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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.

Advancements in modern information technology continuously require companies to present complex data more effectively, especially within the scope of sales management and business decision-making. Dashboards are essential, interactive tools that enable professionals and managers to make strategic decisions quickly, confidently, and based on accurate data visualization. This study focuses on designing an intuitive and user-centered Sales Monitoring Dashboard UI/UX for One Direction at PT. XYZ by applying the five iterative stages of the Design Thinking method, namely empathize, define, ideate, prototype, and test. Key user needs identified include real-time performance summaries, streamlined navigation flow, informative visual hierarchy, and visuals that remain consistent with corporate identity and brand values. The System Usability Scale (SUS) test involving 19 respondents resulted in an excellent average score of 80.92. These findings demonstrate that the Design Thinking approach effectively produces a user-friendly, consistent, and data-driven dashboard interface that supports timely, accurate, and informed business decisions.

Shallots are one of the most strategic horticultural commodities in Indonesia, with high demand and varying production levels across regions. Differences in productivity between areas often create challenges in managing distribution and formulating national food policies. This study aims to analyze shallot production data in Indonesia by applying the K-Means Clustering algorithm using Python. The production data were collected from official agricultural statistics publications, followed by preprocessing, normalization, and determination of the optimal number of clusters using the Elbow method and Silhouette Score. The clustering results show the formation of several groups representing regions with high, medium, and low production levels. Visualization of the clustering results reveals the distribution patterns of shallot production, which can serve as a basis for supporting policy formulation in the development of shallot production centers in Indonesia. Thus, the application of K-Means Clustering with Python proves to be an effective approach to provide clearer insights into regional production variations and can be utilized as an analytical tool to support decision-making in the agricultural sector.

The Student Evaluation of Lecturers (EDOM) at the Faculty of Engineering, Universitas Dr. Soetomo has historically been conducted via Google Forms and processed manually, resulting in slow response times, repetitive recap procedures, and insufficiently documented reporting validity. This study aims to design, build, and evaluate a web-based EDOM system using the Prototype Model (MODEL PROTOTYPE) to improve data collection efficiency, recap accuracy, and the effectiveness of feedback for teaching quality assurance. The development method comprises requirements elicitation with the Quality Assurance Unit through a review of SPMI documents and brief interviews, architectural and interface design (Laravel, MVC pattern, and MySQL), staged prototyping, and rapid iterations based on stakeholder feedback until functional conformity is achieved. The resulting system provides authentication and role-based authorization (Admin, GPM, Lecturer, Student), odd/even period management, a question bank employing a Likert scale, anonymous questionnaire submission, score recap per lecturer and per category (pedagogical, professional, personal, social), dashboard visualizations, and report export to support governance needs. Functional evaluation was conducted through black-box testing on core scenarios (login, period scheduling, submission, recap, and export) and indicated conformance to specifications. User acceptance evaluation employed the Technology Acceptance Model (TAM) to examine perceived usefulness, perceived ease of use, attitude toward use, and behavioral intention; the results indicate positive acceptance and potential for operational adoption. Practically, the prototype approach accelerates requirement alignment, reduces the risk of mis-specification, and facilitates change control, while the Laravel-based implementation supports maintainability, role-based access security, and further feature development. The study is limited to a single faculty; future work may include SSO integration, audit trails, and longitudinal, cross-semester analytics for more comprehensive monitoring of lecturer performance.

Sleep is a fundamental human need that plays a crucial role in maintaining both physical and mental health. Poor sleep quality can trigger a variety of health problems, ranging from decreased concentration to an increased risk of chronic diseases. The complexity of factors influencing sleep quality—such as stress levels, heart rate, blood pressure, physical activity, and lifestyle—makes its assessment difficult through direct observation alone. Therefore, data mining approaches are increasingly utilized to identify relevant patterns in sleep-related data. This study aims to compare the performance of the C4.5 (Decision Tree) algorithm and the Naïve Bayes algorithm in predicting sleep quality using the Sleep Health and Lifestyle dataset, which contains information from 374 respondents. The research method applied is a quantitative comparative approach employing classification techniques with 10-fold cross-validation to ensure robust evaluation. Model performance is assessed using accuracy, precision, and recall metrics to provide a comprehensive understanding of the effectiveness of each algorithm. The findings indicate that the C4.5 algorithm achieves an accuracy of 96.26% and offers advantages in terms of interpretability through its decision tree visualization, enabling easier understanding of variable relationships. In contrast, the Naïve Bayes algorithm demonstrates superior predictive performance, achieving an accuracy of 98.66% along with consistently high precision and recall across nearly all classes. These results suggest that Naïve Bayes is more effective for predictive tasks involving sleep quality, while C4.5 remains highly valuable when the goal is to interpret variable interactions and decision rules. Overall, this research highlights the potential of data mining techniques in health informatics, particularly in improving the understanding and prediction of sleep quality, which in turn can contribute to better prevention and management of sleep-related health issues.

Conventional robotic surgical systems, while offering enhanced dexterity and 3D visualization, suffer from a critical limitation: the absence of tactile sensation. This sensory disconnect can lead to inadvertent tissue damage from excessive force application and complicates delicate maneuvers that rely on the surgeon's sense of touch. This research proposes and validates a novel surgical robotic system architecture designed to bridge this sensory gap by integrating high-fidelity 3D visual input with accurate, real-time force feedback from tactile sensors mounted on the end-effector. To rigorously evaluate this innovation, a structured comparative methodology was employed. A cohort of surgeons performed standardized surgical tasks, including suturing and tissue manipulation, on realistic soft-tissue phantoms. The performance of a conventional (visual-only) system was benchmarked against that of the proposed (visual-haptic) system. A comprehensive dataset was collected, which included objective metrics such as task completion time, precision deviation from the ideal tool path, and the magnitude of applied forces. Concurrently, subjective evaluations from the participating surgeons were gathered to assess perceived control, cognitive workload, and overall task confidence. The test data revealed statistically significant improvements when using the visual-haptic system. Participants not only completed tasks with greater speed and accuracy but also applied considerably lower and more consistent forces. The analysis underscores that haptic feedback, enabled by advanced sensor fusion, not only restores a crucial 'sense of touch' to the surgeon but also reduces the incidence of excessive force application, potentially minimizing tissue trauma and improving patient recovery. These findings confirm the hypothesis that haptic-visual integration constitutes a new paradigm in robotic surgery, shifting the paradigm from purely visual guidance to a more intuitive, multi-sensory surgical experience. This study also discusses future challenges and opportunities, including the potential for AI-driven partial autonomy, such as creating virtual safety boundaries or automating sub-tasks, and the development of next-generation sensor technologies to further enhance clinical outcomes.

Liquefied Petroleum Gas (LPG) leakage remains one of the leading causes of fires in both household and industrial environments, highlighting the urgent need for early detection systems that provide fast and accurate warnings. This study aims to design and implement an LPG leakage detection device based on the ESP8266 microcontroller, utilizing the MQ-6 gas sensor and a real-time notification system through Telegram Bot integration. The system operates by reading LPG gas concentration via the MQ-6 sensor, which is then processed by the ESP8266 to automatically activate a buzzer alarm and a DC fan when gas levels exceed the threshold of 200 ppm. Additionally, the system sends instant alert notifications to the user through the Telegram application, allowing remote monitoring of gas conditions. Real-time gas concentration data are also displayed using a 16x2 LCD for direct visualization. System testing was carried out through controlled gas leakage simulations, and the results showed that the device is capable of responding rapidly, with a reaction time of less than 2 seconds after detection, while consistently providing accurate warnings. The integration of Internet of Things (IoT) technology significantly enhances the effectiveness and efficiency of the system, enabling practical and accessible monitoring. Overall, the developed device demonstrates strong potential as an innovative solution to improve safety, minimize fire risks, and raise public awareness regarding the hazards of LPG leakage, making it suitable for practical application in households and small industries.

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.

Discipline is a crucial aspect of education that plays a significant role in shaping students’ character and sense of responsibility. However, the manual discipline assessment process at SDIP Baitul Maal presents several issues, such as inaccurate data, limited analysis capabilities, and difficulty for teachers and parents to monitor students effectively. With the advancement of information technology, digital systems offer a potential solution to improve the efficiency and objectivity of the evaluation process. This study aims to design and develop a web-based application for assessing student discipline by implementing the K-Means Clustering method optimized with the Elbow method. The system is designed to cluster students based on numerical data such as attendance, tardiness, neatness, and rule violations, allowing for more accurate classification of discipline levels. The results show that the system successfully groups students into clusters automatically and provides informative visualizations of the outcomes. Additionally, the system facilitates real-time monitoring and evaluation by school staff and parents through a user-friendly interface. Therefore, the application of the K-Means Elbow method proves effective in supporting decision-making within the educational environment. This research is expected to contribute to the digital transformation of school management and enhance the quality of student character development.

A lopography or barium enema colostomy is a radiographic examination of the colon using a contrast medium inserted through a colostomy. This examination aims to evaluate the condition of the colon after the colostomy, including detecting the presence of obstructions or masses in the gastrointestinal tract. The contrast medium used is a type of non-ionic soluble water that is inserted through the stoma and anus orifice until it fills the entire colon, characterized by the exit of contrast through the stoma. The examination was carried out using several radiographic projections, including plain photographs of the AP abdomen, as well as post-contrast projections of the Antero Posterior (AP), Right Posterior Oblique (RPO), Left Posterior Oblique (LPO), and lateral. This study aims to find out the procedure for the Lopography examination at the Radiology Installation of Caruban Hospital and the medical reasons for the use of two channels of input of contrast media, namely through the stoma and anus. The method used is qualitative descriptive research with a case study approach. The study was carried out from November to May 2025, with one post-colostomy patient as a sample. Data collection was carried out through direct observation, interviews with medical personnel, and documentation of radiographic procedures. Data analysis includes data reduction, data presentation, and conclusion drawn. The results of the study showed that the procedure of Robotic examination did not require any special preparation before the procedure. The non-ionic contrast medium used is mixed with aquades at a ratio of 1:3 (about 200 cc), and inserted through both the stoma and the anus to obtain a thorough visualization of the colon. The selection of two input paths aims to ensure that there are no blockages or masses that block the contrast flow. The projections used are adjusted to provide maximum information about the structure of the colon after colostomy

This research is motivated by students' low basic table tennis skills, particularly in the technical aspects of holding the racket, hitting the ball, and maintaining proper body position. This condition results in low student learning outcomes in physical education subjects, so learning media that can support the learning process more effectively are needed. One alternative media that can be used is tutorial media, because it has the advantage of presenting movements visually, systematically, and can be repeated according to student needs. The method used in this study was an experiment with a one-group pretest-posttest design. The research subjects were 20 fifth-grade students of Begawat 01 State Elementary School, selected using a total sampling technique. The research instruments included a practical test of basic table tennis skills, observation, and documentation. Data on student learning outcomes before and after the treatment were then analyzed to determine differences in ability. The results showed a significant increase in basic table tennis skills after the use of tutorial media. Students were able to improve their racket holding techniques, adjust their body position, and become more skilled at hitting the ball. In addition, the use of tutorial media also had an impact on increasing student learning motivation and participation in practical activities. The clearly displayed visualization of movements helped students understand the steps of basic techniques more quickly and effectively. The conclusion of this study is that tutorial media is proven to be effective in improving the table tennis learning outcomes of fifth grade students at Begawat 01 State Elementary School. The implications of this study emphasize the importance of utilizing innovative learning media to support the physical education learning process, so that learning objectives can be achieved more optimally.

Weather and cloud cover are two fundamental atmospheric elements that are closely interconnected and play a vital role in understanding, classifying, and predicting atmospheric conditions. Accurate classification of weather conditions is essential not only for meteorological studies but also for practical applications in agriculture, aviation, transportation, and disaster management. Among the various statistical techniques available, correspondence analysis has proven to be an effective exploratory method for revealing associations among categorical variables by displaying their relationships in a two-dimensional graphical map. The primary objective of this study is to examine the relationship between different categories of weather conditions and levels of cloud cover using correspondence analysis. The data were sourced from the Kaggle platform, consisting of 13,200 observations with two key categorical variables: weather conditions (sunny, cloudy, rainy, and snowy) and cloud cover (clear, partly cloudy, cloudy, and overcast). This large dataset provides sufficient variability and reliability to capture the complex interdependence between the two variables. The findings reveal a statistically significant relationship between weather categories and cloud cover levels. The correspondence map visualization shows distinct patterns: clear weather is strongly associated with cloudless skies, while rainy and snowy weather conditions are predominantly linked to fully overcast skies. Cloudy and partly cloudy conditions occupy an intermediate position on the correspondence map, reflecting a transitional state between favorable and unfavorable weather. The first dimension of the map represents a spectrum from favorable weather conditions (sunny and clear) to adverse conditions (rainy and snowy), whereas the second dimension primarily reflects the intensity or density of cloud cover, ranging from thin to thick cloud layers. Overall, this study demonstrates the usefulness of correspondence analysis as an exploratory tool for meteorological data, offering valuable insights into the interrelation of weather and cloud cover categories.

Steel structure projects are increasingly favored in the construction industry due to their benefits in execution time efficiency and long-term cost savings. However, the suboptimal management of human resources (HRM) remains a significant challenge in achieving these efficiencies. This study aims to systematically review the role of HRM in enhancing time and cost efficiency in steel structure projects. A Systematic Literature Review (SLR) was conducted based on the PRISMA protocol, analyzing 35 accredited scientific articles published between 2013 and 2023. The articles were sourced from national databases such as Garuda and Neliti, and data were extracted using standardized documentation instruments. The analysis reveals that workforce planning, project-based training, performance monitoring, and inter-team coordination are key managerial aspects that consistently contribute to improving both time and cost efficiency. Visualization of topic networks using VOSviewer highlights strong interconnections between themes such as "training," "schedule control," and "performance evaluation," all of which are critical components of strategic HRM practices. This study concludes that HRM plays a crucial role in achieving efficiency in steel structure projects, especially through the integration of technical workflows and managerial control systems. Effective workforce planning ensures that the right skills are available at the right time, while performance monitoring and training programs help enhance productivity and reduce delays. The findings suggest the necessity for formulating HR policies that are based on workload analysis and the improvement of real-time workforce evaluation mechanisms. Furthermore, the study calls for further research to test integrative models for HRM practices in steel-based construction projects in Indonesia. This research opens avenues for refining HRM strategies to support the construction industry’s efficiency goals, offering insights for future studies and practical applications in the field.

This study examines the role of sound design in creating a mystical atmosphere in the song “Alternate Universe” by the independent Yogyakarta band, The Melting Minds. The song adopts an exploratory approach to sonic atmosphere creation through elements such as sub-bass drones, long reverbs, pitch-shifted vocals, and extreme spatial panning. The aim of this research is to identify the sound design techniques used and analyze how listeners interpret their listening experience and how these elements contribute to the emotional experience and mystical perception built by the song. The approach used in this research is a qualitative descriptive-interpretative method, with data collected through audio analysis, documentary observation, semi-structured interviews, and open-ended questionnaires given to 15 experimental music listeners. The theoretical framework includes Schafer’s soundscape theory, Schaeffer’s sound objects, Juslin & Västfjäll's BRECVEMA model of music emotions, and Stuart Hall’s reception theory to understand how listeners interpret their experience. The results show that sound design in this song is used strategically to create a transcendental listening experience, evoking a liminal and affective atmosphere. Techniques such as the use of deep sub-bass drones, extended reverbs, pitch-shifted vocals, and extreme spatial panning were found to be highly effective in shaping a mysterious and profound atmosphere. Listeners reported visualizations of a supernatural space, a floating sensation, and even intense spiritual experiences during the listening. 

PT. Soemo Adjie Persada is a company engaged in housing development and is dealing with serious problems in warehouse material management. The manual and unstructured material recording system causes various obstacles, such as data discrepancies, input errors, and stockouts that hamper the smooth running of the project. This study aims to analyze and implement the Kanban system as a more efficient and accurate material management solution. The study was conducted using a qualitative descriptive approach through interviews, observations, and documentation methods. The findings show that the Kanban system, which is based on the principle of workflow visualization and a pull system mechanism, can improve the efficiency of recording and distributing materials between project units. The implementation of Kanban helps reduce data input errors, prevent material loss, and accelerate the decision-making process in the warehouse. Although challenges such as damaged Kanban cards and difficulty adapting among users were encountered in the initial implementation stage, these obstacles can be overcome through proper training and regular evaluation of the system. Thus, the implementation of the Kanban system has proven to be an effective strategy in improving the efficiency of material management in construction projects. This system not only streamlines warehouse operations but also improves control over material availability, thereby supporting the smooth running of the overall construction process. PT. Soemo Adjie Persada is a company engaged in housing development and is dealing with serious problems in warehouse material management. The manual and unstructured material recording system causes various obstacles, such as data discrepancies, input errors, and stockouts that hinder project progress. This study aims to analyze and implement the Kanban system as a more efficient and accurate material management solution. The study was conducted using a qualitative descriptive approach through interviews, observation, and documentation.

Building Information Modeling (BIM) is a technology increasingly used in the modern construction industry, particularly to improve communication efficiency and collaboration between stakeholders. This technology enables the integration of project data and information into a comprehensive digital model, allowing all involved parties to access, verify, and update information in real time. This study aims to evaluate the strategic role of BIM as a communication medium in the Integrated Project Delivery (IPD) approach, focusing on the planning stage involving the disciplines of architecture, structure, and Mechanical, Electrical, and Plumbing (MEP) systems. The IPD approach emphasizes cross-disciplinary collaboration from the early stages of a project to optimize outcomes, reduce risks, and accelerate completion. The research methods used are literature review and case study analysis of various projects that have implemented BIM within the IPD framework. The data analyzed include the effectiveness of information exchange, inter-team coordination, and early identification of design conflicts. The study results show that BIM significantly improves information transparency among stakeholders, minimizes the risk of miscommunication, and accelerates the decision-making process through accurate and integrated data visualization. BIM models also facilitate the detection of potential conflicts, such as clashes between structural and MEP elements, before entering the physical construction phase, thereby reducing repair costs and delays. Furthermore, the use of BIM in IPD fosters a more collaborative work culture, where architects, engineers, and contractors can work together to solve problems quickly and effectively. Thus, BIM has proven to play a crucial role as a primary communication tool in IPD implementation, while also serving as a crucial foundation for achieving efficient, integrated, and high-quality construction project management.

Improving the quality of biology learning in secondary schools requires pedagogical innovations that connect academic content with real-life contexts and leverage digital technology. This study aims to analyze the effect of a contextual teaching approach assisted by interactive PowerPoint on students’ learning outcomes in the human respiratory system topic. A true experimental design with a pretest–posttest control group was employed at SMA Negeri 1 Langowan, involving two eleventh-grade classes selected through simple random sampling. The experimental class received contextual instruction integrated with interactive PowerPoint, while the control class was taught using conventional methods. Data were collected through validated achievement tests and analyzed using normality and homogeneity tests, followed by independent and paired t-tests. The results indicate a significant improvement in learning outcomes for students in the experimental class compared to the control group. The experimental group’s posttest scores were substantially higher, and the difference was statistically significant. Integrating a contextual approach with interactive visualization effectively enhanced students’ understanding of abstract biology concepts, promoted active participation, and strengthened learning motivation. These findings support constructivist theory and highlight the relevance of contextual teaching in science education aligned with the Merdeka Curriculum. The study implies the importance of implementing context-based strategies combined with simple digital media to improve biology learning effectiveness. Future research may explore its impact on non-cognitive skills such as critical thinking and scientific attitudes. Furthermore, the results of this study provide opportunities for teachers to be more creative in designing teaching materials that are not only informative but also interactive and relevant to students' lives. By utilizing media such as interactive PowerPoint, teachers can present complex biological content in a more engaging and understandable way.

Blockchain logistics represents the integration of blockchain technology into the logistics sector, aiming to enhance efficiency, transparency, and security across supply chain processes. From an Islamic economics perspective, digital transformation must align with core values such as justice, transparency, and honesty to support the development of fair and sustainable logistics systems. The decentralized nature of blockchain offers promising solutions for building supply chains rooted in Islamic ethical principles. This study conducts a bibliometric analysis to examine the development and research trends of blockchain logistics within the context of Islamic economics. Using VOSviewer software, relevant scientific publications were analyzed based on bibliographic data sourced from reputable academic databases. Bibliometric parameters—such as the maximum number of authors per document and the minimum number of documents per author—were applied to identify key contributors and dominant research themes. The bibliometric mapping reveals the growth trajectory of blockchain logistics research framed by Islamic values. The visualization highlights research clusters, prominent authors, co-authorship networks, and publication trends that illustrate the evolution and scholarly interest in this interdisciplinary area. Emerging themes suggest a convergence between blockchain-driven logistics innovation and ethical economic practices advocated in Islamic teachings. The findings provide a comprehensive overview of the current landscape and collaboration opportunities in blockchain logistics research through an Islamic lens. This study contributes to the strategic positioning of future research by identifying gaps, potential synergies, and critical areas for development. Ultimately, it offers a foundational reference for scholars seeking to explore the integration of Islamic ethical principles within the advancement of blockchain-enabled logistics systems.

Urinary tract examination with the CT-Scan modality is considered superior to other imaging modalities because it produces better image resolution, clear anatomical details, and is able to accurately detect abnormalities. At the Radiology Installation of Brebes Hospital, the CT-Scan Urography examination is carried out without fasting requirements. Patients are only asked to remove metal objects from the abdominal area and hold urination before the examination begins. This aims to keep the urinary bladder (VU) fully filled so that it facilitates the evaluation of the anatomy of the urinary system, especially in detecting kidney stones which are the main complaints of patients. This study aims to find out in detail the procedure for CT-Scan Urography clinical urography of kidney stones, as well as the reasons why patients are asked to hold urination and are not asked to fast before the procedure is performed. The research method used is a mix method, which is a combination of qualitative and quantitative, with data collection through observation, interviews, and documentation. The research sample consisted of 3 patients who underwent CT-Scan Urography clinical examination of kidney stones at the Radiology Installation of Brebes Hospital. The results of the study showed that the procedure started from the patient's preparation, such as removing metal objects, drinking mineral water, and holding urination so that the VU was fully filled, thus helping the visualization of organs and urinary tract. This examination does not require fasting because the CT-Scan modality is able to provide a clear picture of the anatomy of the urinary tract without interference from the digestive system. These findings confirm that the CT-Scan Urography procedure at Brebes Hospital is simple, effective, practical, and provides optimal diagnostic results for patients.

This study focuses on the development of an interactive web-based learning platform for Proportional-Integral-Derivative (PID) control systems, aimed at addressing the conceptual challenges faced by electrical engineering students when learning PID through conventional teaching methods. Despite its foundational role in control theory, PID remains difficult to grasp without practical visualization and hands-on experimentation. To bridge this gap, the research introduces a practical and accessible platform that enhances conceptual understanding through real-time simulations and physical interaction. The proposed system integrates key hardware components including an ESP-32 microcontroller, DC motor, rotary encoder, BTS 7960 motor driver, and I2C LCD. The platform’s web interface is built using HTML, Tailwind CSS, and JavaScript, enabling intuitive user interaction. Motor response data is captured via the ESP-32 and transmitted to the web interface using the WebSocket protocol, allowing users to instantly visualize system behavior as PID parameters (Kp, Ki, Kd) are adjusted. This dynamic feedback mechanism enables students to observe changes in system characteristics such as rise time, overshoot, and settling time in real time. To evaluate the platform’s feasibility, practicality, and educational effectiveness, beta testing was conducted among electrical engineering students using Likert-scale questionnaires. The results demonstrated that users were able to successfully interpret the impact of PID tuning on system performance. The average evaluation score reached 75.13%, indicating strong agreement regarding the platform’s educational value and its effectiveness in enhancing learning outcomes. In conclusion, the study affirms that the developed web-based platform offers a feasible, engaging, and pedagogically effective alternative to traditional learning approaches. By combining interactive simulations with physical experimentation, the platform significantly improves students’ understanding of PID control systems.