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Postoperative pain is a prevalent condition encountered by patients after surgical interventions and may negatively influence physical recovery as well as psychological well-being when inadequately managed. Conventional pain management strategies that primarily depend on pharmacological agents may lead to undesirable side effects, thereby emphasizing the importance of complementary non-pharmacological approaches. One intervention increasingly applied in nursing care is guided imagery. This review aimed to systematically evaluate the effectiveness of guided imagery in alleviating pain intensity among postoperative patients. A scoping review methodology was employed, with article identification guided by the PICO framework across national and international academic databases. Eligible studies included full-text research articles published within the past five years, written in either Indonesian or English, and specifically examining the use of guided imagery in postoperative settings. A total of ten studies met the inclusion criteria and were subjected to in-depth analysis. The results consistently demonstrated a significant reduction in pain intensity following the implementation of guided imagery across various surgical procedures, including cesarean delivery, appendectomy, fracture surgery, cholelithiasis, and abdominal operations. The intervention, delivered for 10–20 minutes per session, effectively reduced pain levels from moderate to severe to mild, with statistically significant outcomes (p < 0.05). Moreover, guided imagery was found to enhance patient relaxation, comfort, and psychological stability. These findings indicate that guided imagery represents a safe and effective non-pharmacological nursing intervention that can be integrated into evidence-based postoperative pain management.  

This study aims to analyze the inventory management practices of qurban cattle at Purnomo Sapi Mulyo Farm in Boyolali, Central Java, particularly in facing the surge in demand prior to Eid al-Adha. The research is motivated by the unique characteristics of qurban cattle inventory, which involves living assets, seasonal demand, and biological risks that differ significantly from conventional inventory management. A qualitative descriptive approach with a case study design was employed to capture in-depth information regarding inventory planning, procurement, storage, and sales practices. Data were collected through in-depth interviews with the business owner as the key informant, direct observation of operational activities, and documentation review. The findings reveal that inventory management at the farm is conducted in a responsive manner based on consumer orders, enabling the business to minimize overstock risks and operational costs. However, inventory recording remains manual and unstructured, potentially limiting the accuracy of cost calculation and long-term planning. Price fluctuations and supply availability are strongly influenced by the Eid al-Adha momentum, while cattle health and lead time are critical factors affecting inventory effectiveness. From a theoretical perspective, the study extends inventory management concepts to the context of live and seasonal inventory. Practically, the findings suggest that implementing a simple yet structured inventory recording system could enhance operational efficiency and decision-making accuracy in local qurban cattle farms.

The era of globalization and the rapid advancement of information technology have transformed the landscape of dakwah (Islamic propagation), shifting from conventional pulpits to virtual communication platforms (social media, podcasts, streaming). This transition, in line with the Diffusion of Innovation Theory, enables Islamic messages to reach a broad audience without geographical boundaries. Digital dakwah is highly relevant and urgent to research given the dominant use of social media by Muslim Youth, a group that seeks attention but also possesses a tendency toward critical thinking. This research has a dual aim: (1) to analyze the Interpretation of Muslim Youth towards virtual dakwah studies, and (2) to analyze the Effectiveness of Implementing Dakwah Studies through social media platforms. The accessibility of fragmented and competitive content makes the interpretation process active and crucial, where youth are no longer passive recipients but choose sources based on algorithms and their own interests. This study uses the Constructivism Paradigm to understand a dynamic and complex social reality, employing a Descriptive Qualitative Approach and the Online Ethnography Method. Data is collected through Observation, Interviews, and Documentation, with Data Triangulation (source, technique, and time) to ensure the validity of the findings. Social media holds great potential as an effective and inclusive dakwah tool. However, the effectiveness of its expansion must be balanced with the quality of the content and the capacity of Muslim Youth to perform critical, contextual, and responsible interpretation.

The process of determining eligibility for social assistance recipients is often constrained by subjective assessments and uncertainty in decision-making criteria. This condition can lead to inaccurate targeting and unfair distribution of aid. Therefore, an appropriate decision support method is required to handle data uncertainty effectively. This study aims to apply the Fuzzy Mamdani method to determine the eligibility of social assistance recipients based on several assessment criteria. The criteria used in this study include monthly income, number of dependents, and housing conditions. The research method consists of data collection, fuzzification, formulation of fuzzy rules, inference using the Mamdani approach, and defuzzification to obtain a crisp output value. The results show that the Fuzzy Mamdani method is able to classify recipients into eligible and non-eligible categories more flexibly compared to conventional methods. The generated eligibility values reflect real conditions more accurately by considering degrees of membership for each criterion. The implementation of this method can assist decision-makers in improving the accuracy, objectivity, and fairness of social assistance distribution. This research is expected to contribute to the development of intelligent decision support systems in the social welfare sector.

The process of determining scholarship eligibility often faces challenges related to subjectivity and uncertainty in assessment criteria, which can result in inaccurate and unfair decisions. Scholarship selection generally involves multiple criteria, such as academic achievement, family economic conditions, and supporting factors that are difficult to evaluate using conventional decision-making methods. Therefore, an appropriate decision support approach is required to handle such uncertainty effectively. This study aims to implement the Fuzzy Mamdani method in a decision support system to determine scholarship eligibility more objectively and accurately. The research method consists of data collection, fuzzification of input variables, formulation of fuzzy rules, inference using the Mamdani approach, and defuzzification using the centroid method to obtain a crisp eligibility value. The results show that the Fuzzy Mamdani method is capable of producing flexible eligibility scores by considering the degree of membership of each criterion. The generated output reflects real conditions more comprehensively compared to traditional methods. The implementation of this method can assist decision-makers in improving transparency, consistency, and fairness in scholarship selection. This research is expected to contribute to the development of intelligent decision support systems in the field of educational assessment.

This research is motivated by the use of conventional learning models that still dominate Indonesian language learning at the high school level, causing learning to become monotonous and less actively involving students. This study aims to determine the effectiveness of implementing the Quizizz-based Game Based Learning (GBL) model in improving learning outcomes, motivation, and participation of grade XII Social Science students at SMA BIMA Ambulu. The research method used is quantitative experimental with a one-group design (one-group pretest-posttest design). Research subjects consisted of 70 students divided into two classes, namely XII IPS 2 and XII IPS 5, with 35 students each. Data were collected through tests (pretest and posttest), learning motivation questionnaires using a 5-level Likert scale, student activity observation sheets, and documentation of learning activities. Research instruments have been tested for validity using Pearson Product Moment correlation and reliability using Cronbach's Alpha. Data analysis included validity tests, reliability tests, normality tests, and hypothesis testing using Independent Sample t-Test. The research results show that all test items are declared valid (r calculated > r table 0.334) and the instrument is reliable with a Cronbach's Alpha value of 0.812. The average N-Gain for class XII IPS 2 is 0.668 and class XII IPS 5 is 0.679, both in the medium-high category indicating the effectiveness of the GBL model. The t-test results show no significant difference between the two classes (mean difference 0.011), indicating consistency in the effectiveness of the GBL model in both groups. This study concludes that the Quizizz-based Game Based Learning model is proven effective in improving Indonesian language learning outcomes for grade XII Social Science students at SMA BIMA Ambulu. The implementation of GBL creates more interactive, enjoyable, healthy competitive learning, and is able to increase motivation and active student participation in learning.

Mathematics is a core subject that develops critical thinking skills; however, many third to fifth-grade elementary school students face difficulties with conventional teaching methods that tend to be uniform and less adaptive. This study aims to develop and implement a mobile-based educational game, "Ethno Run," which integrates the Bayesian Knowledge Tracing (BKT) algorithm to provide an adaptive learning experience. The method used is Research and Development (R&D) with the Multimedia Development Life Cycle (MDLC) framework. The system uses BKT to track students' mastery in real-time by analyzing their responses to pre-tests and exercises within the game, which then adjusts the difficulty level and focuses the post-test on areas identified as weak, such as arithmetic operations and geometry. The findings show that this adaptive approach significantly improves learning outcomes, with the average score increasing from 44.33 on the pre-test to 85.33 on the post-test among 30 students. This study concludes that the integration of Artificial Intelligence through BKT effectively personalizes learning, enhances student motivation, and provides data-driven insights for teachers regarding students' progress. The implication of this research is that adaptive game-based learning serves as a feasible interactive solution to bridge the gap in conventional basic mathematics education.

This study aims to analyze the development of elementary school students (ages 8–9) in terms of physical, cognitive, emotional, social, moral, and spiritual aspects. The research subjects were two third-grade students named Dinul Mumtaz (8 years old) and Alfatir Ramadhan Hendri (9 years old). This study used a qualitative approach, with observation and interviews as the main data collection techniques. The results indicate that both students show physical development appropriate for their age, with well-developed fine and gross motor skills. In the cognitive aspect, both have reached the concrete operational stage, characterized by logical thinking, understanding of cause-and-effect relationships, and the ability to solve tasks using concrete objects. In terms of emotional and social development, Dinul and Alfatir demonstrate the ability to recognize and manage emotions, as well as build positive social relationships with peers and teachers. Moral development shows that both students are in the heteronomous and early conventional stages, where they obey rules due to authority and a desire to gain social approval. Meanwhile, in the spiritual aspect, both students demonstrate good religious habits and an understanding of spiritual values reflected in their daily behavior. Therefore, it can be concluded that the development of both students is in a good category and in accordance with child development theories, supported by positive influences from family and school environments.

API abuse on lightweight edge gateways has intensified as microservice-based services expose many REST endpoints to heterogeneous clients. Conventional per-identity rate limiting, such as static token buckets, is frequently bypassed through distributed bots and identity rotation, while legitimate burst traffic may be rejected and degrade user experience. This study proposes Adaptive Rate Limiting with Verifiable Delay Functions (ARL-VDF), which couples a lightweight risk score with selective VDF challenges to impose a tunable sequential-computation cost on suspicious clients without forcing aggressive dropping for low-risk users. The gateway continuously derives a per-identity risk score from short-window request rate, error tendency, and identity freshness, then maps the score to a target delay bounded by  and . Evaluation uses a 600-second discrete-event simulation on a mixed workload consisting of normal clients, legitimate bursts, and distributed attackers. Compared with a static token bucket baseline, ARL-VDF maintains full success for legitimate traffic, reduces attacker throughput that passes the gateway, and keeps verification overhead within a fixed budget on the edge device. The results indicate that combining adaptive control with verifiable sequential cost can improve availability and fairness on resource-constrained edge gateways without resorting to aggressive dropping.

Administration is an activity that must be managed effectively to support public service quality, and one of the main keys to achieving a good administrative system is the utilization of information technology, which is currently developing rapidly. Administrative activities at the Wendewa Barat village hall are still carried out using conventional and ineffective methods, particularly in population data recording, which relies on manual bookkeeping. This approach is time-consuming, labor-intensive, prone to errors, and incurs higher operational costs. Therefore, an integrated system is needed to manage administrative activities more efficiently, accurately, and systematically. This research aims to develop a web-based population administration system to improve administrative performance at the Wendewa Barat village office. The system development employs the waterfall method, which consists of several stages, including requirements analysis, system design, implementation, system testing, and maintenance. The system is built using the PHP programming language with the CodeIgniter framework and utilizes a MySQL database for data management. Additionally, jQuery is applied in several system functions to enhance system interactivity, effectiveness, and user interface attractiveness.

This study examines the semantic aspects of the poetry anthology Penyair Tanpa Bait by Ahmad Zayn, a contemporary poetic work characterized by free structure and the absence of conventional stanzas. The background of this research is rooted in the need to understand how meaning is constructed in modern poetry that departs from traditional poetic forms. The objective of this study is to describe and analyze lexical, grammatical, and referential meanings contained in the poems in order to reveal their overall semantic structure. This research employs a qualitative descriptive method with a semantic analysis approach. The data consist of words, phrases, and poetic lines selected from the anthology, which are analyzed through stages of data identification, classification, and interpretation of meaning. The findings indicate that the poems predominantly utilize lexical meanings as the foundation of interpretation, while grammatical structures and referential meanings function to strengthen symbolic and contextual meanings. The absence of stanza divisions encourages a continuous flow of meaning that emphasizes semantic cohesion rather than formal structure. The implications of this study contribute to the field of linguistic and literary studies by enriching semantic analysis of contemporary Indonesian poetry and providing a framework for interpreting non-conventional poetic texts.

The waste problem in Karanglewas Village, Kutasari District, Purbalingga Regency, continues to increase alongside agricultural, trade, and MSME activities, while the management system remains conventional, without sorting, resulting in environmental pollution and limited landfill capacity. This community service program aims to implement the Integrated Independent Waste Sorting and Processing Tool (PLASMA-T) as an innovative solution that processes organic waste into compost and melts plastic waste into paving blocks that are useful and economical. The activities are carried out in stages, including problem identification, socialization, technical training, operational trials, evaluation of results, and the handover of the equipment to the Mitra Sejahtera TPS, with ongoing assistance so that the community can operate the equipment independently. The expected outcomes include a reduction in waste volume at the TPS, increased community awareness and skills in waste management, and the creation of new business opportunities through compost and paving block products. Thus, this program not only addresses environmental issues but also strengthens the village's circular economy and has the potential to serve as a model for other regions.

Early childhood education is a fundamental phase in the formation of children's character, literacy skills, and social skills. However, children's basic literacy skills in various regions of Indonesia, including Aisyiyah 2 Aimas Kindergarten, Southwest Papua, are still relatively low, exacerbated by limited learning media, conventional teaching approaches, and teachers' lack of understanding of inclusive education and positive discipline. This study aims to analyze the implementation of basic literacy training with inclusive education and its impact on improving teacher competence. The method used is a one group pretest in the context of community service, involving six teachers as subjects. The program is carried out through three stages: pre-training (observation, interview, and pretest), training (literacy materials based on the DUBT model—Listen, Speak, Read, Write; inclusive education; and positive discipline), and post-training (posttest, classroom observation, reflection, and mentoring). The results showed a significant increase in teacher competence, as shown by the increase in the average pretest score from 57.5 to 84.8 in the posttest. In addition, 83% of teachers are able to implement literacy practices such as reading picture stories, letter cards, reading corners, and dialogue interactions with children. Teachers also began to show acceptance of children's diversity and applied positive discipline without punishment. These findings show that inclusion-based literacy training is effective in improving teachers' pedagogical knowledge and practices. This research emphasizes the importance of developing adaptive, humanist, and equitable literacy as the foundation of early childhood learning.

The automotive industry requires fast and accurate sales services, particularly in vehicle credit simulation processes. At Mazda dealerships, credit simulations are still commonly conducted using conventional tools such as printed installment tables or static PDF documents, which often cause delays and calculation errors. This study aims to design and develop a mobile-based vehicle credit simulation application using the Human-Centered Design (HCD) approach and the Flutter framework. The HCD method was implemented through the inspiration, ideation, and implementation stages to ensure that the application meets the real needs of Mazda sales representatives. The application supports flexible credit calculations based on vehicle on-the-road price, down payment, loan tenor, interest rate, and insurance schemes, including All Risk and combination insurance. Usability testing results show that the proposed application significantly improves calculation speed, accuracy, and overall user experience compared to conventional methods. Therefore, the application effectively supports sales performance, minimizes human error, and enhances professionalism in automotive sales services.

This study investigates the adoption of adaptive DevOps practices in embedded systems used in safety-critical industrial applications. Traditional DevOps models, which are primarily designed for cloud-based systems, face significant challenges when applied to embedded platforms due to hardware constraints, real-time performance requirements, and stringent safety standards. The research focuses on developing a tailored DevOps framework that integrates continuous integration/continuous delivery (CI or CD) pipelines, automation, real-time monitoring, and safety assurance processes to enhance system reliability, performance, and compliance with regulatory standards. The study uses a case study methodology, involving embedded system teams across multiple industrial sectors, to assess the impact of these adapted DevOps practices on system stability and operational efficiency. Key findings show that the adoption of adaptive DevOps practices led to significant improvements in system reliability, performance, and deployment stability. Continuous feedback mechanisms allowed for early issue detection and faster resolution, leading to enhanced system uptime and responsiveness. Additionally, the integration of safety assurance into the DevOps pipeline ensured that safety-critical systems complied with required safety integrity levels and certification standards. The study further explores the integration of DevOps with embedded safety-critical systems, highlighting the benefits of cross-domain collaboration, enhanced communication, and the ability to address the unique challenges of these platforms. The research also underscores the limitations of conventional DevOps models in embedded systems and presents practical implications for the wider adoption of DevOps in safety-critical industrial applications. Future research is recommended to refine DevOps frameworks for embedded systems, integrating emerging technologies like the Industrial Internet of Things (IIoT) and Digital Twins to further optimize performance, security, and predictive maintenance.

Public relations management is a strategic approach employed by the Ministry of Tourism and Creative Economy (Kemenparekraf) in providing public information related to tourism. This study aims to analyze the public relations management process of Kemenparekraf in disseminating tourism-related public information by using a descriptive qualitative approach and the public relations management theory proposed by Cutlip, Center, and Broom. Research data were obtained through in-depth interviews, literature review, and observation. The results indicate that Kemenparekraf implements the four stages of public relations management comprehensively: defining public relations problems, planning and programming, taking action and communicating, and evaluating the program. Kemenparekraf utilizes various digital and conventional platforms to disseminate tourism information, with an emphasis on transparency, accuracy, and information accessibility. The implementation of the Public Information Disclosure Act is also a major focus, including the provision of information that must be periodically disclosed, immediately announced, and available at all times. Effective public relations management enables Kemenparekraf to address challenges in the dissemination of complex and dynamic tourism information and to ensure equitable access to tourism information for various stakeholders, thereby supporting sustainable tourism development in Indonesia.

This community service activity aims to socialize the development of Human Resource (HR) competencies in the Fashion Design Department at SMK Al Ihsan to face the transformation of the fashion industry based on digital technology. The main challenge faced is the gap (mismatch) between the school curriculum, which still focuses on conventional production techniques, and the needs of an industry that is now digital and automated. The method used in this activity is a participatory and educational approach that includes four stages: needs observation, delivery of theoretical material (lecturing), focused group discussions (FGD) accompanied by application demonstrations, and evaluation. The results of the activity show an increase in participants' understanding of concepts such as eco-fashion, the creative economy, as well as the introduction of digital technologies like 3D design applications (CLO3D) and digital pattern making. Through the integration of four competency pillars hard skills, soft skills, digital skills, and entrepreneurial skills it is expected that graduate profiles can transform from operational seamstresses into competitive fashionpreneurs in the global market. The conclusion of this activity emphasizes that the Link and Match strategy and mastery of technological literacy are key to effectively reducing the skills gap of students in the Industry 4.0 era.

Semantic interoperability remains a major challenge in large scale distributed information systems due to heterogeneous data schemas, diverse contextual interpretations, and the dynamic nature of distributed environments. Traditional metadata-based interoperability approaches are often insufficient to address these challenges, as they lack semantic expressiveness and adaptability. This study proposes a context aware knowledge graph framework to enhance semantic interoperability across heterogeneous distributed systems. The research adopts a design-oriented methodology involving requirement analysis, knowledge graph construction, ontology modeling and alignment, context aware semantic representation, and semantic reasoning. A prototype implementation is developed to evaluate the effectiveness of the proposed framework through interoperability scenarios and cross-system semantic queries. The results demonstrate that the proposed approach significantly improves semantic alignment accuracy, query precision, and recall compared to conventional metadata-based solutions. The explicit integration of contextual information and ontology-based reasoning enables adaptive semantic interpretation and reduces ambiguity across systems. Overall, the findings confirm that combining knowledge graphs with ontology modeling and context aware mechanisms provides a robust and scalable solution for improving semantic interoperability in complex distributed information systems.

The integration of Augmented Reality (AR) technology into higher education has emerged as a promising approach to enhance collaborative learning experiences. This study aims to design and evaluate an AR multimedia framework that facilitates real time interaction and spatial visualization, creating immersive and engaging learning environments for students. The AR framework was developed with a focus on improving student engagement, collaboration, and learning outcomes through interactive 3D models and real time feedback. By leveraging AR technology, the study sought to address common challenges in traditional learning environments, such as limited student interaction and engagement, and lack of real time feedback. The experimental evaluation involved two student groups: one using the AR-based system and the other using conventional multimedia tools. Findings revealed that students using the AR framework showed significant improvements in engagement, interaction frequency, and collaborative task performance. Additionally, the AR framework contributed to better learning outcomes, including enhanced comprehension, retention of complex concepts, and improved problem-solving skills. The study also highlighted the importance of incorporating a user-centered design approach in developing AR applications to ensure that the system meets the needs and preferences of learners. Qualitative feedback from students indicated that the AR system provided an enriched learning experience, although challenges such as interface navigation were noted. Overall, the study demonstrates the effectiveness of AR in fostering collaborative learning and offers practical insights for its integration into higher education curricula. Future research should explore the integration of AR with other immersive technologies to further enhance collaborative learning experiences.

Recent advancements in environmental monitoring and robotic control demand systems that are capable of real-time responsiveness, energy efficiency, and reliable operation in dynamic and resource-constrained environments. Conventional cloud-centric cyber-physical system (CPS) architectures often suffer from high latency, continuous connectivity dependency, and increased energy consumption, limiting their suitability for time-critical monitoring and adaptive control applications. To address these challenges, this study proposes an intelligent embedded cyber-physical system integrating Edge AI, low-power sensor networks, and adaptive robotic control for environmental monitoring. The proposed architecture relocates data processing and decision-making closer to the data source, enabling real-time inference, reduced communication overhead, and enhanced system autonomy. The research adopts a design-oriented experimental methodology involving system architecture design, lightweight Edge AI model development, prototype implementation, and performance evaluation under realistic operating conditions. Experimental results demonstrate that the proposed edge-based CPS significantly reduces end-to-end latency and energy consumption while maintaining acceptable inference accuracy compared to cloud-based processing. Furthermore, the system achieves improved communication efficiency and higher operational reliability, particularly under intermittent network connectivity. The findings highlight that embedding intelligence at the edge enables closed-loop sensing, decision-making, and actuation, which is essential for adaptive robotic control in environmental monitoring scenarios. This study contributes a system-level perspective on Edge AI–enabled CPS design and provides empirical evidence supporting the transition from cloud-centric architectures toward distributed, energy-aware, and resilient cyber-physical systems for real-time monitoring and control applications.