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This study aims to review the perspectives of MSME owners in the Gonilan area, particularly regarding part-time workers and their use in improving operational cost efficiency. The Gonilan area is known to have many MSMEs operating in various sectors, making this study relevant for understanding the challenges they face. A qualitative method was chosen so that the researcher could conduct in-depth interviews with three MSME owners. The informants were selected because they employed both full-time and part-time workers. The interview results showed that part-time workers were effective in reducing operational costs, such as more flexible hourly wages, although there were some disadvantages. The main disadvantages of part-time workers included lack of experience and limited working hours, which could be overcome through extra training and clear task distribution so that they could focus and increase productivity. The study concluded that the use of part-time workers has a significant impact on the operational cost efficiency of MSMEs, helping owners navigate the market without excessive financial burdens and encouraging long-term business growth.

The village is the lowest level of government that directly interacts with the community in providing and delivering public services. This requires the support of competent village officials, who are able to provide transparent and accountable services. Orderly and professional village administration is a crucial foundation for achieving good village governance. However, village administration issues remain a significant challenge that requires serious attention. This Community Service activity aims to improve the capacity of village officials in public service through administrative training in Rinbesihat Village, West Tasifeto District, Belu Regency. This community service activity involved university students and was implemented in several stages: initial coordination with the sub-district and village governments, problem mapping, activity implementation, and evaluation. The results of this community service activity were increased knowledge, which in turn improved the quality of village officials in village administration. With this training, it is hoped that village administration management can become more orderly, effective, and support the achievement of good and accountable village governance.

Erpat Leather is a manufacturer of leather bags, pouches, wallets, and belts, located in Tirto RT 05, Bangunjiwo, Kasihan, Bantul, Yogyakarta. Some production materials are not arranged neatly, which can disrupt the smoothness of the production process. The business needs to improve the efficiency and smoothness of the production process. Then, community service activities were carried out by lecturers, educational staff, and students of the Industrial Engineering and Mechanical Engineering Study Programs of the University of AKPRIND Indonesia to increase the knowledge of Erpat Leather owners and workers about 5S (Seiri, Seiton, Seiso, Seiketsu, Shitsuke). Erpat Leather needed training to improve the smoothness of the production process, work efficiency, and work safety. This training began with a discussion between the service team and the business owner, followed by field observations by the service team, and continued with suggestions for improvement to the owner and workers, and ended with the delivery of conclusions and a group photo. The implementation of 5S at Erpat Leather is carried out through five stages, namely, first, sorting goods that are still in use and those that are no longer used; second, arranging goods in the production area in an orderly manner; third, cleaning the work environment regularly; fourth, maintaining the work area to keep it clean; fifth, disciplining good work habits, and providing slogans that cultivate 5S. This activity is expected to increase Erpat Leather's competitiveness in the leather product market by improving the smoothness of the production process.

Erpat Leather is a manufacturer of leather bags, pouches, wallets, and belts, located in Tirto RT 05, Bangunjiwo, Kasihan, Bantul, Yogyakarta. Some production materials are not arranged neatly, which can disrupt the smoothness of the production process. The business needs to improve the efficiency and smoothness of the production process. Then, community service activities were carried out by lecturers, educational staff, and students of the Industrial Engineering and Mechanical Engineering Study Programs of the University of AKPRIND Indonesia to increase the knowledge of Erpat Leather owners and workers about 5S (Seiri, Seiton, Seiso, Seiketsu, Shitsuke). Erpat Leather needed training to improve the smoothness of the production process, work efficiency, and work safety. This training began with a discussion between the service team and the business owner, followed by field observations by the service team, and continued with suggestions for improvement to the owner and workers, and ended with the delivery of conclusions and a group photo. The implementation of 5S at Erpat Leather is carried out through five stages, namely, first, sorting goods that are still in use and those that are no longer used; second, arranging goods in the production area in an orderly manner; third, cleaning the work environment regularly; fourth, maintaining the work area to keep it clean; fifth, disciplining good work habits, and providing slogans that cultivate 5S. This activity is expected to increase Erpat Leather's competitiveness in the leather product market by improving the smoothness of the production process.

Small and medium-sized enterprises (SMEs) producing bags play an important role in the regional economy, but still face problems in financial management, particularly cash flow planning. The main problem faced by SME partners producing bags in Cipamokolan Village, Rancasari District, Bandung City, is the lack of comprehensive cash flow planning, which has the potential to cause liquidity problems. This community service activity aims to improve the understanding and skills of bag SME  in preparing a simple cash budget and encouraging its sustainable implementation. The methods used include training and mentoring with stages of problem identification, material delivery, cash budget preparation practice, and evaluation. The results of the activity show an increase in partners' understanding of cash planning, their ability to prepare a simple cash budget, and their commitment to implementing a cash budget in their daily business financial management. This activity is expected to improve cash flow control and support the sustainability of bag SME businesses

This study aims to describe the implementation of the principles of tawassuth, tawazun, and tasamuh in religious activities at Islamic boarding school Al-Manshuriyah Plered-Purwakarta, as well as to analyze the supporting factors, challenges, and their impact on shaping the moderate character of the the students. This research employs a qualitative approach with a descriptive method. Data were collected through observation, interviews, and documentation. The findings indicate that the implementation of Ahlussunnah wal Jama’ah (Aswaja) values has been carried out effectively through various programs such as routine Islamic study sessions, Qur’an reading, congregational prayer, commemoration of Islamic holidays, and social-religious activities. The principle of tawassuth is reflected in the congregation’s moderate attitude in understanding religious texts, tawazun is demonstrated through the balance between worship activities and social engagement, while tasamuh is manifested through harmonious interactions and appreciation of differences. Supporting factors include visionary leadership and a conducive learning environment, whereas inhibiting factors involve the diverse backgrounds of community members and limited facilities. The implementation of Aswaja values has positively contributed to the development of moderate, tolerant, and religious character among the congregation. This study reinforces the importance of Islamic boarding school as a center for cultivating Wasathiyah-based Islamic character in society.

K-Pop has developed into a key instrument of South Korean cultural diplomacy with global reach, including in Indonesia. Behind its success as a soft power tool, K-Pop harbors complex dynamics of gender representation, particularly regarding the position and role of women. This study aims to analyze women's representation and agency in South Korean cultural diplomacy through K-Pop in Indonesia during the 2022–2023 period. This study uses a qualitative approach with a descriptive-interpretive design, combining a poststructuralist feminist perspective and cultural diplomacy theory. Data were collected through a documentary study of K-Pop cultural products and in-depth interviews with K-Pop fans in Indonesia. The results show that women play a central role in K-Pop's global success, both as idols and as active fans. However, women's representation in K-Pop is still dominated by standardized beauty standards and images of femininity. On the other hand, women's agency emerges through fandom practices that allow female fans to actively interpret, critique, and negotiate the meaning of gender representation. This study also found that gender issues have not been explicitly integrated into South Korean cultural diplomacy policies. These findings confirm that cultural diplomacy through K-Pop is dynamic and involves active interaction between the country, industry, and the recipient society.

Temulawak (Curcuma xanthorrhiza Roxb.) is an indigenous medicinal plant of Indonesia that has been widely used in traditional medicine and shows considerable potential in the health and pharmaceutical fields. This potential is related to its diverse secondary metabolites with bioactive properties. This review article aims to examine the phytochemical profile of temulawak, the analytical methods used to identify bioactive compounds, and their reported biological activities based on literature studies. The method applied was a literature review of scientific articles discussing the chemical composition and biological activities of temulawak. The results indicate that temulawak contains major compounds such as curcuminoids, xanthorrhizol, flavonoids, phenolic compounds, and essential oils, which are commonly identified using chromatographic and spectroscopic techniques. Several studies report that temulawak exhibits antioxidant, anti-inflammatory, antibacterial, hepatoprotective, and potential anticancer activities. These findings indicate that temulawak has significant potential as a source of natural bioactive compounds. In conclusion, temulawak possesses a rich phytochemical profile and promising biological activities, supporting its potential application in the development of natural-based health and pharmaceutical products.

This study aims to analyze the reaction of the Indonesian capital market to the announcement of Donald Trump’s import tariff policy using an event study approach. Market reactions are measured through abnormal return and trading volume activity of exporting companies listed on the Indonesia Stock Exchange (IDX), with an event window of three trading days before and three trading days after the initial tariff announcement on April 2, 2025 and the revised tariff announcement on July 15, 2025. This study employs secondary data in the form of daily stock prices and trading volumes, analyzed using descriptive statistics, normality tests, and the Wilcoxon Signed Rank Test. The results indicate that the Indonesian capital market reacts to the announcement of Donald Trump’s import tariff policy, as reflected by differences in abnormal return and trading volume activity before and after the announcements, thereby supporting signaling theory and the semi-strong form of market efficiency.

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.

This study investigates the incorporation of Sufi-oriented values into the management practices and production processes of MADA Drinking Water operated by the Ahlus Shafa Wal Wafa Islamic Boarding School Foundation. The research focuses on the Syafi’i ethical concept known as Giti–Gito, which encompasses spiritual and moral values including sincerity, patience, inner richness, holistic physical and spiritual well-being, as well as fairness in sharing resources. The main aim of this study is to examine how these values are implemented within pesantren-based business management and to assess their impact on employees’ work attitudes, leadership styles, and interpersonal relations in the workplace. This research employs a qualitative case study method. Data were gathered through semi-structured interviews, participant observation, and a review of relevant institutional documents. The findings reveal that the implementation of Giti–Gito values has successfully shaped a work environment grounded in religious ethics, social harmony, and humanistic principles. The Giti aspect strengthens employees’ commitment to sincerity, patience, and accountability in carrying out their responsibilities, while the Gito aspect contributes to enhancing employee welfare and fostering a sense of social responsibility. Although challenges remain in reconciling spiritual values with modern management demands, the integration of both spiritual and professional dimensions has demonstrated its effectiveness in creating a productive, ethical, and sustainable organizational environment.

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

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.

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.

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.

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

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

The increasing demand for real time parallel processing in cloud computing environments necessitates the development of more efficient and fault-tolerant scheduling algorithms. Traditional scheduling methods, such as static algorithms, often fall short when handling dynamic workloads and system failures, leading to increased task latency and reduced system performance. In contrast, adaptive scheduling algorithms dynamically adjust to changes in system conditions and workloads, ensuring timely task completion and optimized resource utilization. This study evaluates the performance of adaptive scheduling algorithms in real time cloud environments, focusing on key factors such as task latency, system resilience, and fault tolerance. Simulation experiments were conducted using cloud computing models that incorporate fault injection scenarios, including network failures and virtual machine crashes. The results show that adaptive algorithms significantly outperform traditional static schedulers in terms of task latency reduction and improved system resilience. These algorithms demonstrated better fault recovery times and ensured consistent real time performance, even under failure conditions. The findings highlight the advantages of adaptive scheduling in cloud environments, particularly for applications requiring rapid data processing and high system reliability. Despite the promising results, challenges remain regarding the scalability and complexity of these algorithms in large-scale cloud systems. Further research is needed to optimize adaptive scheduling algorithms for efficiency, scalability, and comprehensive performance evaluation, taking into account factors such as energy consumption, cost, and reliability. This research contributes to advancing cloud computing infrastructures that can dynamically handle real time tasks and maintain high performance under varying workloads and failures.

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.

Employee performance is a key factor in determining organizational success in achieving its strategic objectives. Various management studies indicate that employee performance is not solely influenced by individual factors, but is also significantly affected by organizational factors, particularly organizational planning and organizational structure. Effective organizational planning provides a clear direction and strategic framework that guides employees in performing their tasks, while an appropriate organizational structure facilitates coordination, clarifies authority, and supports the efficient execution of work. This study aims to analyze the influence of organizational planning and organizational structure on employee performance through a systematic literature review approach. The research method employed is a systematic literature review by examining relevant national and international journal articles published within the last ten years. Data were collected from reputable academic databases to ensure the credibility and relevance of the sources. The selected studies were analyzed qualitatively to identify patterns, relationships, and key findings related to the research variables. The results of the literature review indicate that systematic and well-formulated organizational planning contributes positively to improving goal clarity, work coordination, and employee motivation. Furthermore, an organizational structure that is aligned with organizational strategies plays an important role in clarifying task distribution, authority lines, and overall work effectiveness. The findings also reveal that organizational planning and organizational structure are interrelated and mutually reinforcing in shaping employee performance. This study concludes that the integration of organizational planning and organizational structure is a crucial factor in enhancing sustainable employee performance. The results of this study are expected to provide both theoretical contributions to organizational management studies and practical references for organizations in designing effective management systems.