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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 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

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 aims to examine the effectiveness of using animated video media in improving elementary school students’ understanding of the material of changes in the form of objects, which includes the process of melting, freezing, evaporating, condensing, and sublimating. The material is often difficult for students to understand because it is abstract and cannot always be observed directly. This research uses a qualitative method with a library research approach, where data is collected and analyzed from various reliable sources such as accredited scientific journal articles, books, and previous research results. The analysis technique used refers to the Miles and Huberman model, namely data reduction, data presentation, and conclusion drawing. The results of the study show that the animated video media can improve students’ cognitive understanding through visualization of complex processes, strengthen information retention, and reduce common misconceptions. In addition, this media is also proven to increase students’ motivation, interest in learning, and participation in learning. The effectiveness of animated videos is greatly influenced by the quality of visual design, narration, appropriate duration, and their integration in learning activities such as discussions or experiments. Despite challenges such as limited facilities and teacher training needs, strategic solutions can be implemented to optimize the use of this media. Thus, animated videos can be an innovative and relevant strategic alternative in science learning in elementary schools, especially in conveying abstract concepts in a concrete and fun way.

Dengue Fever (DF) continues to be a major public health threat in Indonesia, especially in urban areas with high population density, such as Purwokerto City. This study aims to develop a predictive model to identify high-risk areas for DF outbreaks by integrating Machine Learning (ML) algorithms and Geographic Information Systems (GIS). The research utilizes historical dengue case data, meteorological parameters (rainfall, temperature, humidity), and population density as predictive variables. Three ML classification algorithms—Naïve Bayes, Logistic Regression, and Support Vector Machine (SVM)—were implemented to develop risk prediction models. Extensive data preprocessing, feature selection, and spatial integration were applied to ensure model robustness. The results show that the SVM model outperformed other methods, achieving the highest accuracy, precision, recall, and F1-score in classifying dengue risk zones. Risk maps generated through GIS visualization successfully identify priority areas for targeted interventions. The novelty of this research lies in the combination of local epidemiological data, multi-algorithm comparison, and geospatial mapping to improve early warning systems for DF in Purwokerto. This integrated approach is expected to support more effective prevention strategies and enhance public health preparedness.

The development of AI has fundamentally transformed the professional ecosystem, creating a series of contemporary challenges for Generation Z preparing to enter the work arena. This study focuses on the development of motion graphic storyboards as an educational instrument to enhance Generation Z's employability capabilities for the AI era. Implementing a hybrid research methodology, data collection was conducted through digital surveys and in-depth dialog with experts to explore perceptions on the implications of AI on employment and the strategic competencies needed to adapt. The research findings indicate that Generation Z shows substantial awareness of the urgency of skills upgrading and transfer, although there is still a lack of clarity in understanding the concrete consequences of AI on future employment prospects. The motion graphic design developed presents an adaptive approach through an engaging storyline, narrative visualization, and interactive character elements, with an emphasis on the concepts of T-Shaped Skills and Transferable Skills. The research concludes that professional readiness in the era of AI digitalization requires not only technological understanding, but also adaptive flexibility, creativity, and synergy between human capacity and digital systems. Motion graphics were identified as the optimal medium to convey knowledge and strengthen Generation Z's position in anticipating future professional dynamics.

The automotive industry is a strategic sector that plays a crucial role in national economic growth. Facing rapid digital transformation, automotive companies are increasingly adopting Business Intelligence (BI) systems to facilitate a data-oriented decision-making process. This study aims to explore the implementation of BI in XYZ, one of Indonesia’s largest car manufacturers. Using a descriptive qualitative approach through literature review, the research highlights how BI dashboards enable real-time analysis of vehicle sales trends, regional performance, and product models. The findings indicate that BI significantly enhances strategic planning, marketing accuracy, and operational efficiency. Visual tools such as Tableau provide centralized dashboards that facilitate faster insights, enabling companies to adjust production and distribution strategies based on data patterns. The study concludes that BI is not merely a visualization tool but a vital element of the digital transformation strategy in the automotive sector.

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.

Web-Based Augmented Reality (AR) is an emerging interactive technology that is increasingly adopted in the fields of visual communication design and digital education. This study aims to analyze trends in the use of Web-Based AR within interactive design contexts and to identify user preferences regarding its features. The research employs a literature review and secondary data analysis, drawing from academic publications, industry reports, and online surveys conducted between 2019 and 2024. The findings reveal a significant increase in the adoption of Web-Based AR both globally and in Indonesia. Key factors driving adoption include interactivity without installation, cross-device compatibility, and rapid browser-based access. Trend diagrams, comparative tables of AR platforms (such as 8thWall, ZapWorks, and WebXR API), and user preference visualizations are presented to support the analysis. The study discusses technological challenges, adoption gaps, and design implications, particularly in education and marketing. Limitations include reliance on secondary data and limited geographic scope. The study’s outcomes are expected to serve as a reference for interactive content developers, educators, and researchers in designing inclusive and adaptive AR-based user experiences.

The manufacturing industry faces major challenges in maintaining consistent product quality amidst the dynamics of technology and global competition. This study aims to develop an effective Business Intelligence (BI) implementation model to support data-based quality control. The method used is a conceptual design approach through integrated system simulation, including MySQL database, PHP backend, Power BI visualization, Google Cloud AutoML predictive analytics, and initial processing using Microsoft Excel. Historical production data for 12 months is used for model training and defect trend visualization. The simulation results show that the implementation of BI can reduce product defect rates, accelerate system response, and increase inspection process efficiency. Technical validation proves the model's prediction accuracy is above 90%, while field validation shows positive acceptance from users regarding the ease of use of the dashboard. This system not only supports early detection of quality deviations but also contributes to real-time strategic decision making. With an integrated technology approach, BI enables medium-sized manufacturing companies to adopt an adaptive and sustainable digital quality system, in line with the concept of Quality 4.0.

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.

This study aims to analyze the forms of learning difficulties experienced by students in understanding the path independence theorem in the Vector Calculus course. The focus of the research is a group of students who had previously presented this material in class. Data were collected through a questionnaire containing both open- and close-ended questions to explore conceptual understanding, difficulties in distinguishing between conservative and non-conservative fields, and challenges in solving application problems. The analysis revealed that although students reported having a fair grasp of the basic concepts, they still expressed uncertainty in understanding the relationship between path independence and the conditions for conservative fields. Difficulties were also found in spatial visualization and in connecting concepts with the fundamental theorem of calculus. In addition, students showed a preference for worked example problem sets and visual learning media as the most effective learning supports. These findings indicate the need for an interactive, contextual, and visually supported instructional approach to enhance students’ conceptual understanding and application skills related to this topic.

This study aims to present a comprehensive bibliometric analysis of Intellectual Quotient (IQ), Emotional Quotient (EQ), and Spiritual Quotient (SQ) in an academic context, particularly focusing on the role of lecturers. Using bibliometric methods. The data for this study came from 300 English-language scientific articles published in 2023 from the Scopus and Google Scholar databases. The analysis was carried out using keyword co-occurrence techniques, overlay visualization, density visualization, and author collaboration networks. The findings show that there is a strong focus on developing conceptual frameworks and reviewing literature related to IQ, EQ, and SQ, indicating an effort to understand the integration of these three intelligences as the foundation for human resource development in higher education. However, several keywords were also found to be thematically irrelevant, suggesting challenges in data filtering or uniqueness of terminology between disciplines. Collaborative networks between authors tend to be fragmented, indicating the potential for fostering broader collaboration. The implications of this study theoretically reinforce the need for the integration of IQ, EQ, and SQ in understanding holistic intelligence, while practically encouraging higher education institutions to design lecturer development programs that balance these three aspects of intelligence to form superior character and performance

This study aims to systematically review the application of sensitivity analysis in operational decision-making based on linear programming. The research method used is a Systematic Literature Review (SLR), analyzing scientific articles published between 2018 and 2024 from databases such as Scopus, ScienceDirect, SpringerLink, and Google Scholar. The review focuses on how sensitivity analysis is employed to evaluate the stability of linear programming solutions in the face of parameter changes, such as objective function coefficients, constraint bounds, and resource availability. The results indicate that local sensitivity analysis approaches are the most commonly used due to their simplicity and ease of interpretation. However, they fall short in capturing parameter interactions and complex uncertainty. Therefore, recent studies have started to explore global sensitivity methods, such as Morris and Sobol techniques, as well as geometric visualization approaches to provide a more holistic understanding. This study recommends integrating both local and global approaches and utilizing computational tools to enhance the robustness of operational decisions. The findings are expected to serve as a reference for more adaptive, efficient, and resilient decision-making under uncertainty.

White shrimp (Litopenaeus vannamei) is an introduced species cultivated in Indonesia and plays an important role in increasing national shrimp production and exports. However, infectious diseases such as Enterocytozoon hepatopenaei (EHP) and Acute Hepatopancreatic Necrosis Disease (AHPND) pose a serious threat to the shrimp farming industry. These two diseases cause a decrease in shrimp growth and production performance. The Polymerase Chain Reaction (PCR) diagnostic technique is an effective method for detecting EHP and AHPND infections, because the results are fast and accurate. This research was carried out at the Juanda Fish Quarantine Laboratory, Animal, Fish and Plant Quarantine Center (BKHIT) East Java from July 1 to August 29 2024. This research aims to find out examination techniques and examination results for Enterocytozoon hepatopenaei (EHP) and Acute Hepatopancreatic Necrosis Disease (AHPND) during the examination process at BKHIT East Java. The test method used is a descriptive method by collecting primary and secondary data. The EHP examination at BKHIT East Java uses the single step PCR method, while the AHPND examination uses the Nested PCR method which consists of extraction, amplification, electrophoresis and visualization of the results. Based on the results of examinations during the activity, 4 samples were declared positive for EHP and no samples were declared positive for AHPND out of 51 samples of white shrimp (Litopenaeus vannamei).

The 2024 National Financial Literacy and Inclusion Survey shows that many Indonesians still do not understand financial fundamentals. This condition contributes to difficulty in managing personal finances. Therefore, financial education from an early age is needed to help people develop healthy financial habits. One effective medium for delivering financial education is a children’s savings book. However, most available savings books are less attractive and do not align with children’s preferences. This study aims to develop a children’s savings book design by integrating educational elements, such as a temporary money storage, based on users’ preferences. The Quality Function Deployment (QFD) approach was used to translate customer needs into product visualization. Data were collected through expert discussion, interviews, and questionnaires distributed using purposive sampling. The results show that the highest-priority feature for further development is the temporary money storage integrated into the book’s cover. This element was then incorporated into the children’s savings book design, while considering both functional and educational aspects.

The development of digital technology has changed the landscape of educational media, especially in the field of engineering, where abstract concepts often pose a challenge. In electrical engineering education, students often have difficulty understanding concepts such as current flow and circuit behavior due to limited class time and a lack of visualization tools. This study aims to evaluate the effectiveness of Augmented Reality (AR)-based learning media in enhancing conceptual understanding, learning outcomes, and student engagement in the Electrical Circuits course. A quasi-experimental design with pre-test and post-test control groups was applied, involving two groups: one group used AR-based media, while the control group used traditional instruction. Both groups underwent pre-tests and post-tests with 30 multiple-choice questions. Data were analyzed using descriptive statistics and N-Gain scores. Results showed that the experimental group experienced a significant improvement, with the average post-test score increasing from 62 to 81 and an N-Gain score of 0.48, while the control group only improved from 61 to 71 with an N-Gain score of 0.25. Statistical tests confirmed significant differences between the two groups. These findings indicate that AR is effective in enhancing understanding of complex concepts and can be integrated into technical education curricula to meet modern learning demands.

Cartography is a field that combines science and art in the creation of maps to present geographical information in a visual format. In this regard, cartography plays a vital role in simplifying complex and abstract geographical data, making it easier to understand and use. Maps allow for the representation of geographical phenomena through symbols, colors, and other visual elements, which facilitate analysis and decision-making. Furthermore, technological advancements, such as Geographic Information Systems (GIS) and satellite- based digital mapping, have enhanced cartography's ability to provide more accurate and dynamic data. This article discusses the role of cartography in presenting geographical data by highlighting visualization techniques, the use of the latest technologies, and its practical applications across various sectors. Therefore, cartography is not just a tool for creating maps but also an essential means of analyzing and understanding more complex geographical data.

Low motivation to learn and limited conceptual understanding are significant challenges in learning biology at the junior high school level, especially in abstract material on the classification of living things. This study aims to analyze the influence of the use of animated videos on student learning motivation and learning outcomes. A quantitative approach with a pre-experimental design of one group pre-test and post-test was used in this study. The research sample consisted of 25 students in grade VIII of SMP Negeri 2 East Likupang. Data was collected through observation sheets to assess learning motivation and pre-test and post-test tests to evaluate learning outcomes. The results of the observation showed that the average motivation of students reached 86.32% in the outstanding category. The average pre-test score of 59.57 increased to 81.09 on the post-test, indicating a significant improvement in concept comprehension. The t-test corroborates these findings with a significant value at a 95% confidence level. These results show that animated videos can present a visualization of complex concepts in an engaging and contextual way, thereby increasing students' focus, active participation, and absorption of the material. In addition, the use of this media also supports the development of students' collaborative skills and critical thinking. This research confirms that animated videos are a strategic alternative in effective science learning, especially in school environments with limitations of conventional visual media. It is suggested that the application of this media be expanded to various materials and levels of education.

The sign system in public spaces functions as a visual communication tool and shapes people's experiences and perceptions. The objectives of this study are; 1) to identify the types of signs found in shopping centers; 2) to analyze the function and role of these signs in supporting activities and social interactions in shopping centers; and 3) to explain how these signs influence visitors' perceptions and experiences. The research method used is descriptive qualitative with research stages including literature study, determining the location of the study, data collection, data analysis using Peirce's semiotic theory, data validity testing, and drawing conclusions. Data collection techniques are carried out through observation and documentation stages. The results of this study found that the visual sign system in the Ramayana Teladan Medan shopping center is classified into several categories of signs according to Charles Sanders Peirce's semiotic theory, such as Rhematic Indexical Legisign, Dicent Sinsign, Qualisign, and Iconic Legisign. Visualization of signs—whether through images, colors, or text—can influence visitors' understanding and behavior, for example by increasing alertness, compliance with rules, or perceptions of safety and comfort.