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Background: Digital transformation in arts education has introduced new paradigms in pedagogical tools, yet the specific role of artificial intelligence in fostering creativity within dance education remains under-explored. Objective: This study aims to analyze the contribution of AI Motion technology to enhancing the creative thinking skills of junior high school students in dance learning. Method: A systematic literature review was conducted following the PRISMA 2020 guidelines. A total of 30 peer-reviewed articles published between 2023 and 2025 were selected from databases including Scopus, ScienceDirect, ERIC, Google Scholar, and Garuda. Data were analyzed using the qualitative descriptive framework of Miles and Huberman. Results: The findings demonstrate that AI Motion technology significantly improves movement accuracy by up to 41% and fosters four key dimensions of creativity: fluency, flexibility, originality, and elaboration. The technology provides real-time feedback and visualization, enabling students to transition from passive imitation to autonomous movement exploration. Conclusion: The integration of AI Motion is strategically aligned with the Indonesian Merdeka Curriculum, which emphasizes differentiated learning and 21st-century skills. However, successful implementation is contingent upon overcoming challenges related to teacher digital competency and infrastructure accessibility. This study provides a conceptual framework for modernizing arts pedagogy through AI-assisted creative exploration.

Financial reporting integrity is heavily reliant on audit quality. This research explores the effect of auditor attributes, specifically integrity and professional background, on audit standards in Timor-Leste. Quantitative data was collected from a survey of 60 auditors and analyzed using descriptive statistics, correlation analysis, and multiple linear regression techniques. The findings suggest that auditor ethics has a substantial positive impact on audit quality, indicating that conformity to professional ethical guidelines is vital for enhancing audit results. In contrast, experience in auditing does not demonstrate a statistically significant impact on the quality of audits. Visualization through scatter plots further supports the notion that the relationship between ethics and audit quality is more robust than that of other auditor characteristics. Strengthening ethical standards in the auditing profession is crucial to enhancing audit quality, as these findings demonstrate. This study contributes to the body of research on auditing behavior by presenting empirical findings from a developing institutional setting. The findings also have practical implications for policymakers and auditing bodies in Timor-Leste.

The phenomenon of radical transparency in the Bottled Drinking Water (AMDK) industry in 2025 triggered a reputation crisis and a massive erosion of customer loyalty. This crisis began with negative sentiment on social media that led to surprise inspections by regulatory authorities of the industry leader's "Mountain Spring" claim. The unpreparedness of the communication infrastructure in presenting technical data in real time led to a decline in brand image and a significant correction in market share to a critical figure of 47.4%. This article aims to formulate a conceptual framework for adaptive and data-driven PR presentation techniques through the integration of real-time data visualization and narrative reframing strategies. The method used is a descriptive conceptual analysis by evaluating the chronology of incidents and PR responses during the crisis. The analysis results show that unidirectional communication patterns and static presentation materials are deemed to fail to face viral and spontaneous public audits in the digital space. As a theoretical and practical contribution, this article proposes a new model, The Spontaneous Technical Presentation Model, and recommendations for the development of a Crisis Presentation Kit for the FMCG industry. Through a theoretical approach that expands the theory of Image Restoration, this study confirms that corporate image restoration in the digital era is highly dependent on the precision and transparency of visual data presented during field qualification

This study aims to describe the concept of Immersive Commerce based on Augmented Reality (AR) in increasing consumer confidence in E-Commerce transactions and to design a conceptual prototype design framework for an AR E-Commerce system with a clear technical flow. The research method uses a literature study through a comprehensive review of AR-based E-Commerce implementations and needs analysis from the perspective of consumer problems and business opportunities. The main problem identified is consumer hesitation in purchasing products online due to limited visualization that relies solely on product photos, causing fears about differences in shape, size, and quality of goods. The research results produced a conceptual framework that includes an integrated system architecture with a frontend layer (AR visualization engine), backend layer (product database and 3D asset management), and integration layer, as well as a systematic user flow design from the discovery to the decision phase. Based on simulations using literature data, the designed framework has the potential to increase customer engagement by up to 169%, conversion rates by up to 11 times, and reduce product return rates by up to 50%. The benefits of this research include digital dimensions through E-Commerce technology innovation, social dimensions by increasing consumer trust and reducing product fraud, and environmental dimensions through the potential reduction of product returns. This conceptual prototype provides a foundation for digital innovation, social trust building, and environmental sustainability through reduced product returns.

This study aims to analyze the impact of immersive commerce and augmented reality (AR) on consumer trust in e-commerce transactions using secondary industry data from the BrandXR 2025 Research on Augmented Reality in Retail & E-Commerce. Quantitative data was analyzed descriptively to evaluate the adoption rate of immersive technologies (immersive commerce and AR) and their relationship with consumer trust perceptions. The results show that immersive commerce, characterized by interactive and realistic user experiences, has a positive impact on consumer trust. Similarly, AR which offers realistic product visualization, has a significant impact on strengthening consumer trust in purchasing decisions. Simultaneously, the integration of immersive commerce and AR enhance the digital shopping experience, which can reduce risk perception and increase trust in online transactions. These findings empirically contribute to the literature on digital consumer behavior and e-commerce strategies, and suggest that businesses adopt immersive technologies to increase consumer trust and engagement in the online commerce ecosystem.

Higher education management at the master's level currently faces urgent challenges, namely learning fatigue and low engagement among professional students, especially in Prior Learning Recognition (RPL) classes. Currently, lecturers still tend to apply conventional learning methods based on static presentations that fail to accommodate andragogical characteristics due to a lack of dynamic interaction. Therefore, this study aims to evaluate the effectiveness of the “Humanistic Digital Andragogy” approach through the integration of gamification (Kahoot) and visual thinking (Whimsical) in the Strategic Human Resource Management course. The researchers used a descriptive qualitative design with thematic analysis and collected data through feedback from students in the Master of Management Program (Semarang and Sorong classes). The results revealed that technology served as a double catalyst: Whimsical visualization effectively reduced the cognitive load of complex strategy material, while competition in Kahoot triggered positive adrenaline (eustress) that increased attention. These findings confirm that the success of technology is highly dependent on the role of lecturers as humanistic facilitators (high-touch). This synergy has been proven to change students' perceptions of HRM from merely administrative to strategic partners, as well as creating learning satisfaction that is relevant to the world of work.

This study explores the intellectual structure and research trends surrounding ethnocentrism in multinational corporations (MNCs) through a bibliometric mapping approach, with particular attention to cross-cultural management and workforce diversity studies. An initial dataset of 200 records was retrieved using Publish or Perish from Google Scholar and Crossref, of which 96 peer-reviewed journal articles published between 2020 and 2025 were retained following a PRISMA guided screening process. Bibliometric analysis was conducted using VOSviewer to examine keyword co occurrence, network relationships, and thematic density. The results indicate that ethnocentrism functions as a central organizing concept within the literature, closely associated with cultural differences, expatriation, workforce diversity, and organizational practices in multinational contexts. Temporal patterns observed in overlay and density visualizations suggest a growing scholarly emphasis on practice-oriented and context-specific perspectives, particularly in relation to managerial and organizational implications in global operations. Overall, this study offers a structured synthesis of existing research, highlights emerging thematic directions, and provides a foundation for future empirical and comparative inquiries into cultural diversity management in multinational corporations.

The rapid growth of e-commerce has intensified the need to understand transaction patterns and customer purchasing behavior as a foundation for strategic decision-making. This study aims to analyze e-commerce transaction patterns and customer purchasing behavior based on demographic characteristics and transaction timing. By utilizing e-commerce transaction data, this research seeks to provide a more comprehensive understanding of customers’ purchasing tendencies and the factors influencing their behavior. This study employs Exploratory Data Analysis (EDA) as the primary method to descriptively explore data characteristics through various statistical visualizations, including histograms, bar charts, line graphs, and boxplots. The analysis conducted to identify transaction trends, the distribution of purchase values, and behavioral differences across demographic groups and specific time periods. The results indicate that e-commerce transaction patterns tend to increase during certain periods, particularly in the latter part of the observation timeframe, suggesting the influence of seasonal factors and promotional strategies. The distribution of transaction values is asymmetric, with most transactions occurring in the low to medium value range, while high-value transactions are conducted by a relatively small proportion of customers. Furthermore, variations in purchasing behavior are observed across demographic groups in terms of transaction frequency and value, despite relatively balanced transaction volumes. The findings confirm that e-commerce customer purchasing behavior is influenced by a combination of temporal factors and demographic characteristics. These results are expected to serve as a basis for e-commerce practitioners in developing more targeted marketing strategies and as a reference for future research in the field of e-commerce data analytics.

The growth of online shopping has encouraged brands to utilize live-streaming as a promotional tool to attract consumers, including Parfumoist in Lampung, which actively broadcasts product demonstrations to increase audience engagement. However, whether these broadcasts truly build trust and stimulate purchase intention remains uncertain, forming the central problem of this research. The research tried to analyze the influence of interactivity, visualization, entertainment, and professionalization during live-streaming on consumer trust and purchase intention. Using Stimulus-Organism-Response framework, live-streaming elements are positioned as stimuli, trust as the organism, and purchase intention as the response. A quantitative approach was employed, with purposive sampling of viewers who watched Parfumoist live streams and had made or intended to make a purchase. Data from an online questionnaire then analyzed with SEM-PLS. The findings reveal all four dimensions of live-streaming significantly affect purchase intention, mediated through consumer trust. The findings highlight that effective live-streaming depends not only on frequent broadcasts, but also on the ability of the host to interact meaningfully, present attractive visuals, entertain viewers, and display professionalism. This study concludes that improving the overall quality of live-stream sessions strengthens trust and intention to buy, offering theoretical implications for digital marketing research and practical recommendations for MSMEs to optimize live-streaming strategies in competitive markets.

This study applies the Mean Variance model, which aims to form an optimal portfolio composition in the health, property, and cyclical consumer sectors and combine the three sectors into one portfolio, then visualize its efficient frontier. This study analyzes the return profiles and compares the risks of each portfolio using alternative risk measures such as the Coefficient of Variation (CV), Value at Risk (VaR), and Conditional Value at Risk (CVaR). Daily closing price data for the three sectors listed on the Indonesia Stock Exchange (IDX) from March 2, 2020, to March 3, 2025, were used in this study. Stock selection was conducted using purposive sampling, followed by selecting seven stocks for optimization based on the lowest Coefficient of Variation (CV) value. Portfolio optimization analysis was conducted using the Python programming language with Visual Studio Code software. The findings of this study indicate that the combined portfolio incorporating the three sectors is the most efficient, with an expected return of 0.104%, standard deviation of 0.007, and alternative risk measures such as Coefficient of Variation (CV) 6.9328, Value at Risk (VaR) of -0.99%, and Conditional Value at Risk (CVaR) of -1.44%, which are lower than those of single-sector portfolios. Visualization of the efficient frontier curve confirms that the combined portfolio offers better results in terms of risk and return. The results of this study indicate that cross-sector diversification can significantly reduce risk and prevent significant losses.

Rapid developments in the era of digital transformation, which refer to the emergence of business and technology innovations based on artificial intelligence, big data, and the Internet of Things (IoT), have great potential for strategic sustainability for businesses in the digital age. Efforts to transform digital business models as a global competitive advantage and provide outputs that can be oriented towards future predictions. Digital business models refer to strategic designs for creating platform networks that are implemented through relationships with consumers and cross-sector collaboration. Challenges and opportunities for development between transformation and innovation are necessary in order to create and capture competitive value and provide added value in the digital economy era. The use of bibliometric analysis in research provides direction in understanding the perspectives and issues that require further research, opens up space for exploring publication trends, and identifies the mapping of key concepts that form the basis of main ideas, thereby providing a more structured understanding and developing new research opportunities, especially in the field of digital business models. Bibliometric analysis aims to gain an in-depth understanding of research using the R studio application as a tool for processing data trends over time and VOSviewer as a knowledge map visualization tool. The research was conducted to provide an understanding of current and future developments in a dynamic environment.

The rise of financial technology (fintech) has significantly reshaped global investment over the last decade. Fintech innovations are increasingly applied in areas such as digital investment platforms, robo-advisors, blockchain-based assets, and cryptocurrency trading. The adoption of fintech in investment continues to grow due to the rising demand for accessibility, transparency, and efficiency in financial markets. Fintech has the potential to democratize investment by lowering entry barriers, expanding financial inclusion, and offering diverse investment instruments for retail investors. Therefore, research on fintech and investment has become an essential topic in recent years. This study uses a qualitative approach with data obtained from the Scopus database, which includes a total of 4,794 articles on fintech and investment published in the last decade (2020–2025). In addition, several software tools such as R Studio, VOSViewer, and Publish or Perish were used for data processing and bibliometric visualization. This study aims to analyze the development of research trends in fintech-driven investment, explore how technology is changing investor behavior, and provide insights for policymakers and practitioners in strengthening a sustainable and inclusive investment ecosystem.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

This study aims to analyze the development and scientific relationship between carbon risk perception, behavioral compliance of accountants, and sustainability mindset on the accuracy of carbon performance reporting through a bibliometric approach. This study is driven by the increasing need for accurate carbon reporting amidst global demands for sustainability transparency, as well as the limited understanding of the role of behavioral and psychological factors of accountants in ensuring the reliability of carbon reports. Research data was obtained from two leading scientific databases, namely Scopus and Google Scholar, with the main keywords "carbon risk perception," "behavioral compliance of accountants," "sustainability mindset," and "accuracy of carbon performance reporting." The data selection process was carried out using the PRISMA method to ensure the relevance and validity of the analyzed articles, while bibliometric analysis and visualization were performed using VOSviewer software. The results of the study indicate that the topic related to carbon reporting accuracy has evolved from a technical approach to a behavioral and psychological approach. Network and density visualizations show that behavioral compliance and sus-tainability mindset issues are still new but have high potential for development. Meanwhile, the authors' collaboration map demonstrates the geographic limitations of research, which remains concentrated in developed countries. These findings have important theoretical and practical implications, namely the need to integrate behavioral theory and professional ethics into sustainability accounting research and to en-hance accountants' capacity to understand carbon risks to ensure the accuracy of future sustainability re-porting.

Environmental management auditing is a strategic tool used to assess an organization’s performance in environmental management. Its main objectives are to enhance compliance with regulations, identify environmental risks, and strengthen corporate social responsibility. This study uses a bibliometric approach to analyze trends and research opportunities in the field of environmental management auditing during the period 2015–2025. Utilizing the Publish or Perish and VOSviewer software, this study examines 200 publications obtained through Google Scholar, revealing citation patterns, author collaborations, and frequently occurring keywords in the literature. The analysis results show that topics such as auditing, disclosure, governance, and big data dominate the existing literature, reflecting significant attention to transparency and data management in environmental audits. Additionally, there is a noticeable shift toward the use of technology in environmental auditing practices, including the use of big data and analytics to support audit processes. Bibliometric visualization also identified several areas with low density, such as implementation and environmental information, indicating potential research opportunities. This suggests that although significant research has been conducted, there is still room for further development, particularly regarding the implementation of environmental management audits across various industries. This study provides valuable insights into the development of more adaptive, multidisciplinary environmental auditing strategies that align with sustainable development goals.

The coffee farming sector in Gunungmanik Village, Indonesia, plays a significant role in the local economy. However, the monitoring and management of coffee crops remain largely manual and conventional, making it difficult for farmers to respond quickly to environmental threats such as drought, pests, or sudden temperature shifts. This research presents the development of iotgm.id, a web-based monitoring system integrated with Internet of Things (IoT) devices designed to provide real-time environmental data for coffee plantations. The system measures key parameters including temperature, soil moisture, and motion detection (as a proxy for pest activity), and delivers this data via a user-friendly web interface. It also features digital farm record management, real-time alerts for abnormal conditions, and data visualization through interactive dashboards. Field testing with local farmers showed that the system improves decision-making, speeds up responses to environmental changes, and reduces the need for direct field visits. Unlike earlier systems that often required technical expertise or focused on single parameters, this system offers multi-parameter monitoring and is accessible to farmers without advanced digital literacy. The system bridges the gap between sophisticated agricultural technologies and practical field-level application. It contributes to the adoption of precision agriculture in rural areas, offering a scalable model for broader implementation in similar contexts

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring. 

The digital revolution has transformed retail industry into a new era full of opportunities through e-commerce but also presenting challenges in online furniture sales. Due to their inability to precisely measure and see furniture in their spaces, many customers are hesitant to make purchases. Augmented Reality (AR) offers solutions through realistic visualizations, but it’s costly and has a lot of accessibility problems. WebAR solves these issues by delivering AR features directly on mobile browsers without requiring additional apps. This study investigates the impact of WebAR innovation on e-commerce furniture by examining the roles of interactivity (IN), vividness (VI), augmentation (AU), customization (CT), and ease of access (EA) on purchase intention (PI), mediated by spatial presence (SP), decision comfort (DC), and satisfaction (SF). Using the Stimulus-Organism-Response (SOR) model, data from 100 respondents were analyzed with the PLS-SEM algorithm using SmartPLS 4.0. The findings tell us that WebAR significantly enhances consumers’s shopping experience and ultimately boosts purchase intention.

This study investigates how data visualization helps retail companies make Business Intelligence (BI)-based decisions. The study processed one year of sales data with a quantitative descriptive approach to find seasonal patterns, performance by region, and customer consumption tendencies. The analysis results show that BI software such as Microsoft Power BI can visualize data more easily and accelerate understanding of business performance. Strategic decisions such as promotional planning and product inventory management are more effective with interactive visualization, which allows decision makers to see data in a more understandable way. The study found that data visualization in BI systems can help retail businesses make better decisions. These results show the importance of incorporating BI into a company's operational processes and using interactive visualization to improve overall business performance.

This study aims to systematically map the development of literature on Good Corporate Governance (GCG) using a mixed-method approach that integrates bibliometric analysis with VOSviewer and a systematic literature review. The research focuses on publications from the last five years (2020–2024), with data collected using the Publish or Perish software and the keyword “Corporate Governance.” The initial search identified 772 relevant scientific articles that met the inclusion criteria. Through network visualization analysis using VOSviewer, the study reveals that GCG research can be categorized into four thematic clusters, each representing distinct areas of focus. These clusters highlight key topics such as corporate performance, board structure, stakeholder relations, and sustainability practices, reflecting the diverse and evolving nature of GCG research. The findings provide valuable insights into the intellectual structure and research trends within the field, offering a foundation for future scholarly exploration and practical application.