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Facilities and infrastructure are essential components in the provision of education, functioning to support the effectiveness of teaching and learning processes, student comfort, and the achievement of quality learning outcomes. In boarding-based Islamic schools (madrasah), facility needs become more complex due to the integration of formal academic curricula with religious instruction and a full residential system. The National Education Standards (SNP) serve as the national reference for the fulfillment of educational facilities in Indonesia; however, the standards do not specifically regulate boarding facilities, resulting in a gap in facility fulfillment among pesantren-based madrasah. This study aims to evaluate the suitability of educational facilities and infrastructure at MTsS Sunanul Husna, South Tangerang City, with the SNP and to identify inhibiting factors affecting the fulfillment of such standards. The research employed a qualitative case study design through observation, interviews, and documentation. Data analysis was conducted using interactive procedures, including data reduction, data display, and conclusion drawing. The findings indicate that academic facilities are categorized as adequate, with classrooms, teacher rooms, administrative offices, computer laboratories, and a UKS room available and functioning, although the library and student sanitation facilities require improvement. Boarding facilities such as dormitories, worship areas, and kitchen facilities are categorized as good, despite not being covered in the SNP. The study reveals that financial limitations, centralized authority at the foundation level, and the absence of national standards for boarding education represent the main inhibiting factors. The study implies the need for the formulation of facility standards specifically for boarding madrasah and for strengthened collaboration among the government, foundations, and communities in fulfilling educational infrastructure.

This study aims to evaluate the implementation of civil servant discipline enforcement based on Surabaya Mayor Regulation Number 44 of 2022 at Gubeng Subdistrict. The research employs a qualitative approach with a case study design. Data were collected through in-depth interviews, observation, and document analysis, and analyzed using the interactive model of Miles and Huberman within the Context–Mechanism–Outcome (CMO) framework. The findings indicate that the regulation has generally improved civil servant discipline, particularly in attendance, punctuality, administrative compliance, and public service quality. This improvement is supported by organizational context factors such as daily work culture, active leadership, and the integration of digital attendance systems. Key mechanisms driving compliance include layered supervision, persuasive coaching, and the gradual application of disciplinary sanctions. However, challenges remain, including high workloads and limited human resources, which require continuous guidance for certain employees. The study concludes that the effectiveness of civil servant discipline enforcement is largely shaped by the interaction between organizational context and policy implementation mechanisms.

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 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.

Curriculum management is a strategic component of Islamic education because it plays an important role in achieving educational objectives and internalizing Islamic values within the learning process. Nevertheless, in practice, many schools continue to face managerial challenges in implementing the curriculum effectively. This study aims to evaluate curriculum management at MTs Persis 23 Cirengit based on the core functions of Islamic Educational Management, namely Planning, Organizing, Actuating, and Controlling (POAC). The research employed a qualitative approach using a case study design. Data were collected through in-depth interviews, direct observation, and document analysis, and were analyzed using an interactive analysis model. The findings reveal that the POAC functions have been formally applied but have not yet operated as an integrated managerial cycle oriented toward continuous quality improvement. Curriculum planning remains largely procedural, organizing is not sufficiently participatory, implementation depends heavily on individual teacher capacity, and supervision is mostly administrative with limited follow-up actions.

Adolescent mental health is an essential component of optimal growth and development, yet it often receives less attention compared to academic achievement. Adolescents are in a vulnerable developmental stage characterized by emotional changes, social pressure, and environmental demands, which increase the risk of mental health problems. This activity aimed to improve knowledge and promote positive attitudes among junior high school students regarding adolescent mental health, including its definition, signs and symptoms, risk factors, and prevention strategies. The method used was a health education intervention employing a pre-test and post-test design. The activity was conducted at Al Amanah Junior High School, South Tangerang City, involving 25 students. The evaluation instrument consisted of a 10-item multiple-choice questionnaire with a maximum score of 100. The results showed that the average pre-test score was 98.40%, while the post-test score increased to 99.60%, indicating a 1.20% improvement. Although the increase was relatively small due to the high baseline knowledge (ceiling effect), the findings demonstrate that the educational intervention effectively reinforced students’ understanding of adolescent mental health. In addition, interactive discussions during the session contributed to increased awareness and reduced stigma related to mental health issues. This mental health education program has the potential to support early prevention efforts and foster a more supportive school environment for adolescents’ psychological well-being.

This study aims to determine the effect of implementing the Problem-Based Learning (PBL) model on student learning outcomes in the Ignition System competency at SMKN 1 Katapang. The background of this study stems from the low understanding of students regarding the ignition system material due to the dominant use of the Teacher-Centered Learning (TCL) model, which tends to make students passive and only memorize concepts without understanding the overall working process. PBL is considered more relevant because it emphasizes real problem-solving, critical thinking, collaboration, and analysis according to constructivist theory. The method used is a quasi-experiment with a Nonequivalent Control Group Design. The research subjects consist of two classes of 11th-grade Light Vehicle Engineering students: an experimental group using the PBL model and a control group using TCL, with a total population of 70 students. Data collection was done through pretests and posttests using a validated multiple-choice objective test instrument. Data analysis includes comparing the learning outcome improvements of both groups to determine the effectiveness of PBL. The results show a more significant improvement in learning outcomes in the class using the PBL model compared to the TCL class. This proves that the implementation of PBL is effective in improving analysis skills and diagnostic skills in the ignition system. Therefore, PBL is recommended as a more suitable teaching model for practice-based subjects in vocational schools, especially in automotive electrical competencies.

Senior high school students represent a strategic age group transitioning into adulthood and are expected to become future leaders of the nation. In the context of achieving Indonesia’s Vision 2045, threats to national resilience are no longer dominated by military aggression, but rather by non-military challenges in the form of cognitive warfare. One prominent manifestation of this threat is the massive exposure of students to low-value digital content, commonly referred to as brain rot, on social media platforms. Such content has the potential to reduce attention span, critical thinking ability, and national awareness among adolescents. Consequently, senior high school students have become a vulnerable group in the spread of misinformation, disinformation, and ideologies that contradict Pancasila values. This community service activity aims to provide training and strengthen national defense character (bela negara) among senior high school students in Jakarta through an educational and participatory approach. The methods employed include the delivery of conceptual materials on national defense awareness and digital literacy, as well as national defense debate simulations designed to enhance students’ critical, argumentative, and ethical thinking skills. The results indicate an improvement in participants’ understanding of national defense values and their ability to express logical and responsible arguments. This activity is expected to contribute to the development of a resilient, critical, and nationally-minded young generation capable of facing contemporary challenges in the digital era.

The increasing demand for low latency and high-throughput multimedia applications has spurred significant advancements in hardware software co design. This study explores the integration of custom digital signal processing (DSP) hardware accelerators with optimized software frameworks to enhance deep learning accelerated DSP tasks. The proposed co design approach significantly reduces latency and improves throughput compared to traditional software-only DSP implementations. Through the development of custom hardware accelerators built with FPGA technology, the system achieves up to a 1.85x reduction in latency and a 1.5x improvement in throughput for real-time multimedia tasks such as image recognition, video decoding, and audio processing. The combination of hardware and software optimizations allows for better resource utilization, enabling the parallel processing of computationally intensive tasks while the software framework handles less demanding operations. Additionally, the co design system demonstrated improved energy efficiency, making it highly suitable for embedded systems. The results show that the hardware software co design approach offers substantial advantages in performance, latency reduction, and energy efficiency, positioning it as a viable solution for real-time multimedia applications. The findings have important implications for applications requiring fast data processing, such as autonomous driving, healthcare, and disaster management. Future research could explore alternative hardware accelerators, advanced software optimizations, and AI-based resource management to further improve the system’s efficiency and scalability for more complex multimedia tasks.

Edge-Internet of Things (Edge IoT) systems are increasingly integral to applications that require real time signal processing, particularly where low latency and energy efficiency are critical. This paper explores the design and performance evaluation of a heterogeneous microprocessor architecture aimed at optimizing energy consumption and real time performance. The heterogeneous architecture integrates multiple types of cores, such as Central Processing Units (CPUs), Digital Signal Processors (DSPs), and Graphics Processing Units (GPUs), to allocate tasks based on computational demand. The proposed design significantly reduces energy consumption, particularly during high-performance tasks, while maintaining real time processing guarantees. Simulation-based performance evaluation was conducted to assess the energy efficiency, latency, and overall system performance under varying workloads, including real time Digital Signal Processing (DSP) benchmarks. The results showed that the heterogeneous architecture outperformed traditional homogeneous processors, demonstrating up to a 19-fold improvement in energy efficiency. Furthermore, the system reduced latency by up to 45% in real time applications, making it particularly suitable for Edge IoT environments such as industrial automation and smart healthcare, where both performance and energy efficiency are critical. Despite some trade-offs in task scheduling complexity, the heterogeneous design was able to balance power consumption and computational performance effectively. The findings suggest that this architecture can serve as a foundation for future Edge IoT systems, providing significant advantages in terms of energy efficiency, real time processing, and scalability. Future work will focus on further optimization of the architecture and exploring its application across various IoT environments.

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.

This research explores the impact of Cache Aware optimizations on signal processing pipelines in High Throughput computing systems. The growing demand for efficient memory management in modern computing systems, especially for data-intensive applications such as artificial intelligence (AI) and multimedia processing, necessitates the development of optimized memory hierarchies. Traditional memory systems often suffer from memory bottlenecks, significantly reducing the performance of these systems. This study investigates how memory hierarchy optimizations, particularly cache line aware optimization, dependency-aware caching, and adaptive cache replacement algorithms, can mitigate these challenges and improve system performance. Through analytical modeling and experimental benchmarking, this work evaluates various memory hierarchy configurations, including processing-in-memory (PIM) and three-dimensional integrated circuits (3D ICs), comparing them to conventional systems. The results demonstrate that Cache Aware optimizations lead to a reduction in memory access latency by up to 30%, while throughput improved by up to 40%. Additionally, cache hit rates increased by 25%, and energy consumption was reduced by up to 20%, highlighting the effectiveness of optimized memory management. The research contributes to the field by providing valuable insights into the design and implementation of efficient signal processing pipelines. It also identifies key challenges, including the need for dynamic occupancy mechanisms and DAG-aware scheduling algorithms, and suggests potential areas for future research, such as the exploration of collaborative caching approaches and further optimization of cache-adaptive algorithms. This work lays the foundation for more efficient, high-performance computing systems that can handle large datasets and complex tasks in real-time applications.

The integration of Digital Signal Processing (DSP) algorithms in low power microcontroller based embedded systems has emerged as a promising solution to optimize energy efficiency without compromising signal accuracy and performance. This study focuses on the design and optimization of DSP algorithms specifically for microcontrollers, aimed at achieving real-time, reliable monitoring for applications such as healthcare, environmental sensing, and IoT devices. The research highlights the system's ability to handle complex signal processing tasks while maintaining low power consumption, ensuring long-term, continuous operation in remote or battery-powered environments. The system employs various techniques, including advanced power management strategies such as dynamic voltage scaling (DVS) and adaptive voltage scaling (AVS), along with lightweight AI algorithms and model pruning, to minimize energy use. The results show significant reductions in power consumption compared to traditional systems, particularly during continuous monitoring tasks. Despite this, the optimized DSP algorithms maintain or even enhance signal accuracy, ensuring that critical monitoring data remains reliable. Furthermore, the system demonstrates robust performance and reliability over extended periods, making it suitable for long-term deployment in critical applications such as wearable medical devices and industrial sensors. This research provides a foundation for the development of future low power embedded systems, emphasizing the importance of DSP-aware optimization in achieving energy-efficient and high-performance monitoring. Future improvements may include advanced AI-driven power optimization techniques, enhanced scalability, and cross-domain interoperability, ensuring that these systems can be effectively deployed across diverse applications, from healthcare to environmental monitoring.

This research explores the role of human algorithm interaction mechanisms in enhancing trust, reliability, and user confidence in Decision Support Systems (DSS). Traditional DSS models often focus solely on algorithmic accuracy and performance, neglecting crucial factors such as transparency and user engagement, which are essential for building trust. By incorporating explainable AI (XAI) techniques like SHAP and LIME, real-time feedback mechanisms, and user-friendly interfaces, the study develops structured interaction models that improve the interpretability of AI-driven decisions. The results show that transparent decision-making processes and interactive features significantly enhance user trust, making DSS more reliable and easier to adopt. Users interacting with systems that provide clear, understandable explanations of decisions, along with real-time updates on the system’s confidence, reported higher levels of decision-making confidence, especially in high-stakes scenarios. These improvements lead to greater user engagement and adoption of the system in various domains, including healthcare and finance. The study also highlights the importance of balancing interpretability with efficiency in user interface design to ensure both trust and usability. The findings contribute to the design of more user-centric DSS that prioritize trust, interpretability, and cognitive factors, providing a framework for the successful integration of intelligent decision support systems in complex decision-making environments. Future research should focus on refining interaction models and exploring the broader applicability of these systems in different sectors.

This study investigates the integration of high performance communication protocols with adaptive signal processing engines in multi-core systems, aiming to enhance scalability, throughput, and inter-core communication efficiency. The challenges inherent in traditional multi core architectures, such as communication overhead, latency, and scalability limitations, are addressed through the incorporation of Network-on-Chip (NoC) architectures and adaptive signal processing techniques. By using a multi-core digital signal processing (DSP) platform, the study evaluates the performance improvements achieved by this integration under varying workloads and core configurations. The experimental results show a 35% improvement in throughput and a 25% reduction in communication latency, highlighting the effectiveness of adaptive communication protocols in managing data traffic between cores and reducing bottlenecks. The integration of NoC architecture facilitates parallel data transfers, while adaptive signal processing engines ensure that data flows more efficiently across the cores, enhancing system responsiveness, especially under high data rate conditions. Furthermore, the study explores the scalability of the proposed system, demonstrating its ability to maintain high performance as core counts increase. The findings emphasize the potential of combining advanced communication protocols with adaptive signal processing for optimizing multi-core system performance. Practical implications of this research include the design of scalable, flexible, and efficient multi core architectures suitable for complex, data-intensive applications. Future research should focus on further refining communication protocols and exploring additional integration strategies to enhance the adaptability and scalability of multi-core systems in next-generation computing environments.

This study aims to determine the effectiveness of the Problem Based Learning (PBL) model integrated with Canva in improving students’ reflective thinking skills in the Aqidah Akhlaq subject at MTsN 3 Tuban. Reflective thinking is an essential competency that enables students to analyze moral behavior, evaluate decision-making processes, and connect Islamic ethical concepts with real-life experiences. However, preliminary observations indicated that students’ reflective thinking skills were still low and tended to remain at the level of theoretical understanding without deeper analysis. This research employed a pre-experimental design using a one-group pretest–posttest model. The subjects consisted of 30 eighth-grade students. The research instrument was a reflective thinking test developed based on indicators of moral evaluation, situation analysis, and experiential reflection, which had been validated through expert judgment. The learning process was conducted by applying the stages of Problem Based Learning integrated with Canva as a visual media to organize problem-solving steps and present students’ reflective outputs. Data were analyzed using descriptive statistics and a paired samples t-test. The findings showed a significant improvement in students’ reflective thinking skills after participating in PBL learning supported by Canva. Pretest scores ranged from 48 to 71 with an average of 59.67, while posttest scores increased to a range of 60 to 89 with an average of 71.20. The mean gain of 11.53 points was statistically significant as indicated by the t-test results (t = 10.39; sig. = 0.000), further supported by Cohen’s d value of 1.90, which falls into the category of a very large effect size. Qualitatively, students demonstrated enhanced abilities in identifying core problems, analyzing alternative actions, evaluating their cognitive processes, and visualizing moral reflections systematically through Canva. In conclusion, the PBL model integrated with Canva is effective in improving students’ reflective thinking skills in the Aqidah Akhlaq subject. This model not only enhances academic outcomes but also strengthens character development, creativity, and higher-order thinking skills, which are essential for 21st-century learning.

This study investigates the integration of computational thinking (CT) principles with adaptive curricula to enhance problem-solving skills in undergraduate programming education. Traditional programming curricula often emphasize syntax and basic concepts, neglecting critical problem-solving strategies. The adaptive curriculum framework used in this study combines CT skills such as decomposition, pattern recognition, abstraction, and algorithmic thinking with personalized learning experiences. A mixed-method approach, combining qualitative and quantitative research, was employed to assess the effectiveness of this integrated approach. The results show significant improvements in students' problem-solving abilities, conceptual understanding, and engagement compared to a control group following a traditional curriculum. Students in the experimental group, which received the adaptive curriculum, demonstrated better performance in applying algorithms and debugging code. Additionally, students expressed higher levels of engagement and motivation, suggesting that the personalized learning environment fostered greater academic involvement. The study highlights the importance of integrating CT principles with adaptive learning frameworks to create a more inclusive and effective learning environment that accommodates diverse learning needs. The findings suggest that adaptive curricula can bridge gaps in traditional education by providing personalized support and ensuring that students progress at their own pace. This approach is especially beneficial for programming education, where both conceptual understanding and practical problem-solving skills are critical for success. Future research should explore the long-term impact of adaptive learning frameworks and investigate how these technologies can be integrated with traditional teaching methods to maximize their effectiveness.

This community service activity was conducted at SMK Ganesha Tama Boyolali with the main objective of disseminating knowledge and practical tips on entrepreneurship and starting a business among vocational high school students. The activity aimed to provide students with an understanding of basic entrepreneurial concepts, initial steps in establishing a small business, and key factors that influence entrepreneurial success. This program was based on the importance of preparing vocational students not only to become skilled workers but also to develop the readiness to act as independent entrepreneurs. Several problems were identified prior to the activity, including students’ limited knowledge about how to start a business, fear of taking entrepreneurial risks, and low motivation to pursue entrepreneurship at an early stage. The method used in this program was mentoring through a socialization approach, supported by interactive discussions and question-and-answer sessions. The results showed a significant improvement in students’ understanding of entrepreneurship concepts and their ability to develop feasible business ideas. Most students successfully created simple business plans aligned with community needs, such as technical services, design and drawing services, planning consultancy, and mock-up services. In addition, the activity positively influenced students’ attitudes and mindset by increasing their self-confidence in presenting business ideas before their peers. Overall, this outreach program effectively fostered entrepreneurial spirit, motivation, and readiness among students at SMK Ganesha Tama Boyolali to pursue independent business opportunities after graduation.

Down Syndrome (DS) is a genetic disorder characterized by trisomy of chromosome 21 and is inherently associated with clinical manifestations such as hypotonia, joint laxity, and neuromuscular deficits, all of which collectively contribute to impaired postural control and balance. These balance impairments significantly affect the attainment of motor milestones, performance of daily activities, and increase the risk of falls. This study aims to analyze the effectiveness of core stability training in improving balance among children with DS. A narrative review approach was employed by conducting a literature search across electronic databases including PubMed, Scopus, Google Scholar, and ResearchGate. Inclusion criteria consisted of primary studies (RCTs, quasi-experimental designs) published within the last ten years (2015–2025) that examined core stability interventions targeting balance or postural control in children with DS. A review of 10 relevant studies demonstrated that core stability training, either as a standalone intervention or combined with other modalities (e.g., treadmill training or balance training), resulted in significant improvements in both static and dynamic balance. These improvements are facilitated through the strengthening of deep trunk muscles (such as the multifidus, transversus abdominis, and rectus abdominis), which play a crucial role in proximal stabilization and force transfer to the extremities. In conclusion, core stability training is an effective and recommended intervention modality within physiotherapy rehabilitation programs to enhance the quality of life and motor independence of children with Down Syndrome.  

This community service activity aimed to strengthen teachers’ competencies in utilizing digital platforms to support project-based learning at a vocational high school. The background of this activity was the limited ability of teachers to manage project-based learning in a structured and systematic manner using digital platforms. The method employed was participatory mentoring, involving needs analysis, activity planning, implementation of digital platform mentoring, monitoring and evaluation, and reflection with follow-up actions. The participants were teachers of SMK Negeri 1 Tukak Sadai, Bangka Barat. The results indicated an improvement in teachers’ understanding and skills in designing, managing, and evaluating project-based learning using digital platforms. Teachers became more confident in integrating technology into learning processes and demonstrated better organization of project activities. This activity contributed to enhancing teachers’ digital competencies and improving the quality of project-based learning practices in vocational education. The findings suggest that participatory mentoring is an effective approach to supporting sustainable digital learning innovation in vocational schools.