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Learners are continually faced with choosing appropriate courses or making career choices due to increased educational opportunities. The emergence of machine learning-based course and career recommender systems has the potential to address this issue, offering personalized course recommendations tailored to individual learning pathways, preferences, and learning history. The optimization and feature engineering techniques and practical deployment environments have not been collectively examined in the previous research, despite the significant advancements in this area of research. Furthermore, previous research has rarely synthesized how these technical components help students choose appropriate courses and careers. This systematic review was carried out to investigate the current state of machine learning-based course and career recommender systems, focusing on key elements, such as primary data sources, feature engineering methods, algorithms, optimization techniques, evaluation metrics, and the environments where the existing course recommendation models are deployed. The PRISMA method for conducting a systematic review was used to choose studies that met the requirements for inclusion and exclusion. The study findings show significant reliance on interpretable and traditional machine learning algorithms, such as K-Nearest Neighbor and Random Forest, to develop recommender models. Feature engineering remains basic, as most studies rely on normalization, while optimization processes are often underreported. Also, evaluation metrics varied widely, impeding comparability, while most of the recommender models are deployed in an e-learning environment, leaving the traditional learning environment underrepresented. Furthermore, the study findings identified issues including data sparsity and diversity, data security and privacy, and changes in learner preferences that may have an impact on the performance of recommender systems while recommending further studies to make use of standardized optimization methods, and automated domain-informed feature engineering frameworks, benchmark and annotated datasets in developing models the gives priority to learners’ success and educational relevance.

The development of digital technology has driven fundamental changes in management accounting practices, which no longer serve merely as internal recording tools but have transformed into strategic support systems for business decision-making. This article aims to systematically examine the role of technology-based management accounting in supporting decisions at the strategic, operational, and tactical levels. This study employs a Systematic Literature Review (SLR) method on 20 relevant scientific articles published between 2021 and 2025. The findings indicate that the integration of technologies such as ERP, cloud accounting, artificial intelligence (AI), and big data can enhance the accuracy, speed, and efficiency of managerial decision-making. Additionally, it was found that the implementation of technology significantly impacts operational efficiency and a company's competitiveness. However, the success of implementing technology-based management accounting systems heavily depends on organizational readiness, human resource competencies, as well as supportive work structures and cultures. This article also identifies gaps in the literature, particularly in the context of SMEs, which present important opportunities for future research.

Deepfake technology, a product of artificial intelligence, is widely discussed by the public because of its sophistication in replacing the face of the original subject with the face of another subject in the form of a video or photo. This has been misused to create non-consensual pornographic content that has claimed many victims. Over time, this abuse has been facilitated by the spread of the Telegram conversation application. The abused content is then disseminated by the perpetrators on social media and traded. The research method used in this research is normative juridical research which aims to analyse existing regulations, as well as regulations needed to fill the legal vacuum. Moreover, in the case of crimes using AI, there is no specific regulation, so the vacuum has an impact on the lack of security and comfort for victims of deepfake porn. However, the ITE Law describes AI as electronic agents and electronic systems. Criminal law considers that AI is not a legal subject, so the responsibility for AI crimes is imposed on the users of AI technology itself, especially in the crime of deepfake porn.

The Geopolitics 5.0 era has introduced a new paradigm in which artificial intelligence (AI), digital technology, and global power dynamics are reshaping traditional diplomatic practices. As a nation rooted in the Pancasila ideology, Indonesia faces complex challenges in upholding its principles of humanity, unity, and social justice amid increasingly competitive geopolitical shifts. This research aims to analyze the relevance of Pancasila as a strategic framework for Indonesia’s diplomatic efforts in responding to the challenges of Geopolitics 5.0, while formulating policy recommendations aligned with national values. The study employs a qualitative approach, analyzing content related to Indonesia’s foreign policy, government documents, and recent diplomatic case studies. Supporting data is drawn from academic literature, archives of the Ministry of Foreign Affairs, and reports from global think tanks. The findings demonstrate that Pancasila serves as a critical foundation for shaping Indonesia’s adaptive diplomacy, particularly through: (1) soft power strategies rooted in cultural and creative economic assets, (2) digital diplomacy that prioritizes cyber sovereignty and freedom, and (3) leadership in multilateral forums. Pancasila’s values not only remain relevant but also provide Indonesia with a strategic advantage in building principle-driven diplomacy in the Geopolitics 5.0 era. Policy recommendations include strengthening digital human resource capacity, fostering collaborative technology research, and advancing public diplomacy initiatives.

This study examines the pivotal role of artificial intelligence (AI) in talent attraction within the human resources sector, particularly in the context of modern technological advancements. We aim to understand the influence of AI on recruitment processes and identify factors affecting talent attraction in the information age, as well as the associated challenges. The study focuses on how AI impacts recruitment and utilizes statistical methods, including interviews, questionnaires, standard deviation, arithmetic mean, and Spearman's rank correlation, to achieve accurate results. Participants included 100 employees and professors from the Ministry of Higher Education and Scientific Research, with a research community of around 750. Findings suggest that organizations employing AI for recruiting, attracting, training, and guiding individuals tend to succeed. The study recommends the urgent integration of AI into organizational operations, urging a shift from traditional applicant comparison methods to modern assessment techniques while avoiding favoritism. Additionally, organizations should implement contemporary training programs to boost employee performance.

The continuous evolution of technology has significantly transformed the way humans interact with computers, moving beyond traditional keyboard and mouse inputs toward more natural and adaptive interfaces. This literature review examines the current and emerging trends in user interface (UI) development within the context of Human-Computer Interaction (HCI), with a specific focus on future-oriented innovations. Key areas of discussion include voice-user interfaces (VUIs), gesture-based interaction systems, adaptive and context-aware UIs, artificial intelligence (AI) integration, and neuroadaptive technologies. The study employs a qualitative analysis method, drawing upon scholarly publications from 2020 to 2025 and emphasizing the contributions of researchers from Universitas Islam Negeri Sumatera Utara, particularly M. Khalil Gibran. These technologies are assessed for their usability, accessibility, efficiency, and their ability to enhance user satisfaction through personalization and contextual awareness. Results from reviewed studies suggest that adaptive and AI-driven UIs are becoming essential in delivering personalized user experiences

The COVID-19 pandemic has exposed fundamental vulnerabilities in global supply chain systems, such as over-reliance on single suppliers and a lack of operational visibility. This has highlighted the urgent need for a new approach to risk management—one that leverages smart technologies. Artificial Intelligence (AI) has emerged as a promising solution, thanks to its capabilities in predictive analytics and adaptive, data-driven decision-making in real time. This study aims to develop an AI-based predictive system framework to enhance the resilience of global supply chains in the face of post-pandemic disruptions. Using the Design Science Research (DSR) methodology, the research designs and evaluates a system that integrates algorithms such as LSTM, Random Forest, Natural Language Processing (NLP), and Reinforcement Learning. It also applies a federated learning approach to ensure data privacy among supply chain partners. The study analyzes over 12,000 data entries from diverse sources, including IoT devices, weather data, demand trends, and social media. The system's effectiveness is evaluated through a combination of quantitative methods (PLS-SEM analysis on 103 respondents) and qualitative methods (interviews with 12 industry executives). The findings show that AI-driven predictive analytics significantly improve supply chain resilience (β = 0.67; p < 0.001), with demand forecasting accuracy increasing by up to 40% and delivery times reduced by 30%. Conceptually, the study contributes by designing a resilient model that integrates real-time visibility, adaptability, and cross-organizational collaborative learning. Unlike traditional approaches focused solely on automation, this framework offers a more holistic solution, addressing key gaps in the literature. The implication is clear: AI is becoming a strategic asset in building sustainable, resilient supply chains amid ongoing global uncertainty.

Research on the preservation of local culture amidst globalization emphasizes the importance of a systematic educational strategy aligned with government policy. The main focus of this study is the role of educational institutions in introducing and maintaining the sustainability of Simalungun culture, considering that the cultural knowledge of the younger generation is declining due to modernization and the influence of the media. The research objective was to develop and evaluate SIMALOKA, an artificial intelligence-based framework with a teacher-in-the-loop approach that integrates Simalungun language, arts, rituals, and crafts into both formal and non-formal curricula. The method used combines natural language processing to tag content, a knowledge graph to map cultural concepts and skills, and a multi-objective optimization algorithm to develop balanced learning modules according to the cultural calendar. The system was tested using a dataset containing 1,850 cultural learning objects and produced modules with an average cultural coverage deviation of 3.4%, a content relevance score of 0.92, and an engagement rate of 87.1%, superior to two state-of-the-art baseline models. The results show that the combination of AI-based optimization and human validation can maintain cultural authenticity while significantly increasing student participation. These findings strengthen the hypothesis that context-sensitive, technology-based curriculum design can strengthen local cultural identity without neglecting educational policy demands. The study's conclusions confirm that SIMALOKA is a large-scale model that can be adapted to other local cultures, providing important implications for policymakers, educators, and cultural organizations in maintaining the sustainability of cultural heritage. Future research directions are directed at assessing long-term retention, resource constraints, and cross-cultural adaptation to make cultural preservation more inclusive and effective.

The rapid development of smart cities, integrating technologies like artificial intelligence (AI), the Internet of Things (IoT), and big data analytics, has transformed urban environments, improving public services and governance. However, this progress presents challenges in inclusivity, accountability, and equity, requiring updates to public service law to address emerging concerns. As digital technologies reshape governance, legal frameworks must balance innovation with citizens' rights protection. This study explores the intersection of law, technology, and society in smart cities, focusing on the implications of digital transformation on public service law. It identifies challenges in governance, including the digital divide, privacy protection, and data security. The research aims to propose an inclusive legal framework that supports technological innovation while promoting accountability and social equity in smart cities. A socio-legal approach is used, combining case studies, policy analysis, and stakeholder interviews. The findings reveal that while digital transformation improves efficiency, challenges remain in citizen participation and reducing inequalities. Successful smart city models, such as those in Barcelona and Tallinn, prioritize inclusivity, accountability, and participation. The study highlights the need for flexible, adaptive legal frameworks to ensure that smart cities are governed inclusively, transparently, and equitably.

Technological literacy among high school mathematics teachers is a crucial aspect in realizing creative, interactive, and relevant learning to meet the demands of the 21st century. However, the reality on the ground shows that most mathematics teachers still have limited experience in improving technological literacy, particularly in the use of artificial intelligence (AI) as a learning support medium. This condition has implications for low innovation in the mathematics learning process. This community service activity aims to optimize the use of AI, specifically Generative-AI technology, in supporting mathematics learning in high schools. The target group is members of the High School Mathematics Subject Teachers' Conference (MGMP) throughout Grobogan Regency, Central Java Province, Indonesia. The implementation method includes workshops, interactive discussions, hands-on practice, and mentoring in the development of AI-based mathematics teaching materials, assessments, and learning media. The training materials include an introduction to the basic concepts of Generative-AI, effective prompting techniques, and practice using various AI applications to produce interactive and contextual teaching materials. Evaluation results showed that all training participants agreed or strongly agreed that this activity successfully improved their understanding of the basic concepts of Generative AI and their skills in operating AI applications for mathematics learning. Participants also reported increased confidence in integrating AI technology into their teaching practices, as well as gaining various relevant practical ideas for classroom implementation. High enthusiasm was evident in the 100% commitment of participants who expressed their readiness to implement AI technology in mathematics learning. Thus, this training not only contributed to improving teachers' technological literacy but also became a strategic step in encouraging innovative and adaptive transformation of mathematics learning in the digital era.

This study investigates how artificial intelligence (AI) is transforming Islamic journalism and digital da’wah by analyzing the ethical challenges posed by algorithmically mediated media. Employing a critical-interpretive approach, the research examines how algorithmic logic impacts the production, visibility, and ethical dimensions of Islamic content on platforms such as YouTube and TikTok. The findings reveal a growing tension between Islamic communication principles—sidq (truth), amanah (trust), and hikmah (wisdom)—and the operational values of AI systems that prioritize virality, personalization, and engagement metrics. This paper contributes to global discourse by proposing a hybrid ethical framework that bridges Islamic communication ethics with digital media accountability. It argues for an integrative model where spiritual integrity, transparency, and justice guide the development and use of AI in Islamic media contexts.  

The advancement of artificial intelligence (AI) has opened new opportunities in education, particularly at the primary level. This article presents the outcomes of an AI training program for early childhood education (PAUD) teachers in Semarang Regency, aimed at enhancing their understanding and skills in integrating technology into teaching and administration. The study employed observations, interviews, post-tests, and focus group discussions. Findings reveal significant improvement in teachers’ abilities to use tools like ChatGPT and Canva, alongside increased confidence in adopting technology. However, infrastructure limitations and lack of post-training support remain key challenges. The study highlights the need for continuous and adaptive training to ensure successful AI integration in education.

The rapid advancement and integration of Artificial Intelligence (AI) into diverse sectors of society have generated complex ethical and human rights challenges. Technologies involving surveillance, data collection, algorithmic decision-making, and facial recognition pose significant risks to privacy, equality, and freedom of expression. This study examines the intersection of AI and human rights through a comparative analysis of regulatory frameworks in the European Union (EU), the United States (US), and Asia. Employing a comparative legal approach, the research analyzes international and national regulatory instruments, including the EU AI Act, the General Data Protection Regulation (GDPR), and China’s Personal Information Protection Law (PIPL). Case studies of AI-related human rights violations, such as algorithmic bias and discrimination, are incorporated to illustrate real-world implications. Findings reveal substantial differences in governance approaches: the EU emphasizes a risk-based model prioritizing human rights protections, while the US and Asia adopt more fragmented or centralized strategies. The study underscores the urgent need for global regulatory harmonization to safeguard fundamental rights and promote ethical AI development. By highlighting both strengths and limitations of existing frameworks, the research contributes to ongoing debates on balancing innovation with accountability, transparency, and human rights protection in the digital era.

Mathematical logic is a branch of science that studies the principles of logical reasoning and how to judge the truth of a statement. This article discusses the role of mathematical logic in everyday life, especially in education, technology, and finance. Mathematical logic has been proven to help improve critical, analytical, and systematic thinking skills, making it easier for individuals to solve various problems more effectively and efficiently. In the world of education, mathematical logic supports the development of rational, argumentative, and problem-solving skills, and is an important foundation in the science and mathematics curriculum. Teachers can leverage this logic to encourage students in building consistent reasoning and logical argumentation. In the field of technology, mathematical logic is the foundation in the development of modern computing systems, such as algorithms, programming, artificial intelligence, and data structures. Without mathematical logic, digital systems such as search engines, software, and applications cannot function optimally. In finance, mathematical logic plays a role in budget strategy, investment decision-making, statistical analysis, and rational risk management. With a good understanding of logic, individuals and institutions can make more wise and measurable financial decisions. Although his contribution is large, there are still many people who do not understand the basic concepts of mathematical logic. This can be overcome through more inclusive education, contextual approaches, and interactive learning based on real problems, both in schools and non-formal environments. This study emphasizes the importance of mathematical logic as a foundation in supporting a more rational, efficient, and structured life in today's modern era. Increasing mathematical logic literacy can be a national strategy to create a society that thinks critically, is competitive, and ready to face global challenges.

Mental health issues such as depression, anxiety, and stress continue to increase globally and are recognized as critical factors that influence social functioning, productivity, and overall quality of life. Conventional mental health services are often limited by barriers including high cost, geographical distance, and persistent stigma that discourage individuals from seeking timely help. The digital era provides an alternative through the integration of technology into mental health counseling, offering greater accessibility, flexibility, and anonymity. Nevertheless, a key limitation of many digital counseling platforms lies in their inability to fully capture and respond to the emotional nuances of users during interactions. This study aims to address that gap by developing a speech-based emotion detection framework designed to be integrated into digital counseling environments. The proposed methodology includes the collection and preprocessing of speech samples, feature extraction using acoustic parameters, and training machine learning models to classify emotions in real time. Experimental results demonstrate that this approach significantly improves the accuracy of emotion detection, enabling digital counseling systems to provide more adaptive and personalized support. Beyond counseling, the research highlights the broader applicability of speech emotion recognition in education, telemedicine, and interactive digital assistants, all of which benefit from improved sensitivity to human emotions. These findings underscore the potential of artificial intelligence to strengthen digital mental health interventions, ensuring services that are not only more efficient and inclusive but also capable of fostering long-term emotional well-being in diverse populations.

This research discusses the integration of Artificial Intelligence (AI) in Arabic language learning with a focus on personalizing teaching materials according to learner needs. The background of this research is based on the challenges in teaching Arabic which include the diversity of students' backgrounds. The research was conducted with a descriptive qualitative approach through observation, interview, and documentation study of the AI platform. The results show that AI is able to analyze students' strengths and weaknesses, provide adaptive content, and increase learning motivation. This study concludes that AI can be an effective tool in supporting more personalized and relevant Arabic language learning. Recommendations include teacher training, gradual adoption of technology, and development of local AI-based platforms.

The use of artificial intelligence (AI) in education holds significant potential to enhance the quality of learning and the effectiveness of teaching. This study aims to evaluate a teacher competency development program through the integration of AI, particularly in the development of AI-based teaching materials utilizing the Kelas Ajaib feature in the Canva application. The training involved 40 teachers from SMP Negeri 1 Kota Ambon and was conducted through workshops and interactive simulations. Evaluation results indicated an 85% level of participant enthusiasm and 86% satisfaction, reflecting a highly positive response to the program. However, teacher competence in creating AI-based instructional media reached only 75%, suggesting a need for further mentoring and improved supporting infrastructure. The main challenges identified included limited hardware availability and difficulties in adapting to new technologies. Therefore, follow-up training, enhanced technical support, and improved school facilities are recommended. Collaboration among educational stakeholders is essential to ensure the sustainability of AI integration in the learning process. Further research is recommended to examine the long-term impact of AI implementation on teaching quality and student engagement.

The Era of the 4.0 Industrial Revolution has transformed various aspects of life, particularly with the advent of Artificial Intelligence (AI), which brings innovation and efficiency to sectors such as healthcare, education, and governance. However, the rapid development of AI also presents challenges related to law and ethics that must be addressed, such as legal responsibility for damages caused, secure management of personal data, and ethical boundaries regarding technological intervention. This article aims to discuss the legal and ethical issues surrounding the use of AI in Indonesia, focusing on the importance of developing an adaptive legal framework and the application of appropriate ethical principles. This research uses a normative research method with a regulatory approach and a conceptual approach. The discussion covers the definition of AI, legal and ethical challenges in its use, and recommendations for responsible technology implementation. The findings suggest that to ensure fair and sustainable use of AI, Indonesia needs to strengthen existing regulations, raise ethical awareness in society, and establish a dedicated regulatory body for AI technology.

The livestock industry plays a strategic role in providing animal-based food, yet it continues to face challenges related to efficiency and sustainability. Issues such as land limitations, animal diseases, and feed price fluctuations demand innovative production systems. One emerging solution is digital livestock farming, which integrates information and communication technologies into livestock management. This study aims to examine the role of digital livestock farming in improving production efficiency through a literature review of scientific sources published between 2017 and 2024. Literature was gathered from electronic databases and analyzed using a descriptive-qualitative approach with thematic analysis. The findings reveal that technologies such as the Internet of Things, biometric sensors, big data, and artificial intelligence enhance feed efficiency, animal health, reproduction, and labor management. Moreover, these technologies improve animal welfare and reduce environmental impact. However, challenges such as low digital literacy, limited infrastructure, and insufficient policy support hinder implementation, especially in developing countries. This review highlights the need for cross-sector collaboration to support sustainable digital livestock adoption.

In the growing era of Artificial Intelligence (AI), communication technology plays an important role in supporting the effectiveness and efficiency of business operations. This research aims to analyze how the implementation of business communication technologies, such as email, video conferencing, online collaboration platforms, and information management systems, can improve efficiency in work processes and decision making. The methods used in this research are literature study and case analysis of several companies that have successfully integrated communication technology in their business activities. The results show that the strategic use of communication technology can speed up the flow of information, reduce operational costs, and improve productivity and coordination between teams. The findings emphasize the importance of appropriate adoption of communication technology in improving business competitiveness amidst changing market dynamics.