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Palgunadi Selatan Village, RT 07/RW 05, Bulu Lor Subdistrict, North Semarang, possesses distinctive local potential in the form of community-based grape cultivation. However, this potential has not yet been systematically integrated into spatial and environmental planning at the neighborhood scale. This community service program aims to identify local potential and environmental constraints, formulate a design concept for a grape-based thematic village, and strengthen collaboration between residents, universities, and local stakeholders. The implementation method employs field observation, identification of potential and problems, environmental analysis, participatory discussions with the  community, and formulation of a spatial design concept. The results of the program are presented in the form of a conceptual design for the Grape-Based Thematic Village along Palgunadi Selatan Street, which includes gateway elements, pedestrian pathways, communal seating areas, pergola systems for grape cultivation, neighborhood bridges, vertical planting systems, and security posts. This design concept enhances environmental quality, strengthens the visual identity of the neighborhood, and creates opportunities for community-based economic activities and educational tourism. Furthermore, the program contributes to increased community awareness and participation in environmentally responsive and locally based neighborhood development, supporting the realization of a more organized, attractive, productive, and sustainable urban settlement.

The digital era continues to evolve and bring innovation and change to various industries. Through digital transformation and strategies needed to overcome obstacles in the digital era, organizations can adapt and change. To achieve their goals, MSMEs must implement efficient marketing techniques in their operations. This community service method uses the PAR (Participatory Action Research) technique. This is in line with the conditions of the partner, Dwikora Village, which has human resources that are well known to both village officials and residents. The results found that due to a lack of understanding of digital marketing communication management procedures, they were unfamiliar with digital marketing techniques, different social media platforms, or how to measure their effectiveness. The Community Service Team conveyed their understanding of the importance of digital marketing communication in improving the knowledge and skills of residents as an effort to improve their marketing communication skills. This was because many residents, especially mothers, did not understand how to use digital marketing to promote their MSMEs. The team formed a content creation team or digital marketing communication managers, socialized the value of digital marketing communication to the sub-district residents in improving their knowledge and skills, and implemented a digital marketing communication message management strategy on Instagram. After these activities, partners can create interesting and relevant content that suits the interests of the target audience in Dwikora Village, namely its residents.

Permanent tooth loss is a common oral health problem experienced by patients. This condition can be caused by pathological conditions such as tooth decay, leading to tooth extraction. Rehabilitation treatment for partial posterior tooth loss aims to restore masticatory function, maintain occlusal relationships and periodontal health, and improve aesthetics. A 34-year-old man came with a complaint that his lower right posterior tooth had been extracted and wanted a permanent dentures to replace his missing tooth. The intraoral and periapical radiograph examination revealed that 46 was missing, and 47 had enamel caries. The diagnosis for 46 was determined to be partial edentulous. The treatment plan was a PFM fixed-fixed bridge with a sanitary pontic for 46, a rigid connector, and a full crown retainer for 45 and 47. In this case, the choice of PFM bridge is based on several considerations, i.e., high chewing loads, relatively low cost, and high long-term success. The PFM bridge has been the primary choice for posterior tooth rehabilitation, due to its durability and cost-effectiveness.

Formalin is a hazardous chemical that is banned from use in food, but is still found in imported fruit. Traders have an important role in preventing the circulation of food with formaldehyde, so the knowledge of traders about the dangers of formaldehyde needs to be studied. Objective: This study aims to determine the knowledge of traders and formalin content in imported fruit sold in X Market, Palembang City in 2025. Methods: This study used a quantitative approach with a descriptive design. The population in this study were all imported fruit traders in X Market totaling 9 people who served as respondents. The fruit samples tested were 24 samples consisting of apples, pears, and grapes. Data were collected through questionnaires and laboratory tests using formalin test kit. Results: The results showed that all traders (100%) had a good level of knowledge about formalin. Of the 24 fruit samples tested, 21 samples (87.5%) did not contain formalin and 3 samples (12.5%) showed positive results, all of which were from grapes. Conclusion: The majority of traders had good knowledge about formaldehyde, but formaldehyde was still found in some imported fruits, especially grapes.

This community service program focuses on the theme of creative economy with the aim of encouraging innovation in agricultural products to increase added value and income for Micro, Small, and Medium Enterprises (MSMEs) in Sumber Urip Village, Selupu Rejang District, Rejang Lebong Regency. Although the village has abundant agricultural potential, local products have not been optimally developed due to limited knowledge in processing, packaging, and marketing. The program employed a participatory-educative approach that emphasized active community involvement at every stage, including potential identification, socialization of creative economy concepts, product innovation training, and practical assistance in packaging and marketing. The participants consisted of farmers, MSME actors, and the Bukit Kaba Tourism Awareness Group (Pokdarwis) as strategic partners in developing a tourism-based market. The results indicate that the implementation of creative economy principles improved community understanding of product innovation, hygienic and value-added packaging, and appropriate marketing strategies targeting Bukit Kaba visitors. The strategic selling location at the Bukit Kaba tourism post further enhanced product visibility and market reach. Overall, this program demonstrates that creative economy-based community assistance can effectively strengthen MSME competitiveness, increase household income, and promote sustainable integration between agriculture, local entrepreneurship, and rural tourism development.

Community Service Program (KKN) is an implementation of the Tridharma of Higher Education aimed at dedicating knowledge and technology to society. This article analyzes the implementation of the KKN program by students of Universitas Trunodjoyo Madura Group 30 in Buddagan Village, Pademawu District, Pamekasan Regency, focusing on community empowerment through aspects of environment, education, entrepreneurship, and village digitalization. The activities were carried out using a participatory approach with observation techniques, interviews, and discussions with the community and village stakeholders. The flagship programs include the socialization of used cooking oil for making aromatherapy candles, installation of environmental education plaques, anti-bullying socialization at SDN Buddagan 2, and the creation of the official social media for Buddagan Village. The results show an increase in community awareness, especially among PKK mothers, regarding the health and environmental dangers of used cooking oil and the potential for a creative economy based on domestic waste. The anti-bullying program successfully instilled empathy and mutual respect values in students, while the village digitalization strengthened public access to information and a positive village image. The KKN program in Buddagan Village has had a positive impact on social behavior changes in the community and serves as a model for sustainable community service.

Hospitalization often triggers anxiety in children because of unfamiliar environments, invasive procedures, and disruption of daily routines. Pediatric nurses are expected to implement atraumatic care through developmentally appropriate, non‑pharmacological interventions. This community service program aimed to strengthen nurses’ and families’ skills in delivering puzzle‑based play therapy and to evaluate short‑term changes in children’s anxiety responses in the pediatric ward of Awal Bros Hospital, Batam. The program was conducted in December 2025 using an action-based approach: coordination with the ward team, preparation of graded puzzle sets and education media, bedside education for parents, and supervised play sessions. Four hospitalized children with different diagnoses (chemotherapy, childhood‑onset lupus erythematosus, febrile illness, and stoma care) participated. Anxiety was assessed before and after the session using an observation sheet and a faces anxiety scale adapted for clinical use. After a 20–30 minute session adjusted to the child’s developmental stage, all participants demonstrated lower anxiety scores and better cooperative behaviors. Caregivers also reported increased understanding of play therapy as part of holistic nursing care. Puzzle play therapy is feasible, low‑cost, and can be integrated into routine pediatric nursing to support coping during hospitalization.

This study describes the implementation of Field Work Lectures (KKL) in Muara Wahau Village, focusing on religious education, youth character building, and community economic and social empowerment. KKL students were directly involved in teaching at the TPQ (Islamic Religious Education Center), tutoring for elementary and kindergarten students, leadership development in junior and senior high schools, mentoring MSMEs, community service activities, group exercise, and family health data collection. Data were obtained through observation, interviews, and documentation, then analyzed thematically. The results showed that the KKL successfully improved the youth's Quran reading skills, understanding of religious values, discipline, leadership, and social awareness. Furthermore, economic and social empowerment through MSME mentoring and community activities strengthened community independence and synergy. Obstacles such as high rainfall and the absence of the village head were successfully overcome through intensive coordination and adjustments to the activity schedule. The KKL proved effective as a practical learning tool for students while also having a positive impact on the community.

This study aims to analyze the need for barges and tugboats in distributing Crude Palm Oil (CPO) in the West Papua region. The analysis is conducted based on three main aspects: the balance of supply and demand, ship operational costs, and shipping time, to determine the most efficient mode of sea transportation. The research method used is a quantitative approach by processing CPO distribution data owned by PT Kurhanz Trans in 2024. The results show that the combination of a 240-foot barge with a 5,000 HP tugboat is the most optimal alternative. This combination is able to balance cargo capacity, operational cost efficiency, and shipping time. The total operating cost of a 240-foot barge is recorded as lower than a 230-foot barge, with the same shipping time of 70 hours for a distance of 140 nautical miles. Thus, the 240-foot barge can be recommended as the best alternative to support the smooth distribution of CPO in the West Papua region efficiently and economically.    

This study aims to describe the implementation of smart government through the Sumbergedang Baru Program in Sumbergedang Village, Pandaan District, Pasuruan Regency. The program is a digital village initiative that utilizes information technology to improve the quality of public services, transparency of governance, and the social and economic empowerment of rural communities. This study employed a descriptive qualitative approach with purposively selected informants, including the village head, village officials, community groups (Pokmas GPS and G4S), and residents as service recipients. The findings show that digital literacy among the community and village officials has begun to develop, as indicated by their ability to use basic devices and applications; however, the utilization of village digital services remains limited and uneven across age groups. In terms of ICT accessibility, the village has established an internet network and public Wi-Fi hotspots, yet network coverage and stability have not fully reached all hamlets. Regarding regulations, the village government has established basic policies through decrees forming community groups and regulating the digital village program, although these have not been comprehensively integrated. In terms of human resource quality, village officials and young cadres are relatively adaptive to technology, but a capacity gap remains among older age groups. Overall, the implementation of smart government through the Sumbergedang Baru Program is still at the stage of building a digital village foundation, requiring further improvements in digital literacy, human resources, infrastructure expansion, and technology-based transparency.

Infant massage is an early stimulation method that plays a role in increasing infant weight gain, sleep quality, and comfort. However, limited parental resources and access to healthcare facilities prevent massage services from being optimally implemented. This community service activity aims to improve infant health through homecare-based infant massage services that are easily accessible to families. The activity was conducted on June 22, 2025, in Bulukumba Regency, targeting five infants aged 2–5 months. The activity methods included: (1) initial weight measurement, (2) education on correct massage techniques, (3) massage using olive oil for 15–20 minutes, and (4) monitoring infant sleep patterns and comfort. Repeat measurements were conducted after the intervention. Results showed post-intervention weight gain in all infants, improved sleep patterns (infants fell asleep more easily and slept longer), and increased appetite. Mothers also demonstrated improved self-massage skills. In conclusion, homecare-based infant massage has been proven effective in improving infant comfort, sleep patterns, and weight gain. This program is worthy of continuation and expansion to support community midwifery services

This community service program is entitled Improving Microcontroller Competence of Students of SMK Negeri 3 Pematangsiantar through Arduino Training Based on Industrial Practice and is implemented as a follow-up to the school's official request to invite university practitioners as guest teachers in order to strengthen industry-based vocational learning. The activity was carried out on November 27, 2025 at the Computer Laboratory of SMK Negeri 3 Pematangsiantar involving 50 grade XI students, and guided by Andi Setiadi Manalu, S.Kom., M.Ti as the main instructor of Arduino material which focuses on the introduction of microcontrollers, basic programming, sensor integration, and simple automation project design. The purpose of this activity is to improve students' technical competence in the field of embedded systems while fostering work readiness through real-world practice-based learning experiences. The implementation method uses an experiential learning and project-based learning approach, which combines brief conceptual explanations with direct practice, technical discussions, and problem-based project assignment completion. The evaluation results show an increase in students' understanding of microcontroller functions, programming logic structures, and the ability to connect hardware and software in one work system. In addition, students demonstrated increased motivation, confidence, and interest in industrial technology, as reflected in their active participation during the practicum and their successful independent completion of functional prototypes. Overall, this activity proved effective in strengthening the technical competencies of vocational high school students and supporting the implementation of the link and match policy between vocational education and the needs of the industrial world, while also emphasizing the strategic role of higher education institutions in supporting the improvement of human resource quality at the vocational high school level.

This study critically examines the emerging phenomenon of celebrity preachers as a significant form of religious commodification within the realm of digital da’wah. The rapid proliferation of social media has fundamentally transformed how religious messages are disseminated, with platforms like YouTube, Instagram, and TikTok becoming primary channels. Utilizing a quantitative methodology that combines comprehensive literature studies with online questionnaires distributed to social media users, this research investigates public perceptions regarding digital da’wah practices and high-profile preachers. The findings reveal a commodification process characterized by three key aspects: the tailoring of content to suit market preferences, the shift of audiences into active consumers, and the strategic construction of public images by preachers to sustain popularity. While respondents value the accessibility of digital da’wah, they strongly emphasize the necessity of ethical boundaries to preserve its spiritual essence. Consequently, digital da’wah requires sincerity, scholarly integrity, and moral responsibility to remain an authentic medium for Islamic teachings.

Graph theory as a branch of discrete mathematics has experienced significant development in its application to modern complex network systems, particularly in digital social networks and transportation systems. This research aims to analyze fundamental concepts of graph theory, examine characteristics of cycle detection algorithms along with their computational complexity, investigate their application in digital social network analysis, and explore their implementation in digital transportation system optimization. The research method employs a qualitative approach with library research focusing on scientific literature from 2020-2025 period from accredited academic databases such as Scopus, Web of Science, and IEEE Xplore, utilizing thematic analysis techniques to identify meaningful patterns from the examined literature. Research findings indicate that fundamental graph theory concepts including vertices, edges, and graph classifications form the foundation for relational structure modeling. Cycle detection algorithms such as Depth-First Search, Union-Find, and Tarjan demonstrate effectiveness with O(V+E) complexity for large-scale graphs. Applications in digital social networks facilitate community identification through Multi-View Clustering, centrality analysis for influencer detection, and understanding viral information dissemination patterns. Implementation in digital transportation systems demonstrates route planning optimization using Dijkstra and Bellman-Ford algorithms, vulnerability analysis through articulation point and bridge identification, and bottleneck detection with betweenness centrality. The research concludes that integration of graph theory in discrete mathematics education enhances critical thinking skills and real-world application understanding, with recommendations for algorithm development for massive dynamic graphs and machine learning integration in graph algorithm optimization.

The creative economy industry serves as a strategic pillar of the national economy, experiencing significant transformation in the digital era. This study aims to comprehensively analyze the pattern of human resource (HR) competency gaps within priority subsectors of Indonesia's creative economy and formulate effective, multi-stakeholder development strategies. Employing a Systematic Literature Review (SLR) methodology, this research rigorously analyzes 30 scientific journal articles, government reports, and publications from global institutions published between 2014 and 2024. The findings delineate three primary clusters of competency gaps: (1) The Digital-Technical Competency Gap, encompassing deficiencies in data analytics, specialized software mastery, and digital content creation tools; (2) The Digital-Business Competency Gap, which includes shortcomings in digital financial literacy, online business model development, and management of digital intellectual property rights; and (3) The Social-Cognitive Competency Gap, highlighting needs in adaptability, complex problem-solving, and effective virtual collaboration. In response, this paper proposes an integrative strategic framework grounded in a collaborative multi-stakeholder approach. Key recommendations include revitalizing educational curricula through industry-embedded learning and micro-credential integration, developing agile and accessible training ecosystems featuring bootcamps and digital platforms, and fostering supportive policies through fiscal incentives and the alignment of national qualification frameworks with digital skill standards. The successful implementation of this synergistic strategy is expected to significantly enhance the adaptability, innovation capacity, and global competitiveness of Indonesia's creative workforce, thereby ensuring the sustainable growth of the creative economy sector in the face of rapid digital disruption.

This study explores the integration of adaptive streaming models with edge computing to optimize multimedia delivery, particularly in real-time applications such as video conferencing, live streaming, and virtual reality. The proposed model leverages adaptive compression techniques, including scalable video coding (SVC) and hybrid adaptive compression (HAC), which adjust video quality based on real-time network conditions. The use of edge computing further enhances the model by processing and delivering content closer to the user, reducing latency and optimizing bandwidth usage. The research demonstrates that the edge computing-based adaptive streaming model significantly improves latency by up to 30%, reduces bandwidth consumption, and ensures higher visual quality during video playback, even under fluctuating network conditions. This model addresses key challenges in multimedia streaming, such as maintaining video quality in bandwidth-constrained environments and minimizing buffering times. Furthermore, it enhances the overall Quality of Experience (QoE) for users by providing smoother interactions and real-time responsiveness. The study highlights the potential impact of this model on various fields, including remote education, entertainment, and interactive applications, where low-latency content delivery and high-quality streaming are critical. The findings suggest that integrating AI algorithms for even more efficient compression and expanding edge computing infrastructures will further optimize multimedia streaming in the future, ensuring reliable and high-quality user experiences in increasingly connected environments.

Real time decision making applications, such as those used in autonomous vehicles, smart cities, and industrial IoT, require fast, scalable, and accurate analytics to ensure timely responses and optimized operations. Traditional cloud-based systems face significant challenges in meeting these requirements due to high latency, limited scalability, and bottlenecks in data processing. This study explores the use of a hybrid Edge Cloud architecture to optimize End to end machine learning (ML) pipelines for real time applications. The proposed system offloads time-sensitive tasks to edge devices, while computationally intensive processes are handled by the cloud, ensuring efficient use of resources and reduced latency. Experimental results demonstrate that the hybrid model reduces inference latency by up to 70% compared to cloud-only systems, while maintaining model accuracy and increasing throughput. Additionally, the scalability of the hybrid architecture is highlighted, as it can handle large-scale data streams and adapt to varying workloads. The findings show that hybrid Edge Cloud architectures are well-suited for applications where fast decision making is critical, such as autonomous systems and real time analytics in smart cities. However, challenges remain in managing resources across edge and cloud systems, particularly in balancing computational loads and ensuring system reliability. Future research should focus on optimizing task partitioning, integrating advanced edge AI models, and exploring the use of 5G networks to enhance performance further. Overall, the study demonstrates the potential of hybrid Edge Cloud systems in overcoming the limitations of traditional cloud-based ML pipelines and provides insights into the future of real time data processing.

Autonomous decision-making systems increasingly rely on complex artificial intelligence models to operate in dynamic and safety-critical environments. While these models provide strong predictive capabilities, their black-box nature limits transparency, trust, and accountability. This study proposes a structured research methodology for integrating Explainable Artificial Intelligence (XAI) into autonomous decision-making systems. The research adopts a conceptual–analytical approach to develop an explainability-oriented framework that embeds transparency across perception, decision-making, and action execution stages. The methodology includes literature-driven problem identification, conceptual framework construction, classification and mapping of XAI methods, and formulation of explainability evaluation criteria. The results demonstrate that effective explainability in autonomous systems requires a hybrid integration strategy, combining in-model transparency with post-hoc explanation mechanisms. A structured mapping of XAI techniques to autonomous system components and a conceptual decision-flow diagram are presented to illustrate explainability integration. The findings highlight that layered and context-aware explainability enhances system interpretability, supports human oversight, and improves safety relevance without compromising autonomous operation. This study contributes a reusable methodological foundation for the design and evaluation of explainable autonomous systems, offering practical guidance for future empirical validation and real-world deployment in safety-critical applications.

Human–Robot Interaction (HRI) systems increasingly rely on data-driven approaches to interpret multimodal sensory inputs and support natural interaction. However, purely neural-based HRI models often suffer from limited interpretability and insufficient context-aware decision-making, which can reduce user trust and adaptability in dynamic interaction scenarios. To address these limitations, this study proposes a hybrid neural–symbolic HRI framework that integrates multimodal neural perception with explicit symbolic reasoning for adaptive and interpretable robot behavior. The proposed system combines deep neural networks for processing visual, speech, and gesture inputs with a rule-based symbolic reasoning layer that models interaction context, user states, and behavioral constraints. A loosely coupled integration strategy enables neural outputs to be transformed into symbolic representations, allowing logical inference to guide action selection while preserving perceptual accuracy. The framework was evaluated through controlled HRI experiments comparing a neural-only baseline with the proposed hybrid configuration across multiple interaction scenarios. Experimental results demonstrate that the hybrid neural–symbolic system significantly improves interaction accuracy, contextual responsiveness, and user satisfaction, while achieving substantial gains in interpretability. These findings indicate that symbolic reasoning effectively complements neural perception by enhancing transparency and context-aware adaptation without compromising performance. The study concludes that hybrid neural–symbolic architectures provide a promising foundation for developing trustworthy, adaptive, and human-centered HRI systems.

This study compares the scalability and maintainability of three prominent programming paradigms-functional programming (FP), object-oriented programming (OOP), and declarative programming (DP)-in the context of distributed data processing systems. The research aims to evaluate how each paradigm performs under increased data volume and its ability to handle complex operations, while also assessing the ease of maintenance through code readability, modularity, and the flexibility of updating and debugging. The study employs a comparative experimental design, implementing identical data processing tasks, such as data aggregation, filtering, and transformation, across each paradigm. Key findings indicate that FP and DP outperform OOP in terms of scalability, with their stateless nature and high-level abstractions enabling efficient parallel processing and task distribution. FP, with its emphasis on immutability and concurrency, and DP, with its focus on describing desired outcomes rather than implementation specifics, both demonstrate superior performance in handling large datasets. However, while OOP excels in modularity and flexibility, its reliance on mutable state and shared resources hampers its scalability in distributed environments. In terms of maintainability, both FP and DP offer clearer, more maintainable code due to their abstraction levels, making them easier to update and extend. OOP, while modular, presents challenges in managing mutable state, complicating maintenance. This paper concludes with practical recommendations for developers on when to use each paradigm based on system requirements and suggests areas for future research, such as hybrid paradigms and long-term maintainability studies in real-world applications.