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Flooding is one of the most recurrent natural disasters in Central Java Province, particularly during the rainy season. Diverse geographical characteristics, high rainfall intensity, and rapid urban development contribute to the region’s high vulnerability to flood hazards. According to the Central Java Statistics Agency, a total of 414 flood events and 407,784 affected victims were recorded between 2019 and 2021. This study aims to develop a web-based Geographic Information System (GIS) capable of mapping the spatial distribution and impact levels of floods across Central Java. The methodology includes collecting flood event data from the Central Java Statistics Agency, processing spatial data such as administrative boundary shapefiles, performing attribute integration between spatial and non-spatial datasets, and creating thematic maps using QGIS. The visualization outputs were exported into an interactive web format using the qgis2web plugin and subsequently integrated into a website developed with HTML, CSS, and JavaScript. The results show that the GIS system successfully visualizes flood-prone areas, identifies regions with high flood intensity, and enables users to explore detailed information through interactive digital maps. Additional website features—such as historical flood data, statistical summaries, and descriptive impact indicators—enhance the system's usefulness for disaster analysis. This study demonstrates the crucial role of GIS in supporting disaster mitigation, spatial planning, and policy evaluation related to flood management. Future research is recommended to incorporate more recent datasets and additional non-spatial variables such as rainfall intensity and floodwater depth to improve the system’s analytical accuracy and comprehensiveness.

Per capita expenditure is an important indicator of household welfare because it reflects the economic capacity and consumption patterns of the community, as explained in Engel's Law. In regions with diverse geographical characteristics such as Papua Province, spatial analysis is needed to understand the variations in expenditure between districts/cities and the differences between urban and rural areas. This study aims to analyze the spatial distribution of per capita expenditure percentages for food and non-food items in nine districts/cities in Papua Province during the 2022–2024 period. The research data was sourced from the National Socioeconomic Survey (Susenas). The methods used included quantile-based choropleth mapping using QGIS, attribute data merging through table joins, and Pearson's correlation test to evaluate the consistency of spending patterns between years. The analysis results show that food and non-food spending patterns were relatively stable during the observation period with high correlation values (r = 0,85–0,93), although spatial variations between regions were still apparent. Mamberamo Raya Regency consistently had the highest proportion of food spending (>68%), while Jayapura City showed the lowest proportion. These findings indicate spatial disparities related to urbanization levels and economic access. Spatial visualization proved effective in revealing regional disparity patterns that were not fully apparent through conventional statistical tables and has the potential to support the formulation of more evidence-based regional development policies.  

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.

. Film as a mass communication medium not only functions as entertainment, but also as a means of representing power relations in society. Miracle in Cell No. 7 works by Hanung Bramantyo show various forms of official domination and legal inequality which are relevant to be studied through a hegemony perspective. This research aims to describe the forms of hegemony that appear in the film and interpret the social criticism conveyed through the narrative and visualization. The research uses qualitative methods with listening and note-taking techniques, then the data is analyzed through reduction, presentation and drawing conclusions based on Antonio Gramsci's theory of hegemony. The research results show that this film contains four forms of hegemony: ideological hegemony through the instillation of disciplinary values; hegemony of power through apparatus domination and abuse of authority; cultural hegemony through the imposition of a single standard of behavior; and moral hegemony through the formation of ethical judgments that benefit those in power. These findings indicate that films not only present emotional stories, but also present criticism of legal injustice and structural domination. This research confirms that visual media plays an important role in forming public awareness regarding the practice of power in social life.

. Film as a mass communication medium not only functions as entertainment, but also as a means of representing power relations in society. Miracle in Cell No. 7 works by Hanung Bramantyo show various forms of official domination and legal inequality which are relevant to be studied through a hegemony perspective. This research aims to describe the forms of hegemony that appear in the film and interpret the social criticism conveyed through the narrative and visualization. The research uses qualitative methods with listening and note-taking techniques, then the data is analyzed through reduction, presentation and drawing conclusions based on Antonio Gramsci's theory of hegemony. The research results show that this film contains four forms of hegemony: ideological hegemony through the instillation of disciplinary values; hegemony of power through apparatus domination and abuse of authority; cultural hegemony through the imposition of a single standard of behavior; and moral hegemony through the formation of ethical judgments that benefit those in power. These findings indicate that films not only present emotional stories, but also present criticism of legal injustice and structural domination. This research confirms that visual media plays an important role in forming public awareness regarding the practice of power in social life.

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.

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 skill mismatch between university graduates and technology industry requirements remains a significant challenge in Indonesia. PT Vinix Seven Aurum requires an assessment tool to objectively identify the initial competencies of MBKM and internship program participants. This research aims to design a web-based self-assessment platform that helps students measure their skill gaps against industry standards through radar chart visualization and personalized learning recommendations. The UI/UX design applies the Design Thinking method with empathize, define, ideate, prototype, and test phases, utilizing Figma for wireframe and high-fidelity prototype development. Data collection was conducted through observation, interviews, literature studies, and usability testing with 10 respondents. The results demonstrate good usability with a 100% completion rate across all features. The VINIX Skill Radar platform provides five assessment categories, a 1-10 rating scale system, radar chart visualization, gap analysis, and learning recommendations. This system enhances students' self-awareness of their competencies and supports effective mapping of training program participants' capabilities.

Tebing Tinggi City, which has a strategic position in North Sumatra, is experiencing changes in population growth that need to be predicted for development planning purposes. The purpose of this study is to forecast the population of Tebing Tinggi City in 2030 by applying the Double Integral method, and visualize the results in 3D using GeoGebra. The method used is a quantitative approach with a case study, where the population density function is created based on secondary data from the Central Statistics Agency (BPS) of Tebing Tinggi City for the period 2010 to 2024. Data on area and population per sub-district are used to develop a population growth model calculated using the double integral. The forecast results show that the population of Tebing Tinggi City is estimated to reach 26,038 people in 2030, with varying growth rates in each sub-district. 3D visualization through GeoGebra is able to depict the distribution of population density in an interactive geometric form, thus facilitating the understanding of complex mathematical concepts. The conclusion of this study is that double integrals can be applied effectively to predict population size, and GeoGebra serves as a very useful visual aid in presenting the results of multivariable calculus analysis.

The rapid development of the sea transportation industry produces a massive and complex volume of transaction data, requiring strategic management to support managerial decision-making. This research aims to implement the Executive Information System on SeaPass in order to evaluate the performance of ship ticket sales. The research method uses data visualization with a two-level drill-down mechanism, which allows the presentation of information hierarchically from general summaries to specific details. The methodological stages include needs analysis, user interface (UI) design using Figma, front-end implementation with HTML, CSS, and JavaScript, database integration, and system testing through Black Box Testing. The results showed that the SIE implementation successfully integrated operational data, including schedules, ships, and manifests, into an interactive dashboard. The two-level drill-down feature provides the ability for executives to identify operational anomalies and market fluctuations in real-time. In conclusion, the system significantly enhances executive data analysis capabilities, transforming complex transaction data into accurate strategic information, thereby supporting more precise business decision-making and adaptive to the dynamics of the marine transportation market.

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 difficulties experienced by students in understanding abstract concepts in Islamic creed (akidah) and to evaluate the effectiveness of Islamic-based animation learning media as an innovative and interactive solution. The research employs a qualitative Classroom Action Research (CAR) approach, conducted in two learning cycles using observation, interviews, documentation, and questionnaires as data collection techniques. The implementation of Islamic animation learning media demonstrated a significant improvement in students’ conceptual comprehension. The results indicate that the average understanding score increased from 35.25% in the preliminary stage to 89.25% after the final cycle, showing a substantial rise in students’ achievement levels. In addition, students’ enthusiasm, motivation, and active participation in classroom activities increased markedly when learning materials were presented through animated visualization rather than conventional lecture-based instruction. Expert validation confirmed that the developed instructional media meets pedagogical, didactic, and visual quality standards, and responses from teachers and students revealed positive perceptions regarding the relevance and attractiveness of animation-based learning. The findings highlight that Islamic-based animation learning media serves as an effective educational tool capable of simplifying and concretizing abstract theological concepts, enabling learners to construct deeper understanding through visual and contextual illustration.Therefore,the study recommends the broader application of animation-based Islamic instructional media in akidah education to enhance comprehension, engagement, and learning outcomes in schools.

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.

The advancement of information technology has encouraged organizations to transform their data management practices, including those within the electrical power sector. PT PLN (Persero) UP3 Lubuk Pakam previously utilized Google Sheets to store and manage electrical energy loss data. However, this approach posed data security risks, as the files could be accessed and modified by unauthorized individuals. To overcome these limitations, this study developed a web-based information system specifically designed for the Electricity Energy Transaction Division (TEL) to replace Google Sheets as a platform for managing energy loss data. The proposed web application integrates a Role-Based Access Control (RBAC) mechanism, ensuring that only administrators are authorized to input, edit, or delete data, while other users can only view validated records. Furthermore, the system incorporates interactive data visualization through real-time charts, facilitating effective monitoring and analysis of electrical energy losses. The implementation of this system is expected to enhance data security, accuracy, and management efficiency within the TEL Division of PT PLN UP3 Lubuk Pakam.  

This study aims to examine customer segmentation through K-Means clustering from a customer data management perspective, emphasizing the interpretive value of analytical results rather than solely their computational outcomes. The research addresses a critical issue in contemporary data-driven organizations, where customer analytics is often reduced to technical modeling without sufficient translation into managerial insights. To respond to this gap, the study adopts a qualitative interpretive approach embedded within a quantitative clustering process, positioning clustering as part of a broader information management cycle. The empirical analysis is based on the Mall Customers Dataset obtained from Kaggle, consisting of 200 customer records with numerical attributes representing age, annual income, and spending score. Quantitative processing using K-Means clustering was employed to identify customer segments, while qualitative interpretation was applied to analyze the managerial meaning of each cluster. Data interpretation was supported by analytical documentation, visualization outputs, and reflective analysis of cluster characteristics. The findings reveal four distinct customer segments with different behavioral and economic profiles, each carrying specific strategic implications for customer relationship management and marketing decision-making. The study demonstrates that the primary value of clustering lies not merely in segment formation, but in its ability to transform raw customer data into actionable managerial knowledge. In conclusion, this research contributes to customer analytics literature by integrating data mining techniques with qualitative interpretation, offering a more human-centered and decision-oriented framework for customer data management. Future research is encouraged to extend this approach using organizational case studies or participatory decision-making contexts.

This study maps the regulatory landscape of financial technology (fintech), focusing on cryptocurrency regulation at both global and Indonesian levels. Cryptocurrency, one of the fastest-growing fintech instruments, functions as a virtual currency secured by cryptography. Despite lacking physical form, it is widely used for investment, transactions, and speculation, with trust supported by blockchain’s transparency and immutability. However, regulatory frameworks remain fragmented across countries. The research applies a bibliometric approach, using Bibliometrix (R Studio) for descriptive analysis and VosViewer for keyword network visualization. Data were retrieved from Scopus with the keywords “cryptocurrency regulation” and “fintech regulation,” covering 2016–2025. Findings reveal 1,178 documents from 484 sources, contributed by 4,693 authors, with an average of 7.43 authors per document and an international collaboration rate of 24.79%. The annual growth rate reaches 44.31%, with an average of 14.01 citations per document. Keyword analysis identifies four main clusters: financial regulation, green finance and sustainability, decentralized finance (DeFi), and blockchain cybersecurity. This study provides a knowledge map of regulatory evolution from conventional finance to blockchain-based fintech, offering insights for academics, regulators, and industry to balance innovation, consumer protection, and financial stability.

The integration of green marketing into corporate strategies represents a paradigmatic shift in responding to global sustainability issues while enhancing competitiveness and socio-ecological commitment. With the rapid growth of literature in this field, a systematic analysis is required to map its conceptual evolution and strategic directions. This study presents a bibliometric analysis of global research trends in green marketing, aiming to identify the intellectual structure, thematic evolution, and knowledge development over the period 2017–2024. Using the Scopus database and the Biblioshiny and VOSviewer tools, 275 peer-reviewed articles were examined through quantitative bibliometric mapping techniques. The analysis reveals an annual publication growth rate of 15.27%, with dominant themes such as “sustainability,” “green marketing,” and “sustainable development.” Thematic mapping visualizations indicate a shift in research focus from product-related technical issues to strategic, social, and consumer behaviour dimensions. Five major thematic clusters were identified, reflecting interdisciplinary approaches encompassing digital marketing strategies, consumer behaviour, corporate social responsibility, supply chain management, and environmental ethics. These findings underscore the significance of integrating green marketing as a sustainable business strategy, not only to enhance corporate image but also to foster more environmentally responsible consumer behaviour. The study provides a conceptual foundation for future inquiries and strategic implications for business practices, affirming the role of green marketing as a catalyst for organizational transformation toward environmental and social sustainability.

Sentiment analysis of guest reviews is a crucial aspect in improving the quality of hotel services. This study aims to analyze the sentiment of guest reviews regarding the services of Grand Diamond Hotel Yogyakarta using a machine learning approach with the Support Vector Machine (SVM) algorithm. SVM was chosen because it can handle high-dimensional data such as text and is capable of forming an optimal separating hyperplane between sentiment classes. The research data was obtained through web scraping from Traveloka, yielding 1,119 reviews, which were processed through preprocessing, translation, and sentiment labeling using the TextBlob library. After TF-IDF weighting, the data was divided into 80% for training and 20% for testing. The linear kernel SVM model achieved 80% accuracy in classifying the reviews into positive, negative, and neutral categories. The results of this study were implemented in a web-based application equipped with data visualization and model evaluation features, allowing hotel management to efficiently monitor and analyze guest sentiment and support data-driven service quality improvement.