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This study aims to determine the effect of the Talking Stick model assisted by Mystery Box learning media on learning motivation and learning outcomes in IPAS of fifth-grade students at SD Inpres Borongunti, Bajeng District, Gowa Regency. This study employed a quantitative approach with a pre-experimental design. The research subjects consisted of 31 students. Data were collected using a learning motivation questionnaire and learning outcomes tests, while data analysis was conducted through normality testing and hypothesis testing using the t-test. The results showed that prior to the implementation of the Talking Stick model assisted by Mystery Box media, students’ learning motivation was predominantly in the low and moderate motivation categories. After the treatment was applied, students’ learning motivation increased significantly, with all students categorized as motivated and highly motivated. The t-test results for learning motivation indicated a significance value of 0.002 < 0.05, thus H₁ was accepted. In addition, students’ IPAS learning outcomes also showed a significant improvement, as indicated by an increase in the mean score from 66 in the pretest to 86 in the posttest, with learning mastery increasing from 42% to 100%. The t-test results for learning outcomes showed a significance value of 0.000 < 0.05, thus H₁ was accepted. Based on these findings, it can be concluded that the Talking Stick model assisted by Mystery Box learning media has a significant effect on improving learning motivation and learning outcomes in IPAS of fifth-grade students at SD Inpres Borongunti, Bajeng District, Gowa Regency.

This community service program aimed to strengthen the digital competencies of junior high school students through a structured workshop on graphic design and photography. The activity was conducted on June 10–11, 2025 at Universitas Ma Chung and involved thirteen students from SMP Insan Amanah accompanied by their teachers. The program was designed based on prior identification of learning needs conducted through coordination with school representatives. The workshop integrated theoretical instruction and hands-on practice covering basic photography concepts such as angle, shot, triangle exposure, and three point lighting, followed by editorial layout training using Canva. Students were guided to edit photographs, arrange layouts, and select appropriate text elements. The results indicated improvements in students’ technical skills, learning engagement, and collaborative behavior. A campus tour conducted at the end of the program provided additional insight into the academic environment of higher education. Overall, the program demonstrated that practice-based learning effectively supports digital skill development among junior high school students.

This study examines curriculum strategies implemented in five countries Singapore, Finland, Japan, Indonesia, and the United States using a library research approach. The main objective of this research is to analyze similarities, differences, challenges, and strategic orientations in curriculum development across diverse national education systems. Data were collected from scholarly journal articles, government policy documents, and international education reports published by reputable institutions. The analysis indicates that each country adopts distinct curriculum strategies influenced by its socio-cultural context, governance structure, policy priorities, and long-term educational goals. Singapore emphasizes competency-based learning aligned with economic needs, Finland prioritizes flexibility and teacher autonomy, Japan focuses on character education and cultural values, Indonesia continues to adapt its curriculum to improve relevance and equity, while the United States highlights standards-based accountability and innovation. Despite these differences, common patterns emerge, particularly in the emphasis on competency development, integration of 21st-century skills, teacher quality improvement, and curriculum adaptability to global challenges such as digitalization and workforce transformation. The findings suggest that effective curriculum development requires a balance between global educational trends and local contextual needs. This study contributes to comparative education discourse by providing insights that may inform policymakers and educators in designing responsive and sustainable curriculum strategies.

This study aims to examine the activity of ginger (Zingiber officinale) on metabolism and digestion through a laboratory experimental approach. Metabolism and the digestive system play a crucial role in maintaining physiological balance, and disturbances in these systems can affect nutrient utilization and overall health. Ginger has long been used as a traditional herbal remedy and is known to contain bioactive compounds such as gingerol, shogaol, and zingerone, which are believed to support digestive and metabolic functions. The research was conducted using ginger extract prepared through an extraction process under controlled laboratory conditions. Observations focused on changes in metabolic responses and digestive activity following the administration of ginger extract. The study employed a descriptive experimental design to provide an objective overview of ginger’s biological activity. The results indicated a gradual improvement in digestive activity and metabolic responses after treatment with ginger extract. These changes suggest that ginger extract has the potential to enhance digestive efficiency and support metabolic processes. The findings provide scientific support for the traditional use of ginger as a natural ingredient in maintaining metabolic and digestive health and may serve as a preliminary reference for further research using quantitative and clinical approaches.

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.

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.

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.

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.

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.

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.

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.

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 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.

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 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.

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.

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.

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.