Publication Search

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 use of information technology through website development has become a crucial need for MSMEs, including traditional food businesses like Siomay Batagor Bogarasa. This study aims to develop a business profile website using the Odoo-based ERP website module to strengthen brand identity and facilitate information delivery to customers. The development process follows the Software Development Life Cycle (SDLC) stages, including planning, requirement analysis, design, implementation, and testing. The developed website consists of several pages such as Home, About Us, Menu, and Contact Us, presenting information about the business history, product catalog and pricing, sales locations, and contact channels. Testing results indicate that most features function well, with responsive display, smooth navigation, active contact form, and effective social media integration. One issue was found in the Google Maps display, which has not yet accurately shown the business location. Overall, the website provides practical benefits in terms of promotion, communication, and enhancing the professionalism of the business.

Injustice against women in contemporary Islamic law practice is still a serious problem, especially in cases of divorce, child custody, and the division of common property, which are often decided textually without considering the social, economic, and psychological aspects of women. This phenomenon shows that the application of Islamic law is still normative and does not fully reflect substantive justice as the purpose of maqāṣid al-syarī'ah. This research aims to analyze the nature of justice for women in the modern era, identify the steps needed to realize this justice, and formulate Islamic legal solutions based on maqāṣid al-syarī'ah that can be applied contextually in the religious justice system. The research method used is qualitative with a normative-empirical approach through literature analysis, case studies, and empirical data from religious court decisions and reports of official institutions such as Komnas Perempuan. The results of the study show that justice for women can only be achieved through a dynamic maqāṣid approach, by placing the interests of women and children above the legal-formalities of classical fiqh. The efforts needed include the integration of empirical data in judges' decisions, reform of religious justice policies, increasing the capacity of judges in understanding maqāṣid, and empowering women through legal literacy.

This article examines various guidance and counseling (BK) management models relevant to the context of modern education in Indonesia. The models discussed include POAC (Planning, Organizing, Actuating, Controlling) management, comprehensive BK services, school-based BK management, specialized service management, and the use of digitalization in BK services. This review was compiled using a literature review method, drawing on various credible national sources, such as scientific journals, reference books, and education policy documents. The purpose of this research is to provide an in-depth understanding of the characteristics, principles, and implementation of each BK management model in educational practice. The results indicate that each model has its own advantages and limitations, both in terms of service planning, resource management, and the effectiveness of service delivery to students. Therefore, the selection and implementation of a BK management model must be tailored to the needs of the school, the availability of professional staff, infrastructure, and student characteristics. The integration of a systematic, data-driven, and adaptive management approach to developments in information technology is a key factor in improving the quality and effectiveness of BK services. This article is expected to provide theoretical and practical contributions to school counselors, educators, and education policymakers.  

This community service activity aims to strengthen the role of higher education institutions in preserving local culture through the revitalization of cultural arts learning based on local wisdom, particularly traditional Nias carving art. The main problems faced by the partners include the limited availability of contextual cultural arts learning, minimal integration of traditional art practices into university courses, and students’ low understanding of the philosophical values embedded in Nias carving motifs. The implementation method employs a participatory–educational approach consisting of preparation, socialization, theoretical and practical training, intensive mentoring, and evaluation stages. This activity involves students and lecturers as participants as well as agents of cultural preservation. The results indicate a significant improvement in participants’ knowledge of the symbolic meanings of Nias carving motifs, their basic skills in designing and drawing carving motifs, and their appreciative attitudes toward the preservation of local cultural arts. This activity contributes to the strengthening of cultural arts learning in higher education and has the potential to serve as a sustainable model of community service based on local culture.

This study aims to describe the integration of environmental education into early childhood learning activities at TK Prawidya Dharma Demulih through the use of recycled waste as a creative and educational learning medium. The study was motivated by the low environmental awareness among children and the limited use of environmentally themed learning media in the institution. A qualitative descriptive approach was applied using the ADDIE development model, consisting of the stages of analysis, design, development, implementation, and evaluation. The findings reveal that employing a recycled-material spinner game enhanced children’s understanding of environmental cleanliness and encouraged environmentally responsible behavior through playful learning activities. The children showed strong enthusiasm, participated actively, and began to develop habits related to cleanliness after the learning sessions. Moreover, teachers gained new insights into designing innovative and functional learning media using discarded materials. Overall, the use of recycled waste as an educational tool proved effective in fostering environmental awareness while supporting creativity and meaningful learning experiences for early childhood learners..

That Christian Religious Education teachers update their professionalism and competencies to ensure that Christian education remains relevant, effective, and transformative. This study aims to analyze the modernization of the professionalism of Christian Religious Education teachers, including the integration of spirituality with modern pedagogical approaches and strategies for developing teacher competencies in addressing the challenges of the digital generation. The study employs a descriptive qualitative approach, collecting data through literature review from books, journals, notes, and relevant reports, and presenting the findings in a narrative form. The results show that the modernization of teacher competencies involves the development of pedagogical, personal, social, spiritual, and professional competencies, with the ability to integrate spirituality, technology, and modern teaching methods such as collaborative and digital learning to create contextual, engaging, and transformative learning experiences. In conclusion, the modernization of professionalism among Christian Religious Education teachers is an urgent necessity to enable teachers to deliver God’s Word in a relevant manner, shape students’ character and spirituality, and enhance the effectiveness of Christian education through mastery of holistic and collaborative competencies.  

The use of protective equipment in the form of helmets is an important aspect of ensuring motorcycle rider safety. However, violations of helmet usage still frequently occur and are difficult to monitor continuously. This study proposes a real-time helmet detection system using the YOLOv8 object detection method. The YOLOv8n model was trained using a helmet and no-helmet image dataset that underwent data augmentation to improve the model’s robustness against variations in environmental conditions. The system was implemented using the Python programming language with the support of the Ultralytics and OpenCV libraries. The system input was obtained from a webcam with a resolution of 640×640 pixels, where each video frame was processed in real time to detect the Helmet and No Helmet classes. The system displays bounding boxes and class labels in real time and is equipped with a violation duration calculation mechanism. When a no-helmet condition is detected continuously, the system generates pop-up alerts and automatic notifications via the Telegram application. The experimental results show that the system is capable of detecting helmet usage and no-helmet violations in real time with stable performance. The integration of violation duration calculation helps reduce momentary detection errors and improves the reliability of identifying valid violations

Managing Regional Public Service Agency (Badan Layanan Umum Daerah/BLUD) hospitals requires planning and budgeting processes that are accountable, measurable, and aligned with service performance. In practice, BLUD planning is still constrained by fragmented applications (hospital information system/SIMRS, finance, human resources, e-office, and procurement), duplicate data entry, approval delays, and limited monitoring of process compliance. This study aims to analyze requirements and design a web-based BLUD planning information system using an Enterprise Application Integration (EAI) approach through middleware to improve cross-system interoperability, data consistency, and the timeliness of executive reporting. The study adopts the Design Science Research (DSR) framework, comprising problem identification, definition of solution objectives, artifact design and development, demonstration, evaluation, and communication/report writing. The proposed system includes a unit-based budget proposal module and item management, a role-based approval workflow (RBAC) with SLA tracking, a budget ceiling (pagu) master to benchmark proposals, audit trails and report exports, and an executive dashboard integrating budget perspectives, service indicators (e.g., bed occupancy rate/BOR and patient visits), and process compliance. It also provides an integration design via middleware (ESB/message broker) supported by a canonical data model (CDM) and traceable logging (trace_id/correlation_id). Evaluation using black-box testing and API contract testing indicates that the main planning workflow operates as intended and the integration interfaces are consistently defined, providing a foundation for staged implementation and further performance evaluation.

SMP Negeri 5 Merlung is a public junior high school in Merlung Subdistrict that has utilized the DAPODIK system for online data processing management, enabling efficient sending and receiving of information to the government. This research analyzes IT governance on the DAPODIK system using the COBIT 5 framework, specifically the MEA01 domain (Monitor, Evaluate and Assess Performance and Conformance), which focuses on monitoring and evaluating performance and conformance. The research background is based on the need to maximize the utilization of the system at the school level. The main objectives are to determine the current and expected capability levels, as well as to provide improvement recommendations to achieve higher process maturity. The research method applies Assessment Process Activities, covering observation, interviews, identification of findings, gap analysis, and recommendations. The results show that the current capability level is at level 3 (established process), while the expected capability level is directed toward level 4 (predictable process). The implications of these findings provide practical recommendations such as routine monitoring enhancements, staff training, and integration of automation tools to bridge the capability gap, thereby improving the effectiveness of IT governance at SMP Negeri 5 Merlung sustainably.

The rapid development of artificial intelligence, particularly ChatGPT, has created new opportunities to support students’ academic activities in higher education. However, its utilization needs to be evaluated in terms of the alignment between academic task characteristics and technological capabilities to ensure optimal outcomes. This study aims to examine the feasibility of using ChatGPT in students’ academic activities by applying the Task–Technology Fit (TTF) model. This research employed a quantitative approach using Structural Equation Modeling based on Partial Least Squares (SEM-PLS). Data were collected through questionnaires distributed to university students and analyzed using SmartPLS 4 software. The variables examined included Task Characteristics, Technology Characteristics, Task–Technology Fit, Performance Impact, and Utilization. The results indicate that Task Characteristics and Technology Characteristics have a positive and significant effect on Task–Technology Fit. Furthermore, Task–Technology Fit significantly influences Performance Impact and Utilization. Performance Impact also shows a positive and significant effect on the utilization of ChatGPT by students. These findings suggest that the alignment between academic task requirements and the capabilities of ChatGPT plays a crucial role in improving students’ performance and encouraging sustained technology use. The implications of this study highlight the importance of selective and purposeful use of ChatGPT in higher education and provide a reference for higher education institutions in formulating policies related to the ethical and effective integration of artificial intelligence technologies as learning support tools.

The rapid development of the Internet of Vehicles (IoV) has introduced new security challenges, particularly in protecting Controller Area Network (CAN Bus) communications from cyberattacks such as Denial of Service (DoS) and spoofing attacks. This study proposes the implementation of the Extreme Gradient Boosting (XGBoost) algorithm combined with Information Gain feature selection to improve intrusion detection performance in IoV environments. The CICIoV2024 dataset, which represents both benign and malicious traffic, is used as the primary data source. The research process includes data integration, preprocessing, feature selection, data splitting, and model training using a 5-fold cross-validation approach. Experimental results demonstrate that the proposed model achieves outstanding performance, with accuracy, precision, recall, and F1-score exceeding 99.99%, and an Area Under Curve (AUC) value approaching 1.00. Furthermore, Information Gain successfully identifies the most influential CAN payload features, enhancing model efficiency without sacrificing accuracy. These findings confirm that the combination of Information Gain and XGBoost is highly effective for developing a fast, accurate, and efficient intrusion detection system in IoV networks.

Public complaint services are an essential part of public service delivery in supporting the government’s rapid response to various social issues and emergency situations. In West Tanjung Jabung Regency, public complaint services are provided through the HALO USTAD 112 Call Center managed by the Department of Communication and Informatics. However, the existing service still faces several limitations, including the lack of optimal integration in complaint data management, inadequate documentation of reports based on regional classifications, and limited capabilities in storing and retrieving complaint data. This study aims to optimize the HALO USTAD 112 Call Center service through the design of a mobile-based public complaint information system, so that the processes of receiving, managing, and monitoring reports can be carried out more effectively and in a structured manner. The system development applies the Waterfall method, which consists of requirement analysis, system design, implementation, and testing stages. The designed information system includes key features such as user and admin login, complaint submission, report management and verification, report monitoring, statistical visualization of complaint data, and regional-based report recapitulation. The application is developed using the Flutter framework with the Dart programming language, while Supabase is utilized as the backend integrated with a PostgreSQL database. The results of this study are in the form of a system design and prototype that are expected to improve the quality of public complaint services and support more accurate, integrated, and efficient data management.

This study aims to explore the contribution of Christian Religious Education in developing the character of people with disabilities, grounded in Jean Vanier’s perspective on inclusive community and human dignity. People with disabilities are often marginalized due to persistent social stigma, which limits their access to education, meaningful participation, and employment opportunities, particularly within faith-based educational contexts. Employing a qualitative research approach through an in-depth literature review, this study examines key concepts in Christian Religious Education, the characteristics and lived experiences of individuals with disabilities, and the challenges and strategies associated with inclusive educational practices. The findings indicate that Christian Religious Education can function as an effective empowerment framework by integrating spiritual formation with the development of social skills, self-confidence, and communal belonging. Based on Jean Vanier’s inclusive vision, the study highlights practical implications for local churches, Christian schools, and faith-based communities, such as fostering inclusive learning environments, implementing participatory pedagogical models, and strengthening community-based support systems for people with disabilities.Furthermore, reducing social stigma through value-based education and community engagement emerges as a critical strategy to enhance educational participation and social integration. These findings contribute to the discourse on inclusive Christian education and offer contextual strategies applicable to local academic and ecclesial settings in promoting the dignity and empowerment of people with disabilities.

Green innovation has become a crucial approach to addressing sustainability challenges within global economic and environmental contexts. This study maps the development of green innovation research through a bibliometric analysis using data from the Scopus database covering the period 2021–2024. Bibliometric techniques were applied with VOSviewer and R Studio to examine publication trends, citation patterns, author collaboration, and keyword networks. The results show a significant growth of publications in the last five years, with major themes focusing on sustainable development, environmental technology, and economic implications of green innovation, while leading contributions come from China. Influential journals in innovation and environmental management are identified as key publication outlets, and keyword analysis reveals the integration of green innovation into sustainability strategies and economic policy discussions. This study contributes to a clearer understanding of the intellectual structure and emerging directions of green innovation research, offering insights for scholars, business practitioners, and policymakers in advancing sustainable innovation practices.

Global concern on climate change has encouraged policymakers and central banks to adopt green financial instruments such as green bonds within sustainable monetary frameworks. Research on the integration of green bonds and monetary policy has grown rapidly in recent years, reflecting wider trends in sustainable finance, climate risk management, and central bank policy innovation. Green bonds play an important role in supporting low-carbon transitions and can influence monetary operations through asset purchases and collateral policies. This study applies a bibliometric analysis of publications on green bonds and monetary policy indexed in Scopus from 2021 to 2025. Using bibliometric methods with VOSviewer and R Studio, the analysis maps dominant themes, co-authorship networks, and the evolution of green monetary studies. The results show strong growth in research output, high levels of international collaboration, and a concentration on sustainable development and green finance. However, fewer studies address climate policy uncertainty and geopolitical risk, even though these factors are highly relevant to financial stability and the effectiveness of monetary policy. Future research in these underexplored areas could provide stronger scientific foundations for building more adaptive and resilient monetary systems in both developed and emerging economies.

Digital entrepreneurship has become a transformative phenomenon in the modern economy, changing the way businesses are developed and run through digital technology. Although the literature on digital entrepreneurship is growing rapidly, comprehensive mapping of the evolution of knowledge and research patterns is still limited. This study analysis the development of digital entrepreneurship in academic literature through bibliometric analysis of the Scopus database to identify research trends, knowledge structures, and future directions. The analysis was conducted on 1,815 publications from 681 sources (1988-2025) written by 8,023 researchers, using R Studio (bibliometrix) and VOSviewer. The results show exponential growth with an annual growth rate of 17.22%, as well as five main theme clusters: digital business models, digital innovation, social entrepreneurship, e-commerce, and fintech. Thematic evolution shifted from traditional entrepreneurship (1988–2010) to digital transformation (2011-2018) to new technology integration (2019-2025). The level of international collaboration reached 26.39%, with the United States, China, and the United Kingdom as the main contributors. These findings provide a research roadmap for identifying research gaps, collaboration opportunities, and trending topics in digital entrepreneurship.

The digital era has transformed the financial sector through the integration of FinTech, making it more susceptible to increasingly complex cyber threats. As these risks rise, there has been a significant increase in academic research to better understand the cybersecurity challenges within the financial sector. This study aims to explore the development of cybersecurity research globally within this field. By utilizing bibliometrics, the research analyzes literature data collected from the Scopus database over the last five years. The analysis was conducted using VOSviewer and RStudio to identify dominant clusters, with cybersecurity and network security as the central themes linking various sub-fields, including artificial intelligence, cyberattacks, and phishing. The findings reveal areas of extensive research and highlight gaps that require further exploration. This study provides valuable insights for researchers and professionals in the cybersecurity field, offering a roadmap for future investigations and the identification of underexplored areas that need attention. Ultimately, this research contributes to advancing knowledge in the financial sector’s cybersecurity landscape and assists in shaping future research directions.

Artificial Intelligence (AI) has become a significant driver of innovation in the banking sector, especially in the context of post-pandemic digital transformation. AI is widely utilized in areas such as fraud detection, credit evaluation, risk management, and customer interaction, attracting considerable interest from both academics and industry professionals. This research explores the recent advancements in AI within the banking industry, focusing on studies published between 2020 and 2025. A bibliometric approach is employed, using data from the Scopus database and bibliometric tools like VOSviewer and R Studio to visualize keyword networks and track emerging trends. The study aims to identify influential authors, journals, and countries contributing to AI research in banking. By analyzing these developments, the research highlights the contributions of AI to improving operational efficiency, data security, and financial inclusion, particularly in the Indonesian context. This work offers valuable insights into the ongoing integration of AI in the banking sector and its potential to shape future financial services, emphasizing its relevance to both global and regional markets.

The integration of big data in the financial sector has increasingly attracted scholarly attention, particularly in areas such as risk management, fraud detection, algorithmic trading, and investment optimization. Given the rapid development of this field, it is essential to map research trends and identify emerging directions that shape the future of financial innovation. This study applies a bibliometric approach using 3,829 articles retrieved from the Scopus database from 1981 to 2025, with data processed through R Studio and the Bibliometrix-Biblioshiny application. The objective is to explore the intellectual landscape of big data finance and reveal research frontiers as well as thematic evolution. The results show a sharp increase in publications after 2015, alongside the growth of fintech and artificial intelligence applications, with dominant themes including blockchain integration, risk analytics, and predictive modelling. Cross-disciplinary and cross-regional collaborations continue to expand. These findings provide a comprehensive overview of how big data has shaped financial studies and offer insights for potential future research directions.