digital era is increasingly rapid, and artificial intelligence (AI) has become an important part of various aspects of life, including education. College students as the next generation need to have good AI literacy in order to adapt to the changing times and face the challenges of the increasingly technology-based world of work. AI literacy is not only about understanding how this technology works, but also how to use it effectively and ethically in academic and professional life. The research method used in this study is a descriptive qualitative method, with data collection techniques, namely interviews and documentation studies that aim to examine the development of technology in the increasingly rapid digital era, and artificial intelligence (AI) has become an important part of various aspects of life, including education. The results of the study are then narrated in descriptive form. It can be concluded that AI literacy has an important role in improving the effectiveness of student learning and preparing them for competition in an increasingly technology-based world of work.

The development of digital technology has brought a significant transformation in the field of education, particularly in learning processes. Traditional teaching methods are now shifting toward more flexible, interactive, and accessible digital systems. This article discusses various strategies for integrating technology into learning in the digital era, including the use of Learning Management Systems (LMS), the application of Artificial Intelligence (AI), and the development of multimedia-based interactive learning content. Furthermore, strengthening digital literacy among teachers and students is a key focus in ensuring the successful implementation of technology in education. This study employs a literature review method by summarizing various scholarly sources and previous research findings. The results indicate that the appropriate application of technology in education can enhance learning effectiveness, promote student independence, and foster 21st-century skills. However, challenges such as unequal access to technology and the lack of teacher training remain obstacles that need to be addressed. Therefore, collaboration between educational institutions, the government, and the community is essential to create an inclusive and sustainable digital learning ecosystem. This article is expected to contribute to the development of adaptive learning strategies aligned with technological advancements and the needs of the times.    

This community service activity is motivated by the rapid development of deep learning and artificial intelligence (AI) which has penetrated various aspects of life. Prasetiya Mandiri Polytechnic held a workshop "Deep Learning for Smart Solutions: Workshop on the Use of AI Applications for Daily Life" to increase AI literacy among students and lecturers. The method of implementing this activity includes the preparation of workshop materials, the implementation of presentation sessions, discussions, and practical exercises, as well as evaluation through questionnaires and observations. The results of the activity showed high enthusiasm of participants and increased understanding of the basic concepts of deep learning and AI applications. The interpretation of the questionnaire data showed a high level of participant satisfaction, with an average score of 4.5 on a scale of 5. The results of the participants' practical exercises also demonstrated their ability to apply AI concepts to create simple applications. This activity succeeded in achieving its goal of improving participants' digital skills and encouraging the application of AI in learning and research at Prasetiya Mandiri Polytechnic. In conclusion, this workshop is effective in improving AI literacy and providing practical experience to participants, and has the potential to be further developed by adding more intensive and diverse practice sessions

Artificial intelligence (AI) has become a critical tool for transforming organizations in the ever-evolving digital age. In this article, we will discover the various ways in which AI can improve the efficiency and productivity of leaders in various industries. Leaders can focus on strategy and innovation by optimizing work processes and making faster and more accurate decisions with the help of in-depth data analysis. This article shows how AI can help organizational performance and how leaders can use it to achieve long-term goals. The results are expected to provide guidance to leaders and decision-makers on how to use AI to drive change in their companies.  

Amid rapid technological advancements, improving the quality of primary education remains a critical challenge. The purpose of this study is to determine the influence of Artificial Intelligence (AI), learning evaluation, and teacher competence on the quality of Social Studies instruction. The research used a quantitative design involving 25 sixth-grade students at SD Inpres Barua, Bontolempangan, during the 2024/2025 academic year through total sampling. Data were gathered via questionnaires and analyzed using multiple linear regression, t-tests, and F-tests in SPSS 26. Results revealed that AI, evaluation, and teacher competence significantly and positively affect learning quality both individually and collectively. These findings reinforce the critical role of digital tools and professional teaching standards in fostering more effective and meaningful learning experiences.

Artificial Intelligence (AI) in learning can serve as a tool for students to acquire knowledge. However, the understanding and use of AI in education still face various challenges. Some universities have started integrating AI learning into their curricula, but its implementation remains limited and uneven across different institutions. Additionally, the level of AI literacy among students in Indonesia is still relatively low. Adequate AI literacy is crucial for students to optimize the use of this technology without excessive dependence and to understand its ethical implications.This research aims to assess students' understanding of AI literacy and explore how AI literacy education can be integrated with the European model. A mixed-method approach is used in this study, combining quantitative research through questionnaires and qualitative research through interviews. The results indicate that students in Indonesia have a fairly good understanding of AI literacy. However, several challenges remain, including students' dependence on AI and ethical issues related to its use.Therefore, collaboration among various stakeholders, including universities, the government, and industry, is essential to enhance students' AI literacy skills. Efforts can include training programs, providing access to AI resources, and adopting AI-based learning models that have been implemented in Europe. Through these measures, it is expected that students' AI literacy will improve, supporting the advancement of technology-based education in Indonesia.

Healthcare Information Systems (HIS) play a critical role in modern medical services by improving patient data management, clinical decision-making, and overall healthcare efficiency. However, existing HIS models face challenges related to interoperability, security, and processing efficiency. This study conducts a systematic literature review to evaluate cloud-based, blockchain-enhanced, and AI-driven HIS solutions. The proposed hybrid HIS model integrates AI-driven decision-making with blockchain-based security to enhance accuracy, interoperability, and data protection. The evaluation metrics include accuracy, latency, and security score, comparing the proposed system with state-of-the-art HIS implementations. Experimental results indicate that the hybrid HIS model achieves 93.4% accuracy, a security score of 0.90, and reduced latency (220 ms), outperforming traditional cloud-based and standalone blockchain solutions. These findings demonstrate that a hybrid approach balances efficiency and security, making HIS more practical for real-world applications. Future research should focus on real-world deployment, computational cost reduction, and regulatory compliance.

This study analyzes the factors contributing to the low interest in reading among elementary school students in the implementation of the Merdeka Curriculum, with a particular focus on the dependence on artificial intelligence applications such as ChatGPT. Technological advancements have made information access easier, but they have also raised concerns about the decline in the interest in deep book reading. Students who frequently use ChatGPT tend to only read summaries without delving deeper into the material, which weakens their critical thinking skills. In the Merdeka Curriculum, strong literacy is crucial, and therefore, the role of teachers and parents is essential to guide students in making books their primary learning resource. This research not only examines this phenomenon but also offers solutions for teachers and parents to enhance students' reading interest.

This study analyzes the factors contributing to the low interest in reading among elementary school students in the implementation of the Merdeka Curriculum, with a particular focus on the dependence on artificial intelligence applications such as ChatGPT. Technological advancements have made information access easier, but they have also raised concerns about the decline in the interest in deep book reading. Students who frequently use ChatGPT tend to only read summaries without delving deeper into the material, which weakens their critical thinking skills. In the Merdeka Curriculum, strong literacy is crucial, and therefore, the role of teachers and parents is essential to guide students in making books their primary learning resource. This research not only examines this phenomenon but also offers solutions for teachers and parents to enhance students' reading interest.

This study aims to analyze the effectiveness of ChatGPT as a tool to help students complete academic assignments. Using a quantitative descriptive method, this study involved 150 6th semester students of the Mathematics Education Study Program selected through a simple random sampling technique. Data were collected through an online questionnaire that measured the intensity of ChatGPT use, ease of understanding the material, and its impact on learning outcomes. The results showed that the majority of students felt helped by the use of ChatGPT, especially in compiling essay assignments, understanding complex academic concepts, and increasing self-confidence in solving math problems. However, it was found that excessive use has the potential to reduce learning motivation if students rely too much on instant answers. Therefore, wise use of ChatGPT and integration with conventional learning methods is highly recommended so that students continue to develop critical thinking skills and independence in learning.

Artificial Intelligence (AI) is increasingly used in financial accounting to improve decision-making effectiveness. This research analyzes the role of AI in supporting data-driven decision making and identifies challenges in its implementation. Using a qualitative approach with the Systematic Literature Review (SLR) method, this study reviewed 41 relevant articles from national and international journals. The results showed that 28 studies supported the effectiveness of AI in improving financial decision-making by automating transaction recording, enabling algorithm-based predictive analysis, and detecting financial anomalies. AI enables companies to respond faster to market changes, increase transparency of financial reports, and reduce human errors in accounting processes.However, 13 studies highlighted challenges such as technological complexity, limited transparency in decision-making, algorithmic bias, and organizational readiness. In addition, evolving regulations are an obstacle to ensuring optimal use of AI while minimizing ethical and legal risks. The success of AI in financial decision-making depends on infrastructure readiness, regulatory support, and human resource competencies. Without a well-planned strategy, AI may pose new challenges that hinder its effectiveness. Therefore, this study provides insights into the optimal AI implementation strategy to ensure that this technology improves the accuracy and transparency of decision making while maintaining financial accounting accountability.

Google Translate is an artificial intelligence-based translation service developed by Google. Since its introduction in 2006, this service has continued to create with the application of Neural Machine Translation (NMT) technology, which improves the accuracy and fluency of translation compared to previous methods. This study aims to determine the effectiveness and limitations of Google Translate in translating Batak into Indonesian. The research method used is descriptive qualitative with a comparative approach of Google Translate translation results and manual translations by professional translators. The study results show that Google Translate can translate basic words and simple sentences quite well. However, there are several limitations, such as a lack of understanding of the cultural context, idioms, and dialect variations in the Batak language. In addition, the translation is also influenced by the limitations of the database and vocabulary enrichment in this service. Thus, although Google Translate can be a tool in translation, users still need to do manual verification to ensure accuracy, especially in fields that require high precision such as law, academics, and professional communication.