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This study aims to analyze consumer purchasing behavior on e-commerce platforms using the Decision Tree algorithm as an easily interpretable classification method. The dataset used consists of 12,330 transaction records with 18 attributes representing visitor characteristics and user activities during interactions with the e-commerce platform. The research stages include data exploration to identify initial patterns, data preprocessing to handle missing values and class imbalance, splitting the data into training and testing sets, training the Decision Tree model, evaluating model performance, and visualizing the tree structure to analyze decision rules.The test results show that the Decision Tree model with a maximum depth of 3 achieves fairly good performance, with an average accuracy of 89.78%, precision of 69.82%, recall of 59.95%, and an F1-score of 64.51% for the buyer class. The visualization of the decision tree provides clear interpretation of the main attributes influencing purchasing decisions, thereby facilitating understanding for non-technical decision makers. Overall, this study demonstrates that the Decision Tree method is effective in modeling consumer purchasing behavior in e-commerce and can be utilized as a basis for data-driven business decision making, particularly in marketing strategies and improving sales conversion rates.

Rapid advances in digital technology bring various benefits and risks, including the threat of cybercrime, which can particularly affect Generation Alpha. The purpose of this seminar was to raise awareness and understanding among students at SMK Bina Patriot of the importance of protecting personal data on digital platforms. The seminar was attended by 62 participants who are active internet users in their daily lives. The seminar was conducted interactively through lectures, case studies, and training on steps to protect personal data, such as creating secure passwords and managing privacy on social media. The evaluation of the results showed a significant increase in participants' understanding, reaching an average of 97%. It is hoped that this will become a strong foundation of digital literacy for the younger generation in facing the challenges of the cyber world wisely and safely. This increased understanding is expected to be a strong foundation for Bina Patriot Vocational School students to develop their digital literacy, which in turn will help them to be able to face the challenges of the digital world wisely, safely, and responsibly.

Rapid advances in digital technology bring various benefits and risks, including the threat of cybercrime, which can particularly affect Generation Alpha. The purpose of this seminar was to raise awareness and understanding among students at SMK Bina Patriot of the importance of protecting personal data on digital platforms. The seminar was attended by 62 participants who are active internet users in their daily lives. The seminar was conducted interactively through lectures, case studies, and training on steps to protect personal data, such as creating secure passwords and managing privacy on social media. The evaluation of the results showed a significant increase in participants' understanding, reaching an average of 97%. It is hoped that this will become a strong foundation of digital literacy for the younger generation in facing the challenges of the cyber world wisely and safely. This increased understanding is expected to be a strong foundation for Bina Patriot Vocational School students to develop their digital literacy, which in turn will help them to be able to face the challenges of the digital world wisely, safely, and responsibly.

Public service in the transportation sector plays a strategic role in ensuring public safety and comfort, particularly through roadworthiness testing (Kir) for public transportation. This study aims to analyze the implementation of public services in roadworthiness testing at the Bandar Lampung City Transportation Agency and to identify the factors influencing its service quality. The research employs a qualitative approach, with data collected through interviews, observations, and documentation. The results indicate that the roadworthiness testing has been implemented systematically in accordance with statutory regulations, covering the stages of registration, technical inspection, result determination, and administrative completion. The application of technical inspections and on-field safety inspections (ramp checks) demonstrates the local government's commitment to improving public service quality and transportation safety. However, the implementation still faces several obstacles, including technological system disruptions, long waiting times, limited testing facilities and infrastructure, and a lack of understanding among some service users regarding the importance of roadworthiness. This study concludes that enhancing public services in roadworthiness testing requires strengthening the service systems, increasing human resource capacity, and raising public awareness to ensure services operate more effectively and remain oriented toward the public interest

The development of bioinformatics has led to the availability of large amounts of genetic data through public databases such as NCBI Gene, OMIM, and Ensembl. However, the complexity of data presentation and the dominance of English language hinder students, novice researchers, and the general public in understanding the relationship between genes and disease. This research aims to develop a simple web-based information system to identify disease-causing genes with concise, Indonesian-language, and user-friendly information presentation. The method used is Research and Development (R&D), which includes literature study, needs analysis, system design, implementation, testing, and evaluation. The system was developed using a MySQL relational database with a web interface that displays basic gene information, chromosome location, biological function, and gene-disease relationships, complete with simple visualizations. Black Box testing results indicate that all main functions run according to user requirements. This system is expected to improve bioinformatics literacy and become an effective learning medium.

The use of social media is no longer just for information and entertainment, but has developed into a strategic means in building a positive self-image in the eyes of the public. School students are generally active users of social media whose intensity of use is quite high in daily life. As a group of teenagers who are still in the phase of finding their identity and tend to be emotionally labile, they need the right education to be able to use social media wisely, productively, and responsibly. Community Service activities carried out for students of SMK Wiyata Satya are expected to increase understanding of the importance of personal branding from an early age. Through this activity, students are not only given socialization about the concept of personal branding and social media ethics, but also equipped with practical skills in compiling portfolios and fostering awareness of career planning and goal achievement. At the end of the activity, students presented their self-concept that had been prepared and responded through a questionnaire to evaluate the effectiveness of the entire series of activities.

The rapid development of Artificial Intelligence (AI) technology has opened significant opportunities to support maritime monitoring systems, particularly in detecting anomalies in ship movements that may indicate illegal or abnormal activities. However, the understanding and utilization of this technology among the general public and maritime stakeholders remain limited. This Community Service Program aims to conduct socialization and dissemination of knowledge on AI-based ship anomaly detection through the development and utilization of an interactive and informative web-based socialization platform. This activity is the result of collaboration between a team of lecturers from the Faculty of Communication and Informatics Technology (FTKI) and the National Research and Innovation Agency (BRIN). The implementation methods include the design of web-based educational content, presentation of fundamental AI concepts and ship anomaly detection, as well as visual simulations of ship movement data analysis results. The web-based socialization platform serves as an educational medium to enhance users’ understanding of the benefits, working mechanisms, and potential applications of AI technology in maritime surveillance. The results indicate an improvement in participants’ understanding of ship anomaly detection concepts and the role of artificial intelligence in supporting maritime security and safety. This PKM activity is expected to promote technological literacy, strengthen synergy between academia and research institutions, and serve as a model for practical and sustainable web-based technology socialization

The rapid development of generative Artificial Intelligence (AI) technology offers significant efficiency opportunities across various sectors; however, empirical research within the local Indonesian context, particularly in Batam City, remains scarce. This exploratory study aims to analyze the influence of positive perception, negative perception, and AI regulation understanding on technology adoption trends, as well as productivity and product innovation opportunities among creative industry players. The creative industry is a focal point due to the inherent tension between technological efficiency and the preservation of human originality in the creative process. This research employs a quantitative causal approach, utilizing a sample of 30 respondents reached through snowball sampling techniques. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The findings reveal that only positive perception has a significant direct impact on product innovation (p=0.004), while AI regulation and technical adoption do not show significant effects. This suggests that a positive technology mindset is a more decisive factor for innovation than technical mastery or current regulatory compliance. These results underscore the urgent need for local government socialization of AI policies and enhanced digital literacy for Batam's creative practitioners to transform them from mere users into strategic AI-driven innovators.

Instagram has become a strategic medium for government institutions in delivering public information, particularly weather and disaster-related information that requires speed, clarity, and ease of understanding. The BMKG of Gowa Regency utilizes digital communication innovations through the use of informative memes and a virtual character named Shinna as a visual communication strategy to enhance the effectiveness of information dissemination to the public. This study aims to analyze the influence of meme usage and the virtual character Shinna on the information satisfaction of Instagram users of BMKG Gowa Regency by employing the Stimulus–Response (S–R) theory perspective, which views visual messages as stimuli capable of eliciting cognitive and affective responses from audiences. This research adopts a quantitative approach using a survey method. Data were collected through an online questionnaire with a four-point Likert scale administered to followers of the BMKG Gowa Regency Instagram account who had viewed or interacted with meme content and the virtual character Shinna. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS software. The results indicate that the use of memes and the virtual character Shinna has a positive and significant effect on users’ information satisfaction, both partially and simultaneously. Meme usage shows a more dominant influence compared to the virtual character Shinna, while the coefficient of determination (R²) value of 0.834 indicates that both variables explain 83.4% of the variance in users’ information satisfaction. These findings confirm that public communication strategies based on memes and virtual characters are effective in enhancing audience understanding, comfort, and satisfaction with disaster-related information.

This community service activity was carried out to overcome the problem of open and uncontrolled internet networks at SMK Islamiyah Serua. This condition poses security risks as well as inefficient bandwidth usage. The solution offered is the implementation of a network gateway system with a user-friendly web-based login portal, so that internet access can be limited only to educators through an authentication mechanism. The implementation method includes needs analysis, system design, implementation using MikroTik RouterOS and HTML/CSS/JavaScript-based web portals, system trials, and socialization to schools. The results showed a significant improvement in network security, bandwidth usage efficiency, and ease of access for teachers. In addition, this activity also increases educators' understanding of the importance of network security in supporting the learning process. The implementation of this system provides sustainable benefits for schools, both from a technical and educational perspective, because it is able to create a safer and more controlled digital environment. Thus, this community service activity not only solves technical problems, but also contributes to improving the quality of educational services at SMK Islamiyah Serua.

User experience (UX) evaluation plays a crucial role in understanding how users interact with digital platforms and in improving product design. Traditional UX evaluation methods, such as surveys and interaction logs, often rely on a single data source, which limits the depth of analysis. This study explores the integration of multimodal data processing techniques in UX research, aiming to enhance the accuracy and comprehensiveness of UX evaluations. By combining interaction logs, visual attention data, and physiological measurements, this approach provides a more holistic understanding of user behavior, emotional responses, and satisfaction. Interaction logs offer objective data on user actions, while eye-tracking and physiological data capture users' emotional states, providing richer insights into usability and user experience. This study highlights the effectiveness of multimodal integration in identifying patterns that traditional methods overlook, such as emotional responses to interface elements and real-time feedback from users. The findings reveal that multimodal data processing improves the precision of UX assessment by combining objective behaviors with subjective emotional responses, offering a more complete view of user interactions. The study also discusses the challenges of data synchronization and the potential ethical concerns related to the use of physiological data. The integration of these data sources shows great potential for enhancing the design process, allowing designers to make informed decisions based on comprehensive insights. Finally, this research underscores the future potential of multimodal analytics in UX research, suggesting further exploration of additional data modalities and real-time applications in various digital environments.

The increasing volume and complexity of data have made traditional 2D visualization methods insufficient for effectively exploring and understanding high-dimensional datasets. Immersive Virtual Reality (VR) presents a promising solution by providing an interactive 3D environment that enhances spatial understanding, task efficiency, and user satisfaction. This research aims to evaluate the user experience (UX) and interaction design quality of immersive VR interfaces for 3D data visualization in complex environments. The study employs a mixed-methods approach, combining usability testing, UX questionnaires, and task-based performance analysis. Participants interacted with VR prototypes designed to visualize complex data and were assessed on their ability to manipulate and explore the data efficiently. The findings show that immersive VR interfaces significantly improve spatial comprehension, reduce cognitive load, and increase task performance efficiency compared to traditional 2D systems. Additionally, user satisfaction was notably high, with participants appreciating the intuitive and engaging interaction methods. The study concludes that immersive VR can provide substantial benefits in real-world data visualization applications, particularly in domains requiring the exploration of complex and high-dimensional data. However, further research is needed to optimize VR interfaces and address challenges such as motion sickness and interaction complexity.

This study was based on the low ability of third-grade students at SD Negeri 2 Wonorejo to understand syntactic material, particularly the use of conjunctions, due to a lack of interactive and contextual learning media. This study aimed to develop EKUJARSI E-Flipbook learning media based on Kudus local wisdom that has been tested for feasibility and practicality to improve student understanding. The research method used was Research and Development (R&D) with the ADDIE (Analyze, Design, Development, Implementation, Evaluation) development model. The test subjects included subject matter experts, media experts, classroom teachers, and third-grade students. Data collection instruments used validation sheets and user response questionnaires. The results showed that the EKUJARSI media was highly valid for use, as evidenced by a validation percentage of 89.6% from media experts and 86.15% from subject matter experts. The practicality test also showed positive responses, with teachers giving a score of 80% and students giving a score of 85.9%, which is considered very feasible. Specific findings show that the ease of use aspect received a perfect score of 100% from students, indicating that this media is very user-friendly. It is concluded that the EKUJARSI E-Flipbook is feasible and practical to be implemented as an innovative learning media that effectively integrates local cuisine to facilitate understanding of language concepts.

User reviews on the Shopee e-commerce platform represent an important source of information for understanding consumer perceptions of products and services. Sentiment analysis is commonly applied to classify user opinions into positive, neutral, and negative sentiment categories based on textual data. This study aims to analyze the performance of the Long Short-Term Memory (LSTM) method in sentiment classification of Shopee user reviews. The dataset used in this study consists of Indonesian-language user reviews that have undergone preprocessing stages, including case folding, text cleaning, tokenization, and stopword removal. The LSTM model was trained using preprocessed text represented as word sequences. Model performance was evaluated using overall accuracy and class-wise classification results. The experimental results indicate that the LSTM method achieved an overall accuracy of 87.62%. In addition, the classification performance for the positive sentiment class reached 95.27%, the neutral class achieved 4.96%, and the negative class reached 74.26%. These results demonstrate that the LSTM method performs well in classifying sentiment in Shopee user reviews, particularly for positive sentiment. This study is expected to provide insights and references for the application of deep learning methods in sentiment analysis of Indonesian e-commerce review data.

In the ever-evolving digital era, the importance of cyber law in safeguarding user privacy cannot be overstated. As a distinct legal discipline, cyber law examines regulations that oversee activities in cyberspace, offering legal protection regarding personal data and user privacy. Referring to various credible sources, this article evaluates the role of cyber law in protecting user privacy in the Indonesian context. The article discusses regulations such as the Electronic Information and Transactions Law (UU ITE), the Government Regulation on Electronic Systems, and the Personal Data Protection Bill. The main elements analyzed include supervision, regulation, resolution, and protection of user rights when facing digital security challenges. The examination shows that cyber law plays a significant role in protecting individuals' personal information, thereby encouraging safer and more trustworthy digital services. Furthermore, the article points out the various challenges faced in enforcing cyber law, such as administrative constraints, inadequate digital literacy, and limited access to justice, especially for those without legal knowledge or support. Consequently, to improve the effectiveness of cyber law, continued efforts are needed to strengthen the digital regulatory framework and provide more comprehensive user privacy protection. This perspective seeks to enhance understanding of the significance of cyber law in safeguarding privacy and proposes recommendations for governments and relevant organizations in addressing privacy issues in the digital age.

The rapid advancement of information technology has encouraged elementary schools to adopt digital systems for managing learning resources, including school libraries. SDN 15 Tangerang still applies a manual library management method, which leads to several issues such as poorly organized loan records, difficulties in locating book data, and low reading interest among students. This study aims to design and develop a digital library information system using the Human Centered Design (HCD) approach, which emphasizes user needs and comfort. The HCD method is implemented through four stages: understanding the context of use, identifying user needs, designing solutions, and evaluating the system. The findings indicate that the developed system improves the efficiency of library management, simplifies the book borrowing and return processes, and provides a better user experience for students and library staff. Therefore, the implementation of an HCD-based digital library information system is expected to support the improvement of literacy and reading interest among elementary school students.  

This study aims to analyze the role of internet technology in enhancing the competitiveness of ebusiness in Indonesia, particularly in the sector of small and medium enterprises (SMEs). Based on theoretical reviews, internet technology, e-business, technology adoption (TAM), and the concept of competitiveness serve as the main foundations for understanding the ongoing digital transformation. The research employed a descriptive qualitative method with a purposive sampling technique, involving five informants consisting of digital SME owners, online store managers, and users of service platforms. Data were collected through interviews and observations, then analyzed using the Miles and Huberman model through the stages of data reduction, data presentation, and conclusion drawing. The findings reveal that the internet plays a crucial role as an essential infrastructure that enhances marketing effectiveness, expands market reach, and improves operational efficiency. Marketplaces, social media, and delivery-service platforms contribute significantly to sales growth and service quality. However, challenges such as low digital literacy, platform commission fees, changes in social media algorithms, and uneven infrastructure development still limit optimal utilization. From a policy perspective, the study recommends strengthening digital infrastructure and improving national digital literacy. This research emphasizes that the success of e-business depends on technology access, human resource competence, and support through public policy. It can be concluded that internet technology serves as a vital foundation for e-business competitiveness in the digital era.

This study aims to develop an educational application based on a Graphical User Interface (GUI) using MATLAB App Designer that functions as an interactive simulation for evaluating blood pressure. The application allows users to input systolic and diastolic blood pressure values along with supporting information such as name and age. The input data are then analyzed and classified into several blood pressure categories according to the standards of the American Heart Association (AHA), including normal, hypotension, stage 1 hypertension, stage 2 hypertension, and hypertensive crisis. The classification results are presented visually through an interactive pie chart with dynamic percentages and legends to enhance user understanding. In addition, all data are automatically stored in a Microsoft Excel file containing a summary of blood pressure categories and session timestamps. The system is designed with a simple interface and intuitive interaction, making it suitable for early health education purposes. Although the application still relies on manual data input, it has the potential to serve as an effective learning tool for increasing public awareness of the importance of regular blood pressure monitoring. 

The use of Large Language Models (LLMs) in scientific research is becoming increasingly widespread, but presents epistemic risks that are not yet fully understood. This article discusses how the probabilistic mechanisms of LLM can produce outputs that appear correct and justified but are actually dependent on epistemic luck, thus resembling the Gettier case pattern. Through a conceptual study approach, this research clarifies concepts, analytically reconstructs the generative structure of LLM, and conducts a normative analysis of its implications for scientific accountability and authorship. The results of the analysis show that Algorithmic Gettier Cases (AGCs) occur when linguistic coherence deceives users and creates the impression of justification, even though the truth that emerges is statistical coincidence and is not supported by valid causal relationships. This condition poses a serious challenge to the attribution of knowledge and author responsibility in the production of academic texts. To address this issue, this article proposes the principle of Hyper-Justification Obligation, which is the ethical obligation for researchers to actively verify and causally reason every AI output before using it in scientific works. This research provides a theoretical contribution to understanding the epistemic risks of LLM and offers an ethical foundation for academic practice in the era of generative AI.

The Motor Operated Valve (MOV) is a critical component in fluid control systems at Steam Power Plants (PLTU). Training new technicians is often hindered by limited access to actual equipment and operational safety risks. This research aims to design and develop an Arduino-based MOV control module simulator capable of simulating basic functions such as open, close, stop, and limit switch responses. The method used is Research and Development (R&D) with an experimental approach. The simulator was tested using a DC motor as the simulated valve actuator, equipped with push buttons, relays, limit switches, and indicator lamps for visual feedback. The test results showed that the simulator successfully represented control functions with 100% accuracy in limit switch responses and consistent operation. User evaluations involving ten new technicians indicated an 85% satisfaction rate in terms of ease of understanding and operational safety. This simulator has proven to be an effective, interactive, and safe learning medium for new technicians at PLTU Nagan Raya.