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This study investigates the relationship between design patterns, modular architecture, and the maintainability of distributed real time systems developed using agile practices. Distributed real time systems are critical in various sectors, including telecommunications, healthcare, and automotive, where strict timing constraints and reliability are essential. Agile methodologies, known for their flexibility and iterative development, have been widely applied to software engineering, but their impact on long-term system maintainability, especially in complex real time environments, has been insufficiently explored. This research employs an empirical analysis, combining both quantitative and qualitative data from multiple real time system projects using agile methods. The analysis focuses on the application of design patterns, such as Singleton, Observer, and Factory, and evaluates the effectiveness of modular architectures in enhancing system scalability, flexibility, and long-term sustainability. The study also explores how agile practices contribute to system performance and maintainability, despite challenges related to frequent updates and coordination among distributed teams. Key findings show a positive correlation between the consistent use of design patterns and modularity, which significantly improves the maintainability and adaptability of distributed real time systems. This research also highlights the challenges faced by agile methods in maintaining architectural consistency and managing non-functional requirements, particularly in distributed environments. The results contribute valuable insights into adapting agile practices to meet the specific demands of distributed real time systems, offering recommendations for developers and project managers to incorporate modular architecture and design patterns to enhance long-term system sustainability. Further research is suggested to explore new design patterns and investigate the broader impact of agile methodologies on system quality beyond maintainability.

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

Aceh Tamiang Regency is an area with a high risk of annual flooding. This emergency condition often triggers a surge in environment-related diseases such as skin diseases, respiratory infections, and diarrhea. The success of managing health crises heavily depends on pharmaceutical logistics management, especially the availability of essential medicines and ease of access for refugees at evacuation points. This study aims to analyze the extent of medicine availability at community health centers and health posts, as well as to evaluate the barriers to medicine accessibility for flood victims in Aceh Tamiang Regency. This study uses a qualitative/quantitative descriptive method (choose one) with a case study approach. Primary data were collected through in-depth interviews with pharmaceutical logistics officers and surveys of flood survivors. Secondary data were obtained from the drug stock reports of the Aceh Tamiang District Health Office. Analysis was conducted on variables such as drug types, stock amounts (Buffer Stock), and distribution channels during the emergency response period. The results of the study indicate that the availability of drugs in the initial disaster phase tends to be (state the prediction, e.g., sufficient/limited). However, accessibility is often hindered by damaged road infrastructure and uneven distribution to remote posts. There is an urgent need to strengthen the logistics early warning system so that the types of medicines available match the disease patterns that emerge after floods. Although medicine stocks are generally available in central pharmacy warehouses, geographical constraints and distribution coordination are the main factors hindering accessibility. It is recommended that local governments map out alternative distribution routes and provide disaster-specific buffer stock of medicines at the sub-district level.

Islamic character education has become a central focus of madrasah education; however, its planning is often implemented normatively without adequate managerial and evaluative mechanisms. This study aims to analyz ethe planning of Islamic character educationatMTs Persis 23 by examining the alignment betweent he madrasah’s strategic direction, curriculum, instructional practices, habituation programs, and character evaluation. Using a qualitative case study approach, data were collected through document analysis, classroom and school observations, and in-depth interviews with the head of the madrasah, the vice principal for curriculum, and home room teachers. Data were analyzed thematically to identify patterns of planning, implementation, and evaluation. The findings reveal that the madrasah has established a strong strategic foundation for character education through its vision, mission, and religious school culture, positioning character development as a core educational objective. Character values are integrated in to the Madrasah Operational Curriculum, lessonplans, and daily habituation activities functioning as a hidden curriculum. Nevertheless, the planning of character education remains weak at the operational level, particularly due to the absence of m easurable behavioral indicators, standar dizede valuation instruments, and systematic documentation of students’ character development. This study highlightsthe gap between normativ estrategic intentions and managerial implementation. It recommends the development of simple behavioral indicators, baselineand longitudinal character assessments, ands trengthenedpe dagogical supervision to ensure that character education planning is implemented systematically and sustainably.    

The rapid development of digital technology has accelerated the transformation of business models, particularly within the Micro, Small, and Medium Enterprises (MSMEs) sector. One significant form of this transformation is the adoption of e-commerce as a platform for digital marketing and business transactions. This study aims to analyze the role of e-commerce in increasing the income of MSMEs in Medan Perjuangan District. The research employs a qualitative approach using secondary data obtained from government reports, scientific journals, and relevant previous studies. Data were analyzed through content analysis to identify patterns and key findings related to e-commerce utilization among MSMEs. The results show that the use of e-commerce has a positive impact on MSME income by expanding market reach beyond local boundaries, reducing marketing and operational costs, and improving consumer access and transaction convenience. However, the study also identifies major challenges, particularly limited digital literacy, inadequate technological infrastructure, and low readiness among MSME actors, which need to be addressed to maximize the benefits of e-commerce adoption.

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.  

The Local Currency Settlement (LCS) initiative is a strategic instrument to promote ASEAN regional financial integration while reducing dependence on the US dollar in trade and investment transactions. Sub-regional cooperation between Indonesia, Malaysia, and Thailand has become an important policy arena to test the effectiveness of LCS as part of the implementation of the ASEAN Economic Community (AEC) Blueprint 2025. This article aims to analyze the role, opportunities, and challenges of LCS implementation within the framework of ASEAN financial integration, focusing on the dynamics of cooperation between the three countries. The research uses a qualitative approach through literature review and policy analysis. Data were obtained from official central bank documents, regional cooperation agreements, international agency reports, and academic literature related to financial integration and regional monetary cooperation. The analysis was conducted descriptively and analytically to identify implementation patterns, structural barriers, and policy implications. The results of the study indicate that LCS contributes to increasing the efficiency of cross-border transactions, reducing exchange rate risk, and strengthening sub-regional ASEAN financial cooperation. However, its implementation remains limited due to differences in financial infrastructure readiness, variations in domestic regulations, and low adoption by business actors. This article emphasizes the importance of policy coordination, regulatory harmonization, and private sector involvement to optimize the role of the LCS in supporting ASEAN financial integration.

This article aims to describe the teaching methods and practices of the Philosophy of Islamic Education course at STAI Darussalam. This research uses a qualitative descriptive approach with a field study method that focuses on the learning process, the competencies to be achieved, teaching methods, assignment formats, evaluation systems, and obstacles encountered during the course. Data were obtained through observation and information gathering related to the implementation of the Philosophy of Islamic Education course. The results show that the teaching of the Philosophy of Islamic Education at STAI Darussalam focuses on understanding the nature of Islamic education, developing students' critical thinking patterns, improving educational literacy, and linking philosophical studies to social and political realities. The lecture method remains the dominant method used by lecturers, with an emphasis on students' ability to define and explain basic philosophical concepts accurately as an indicator of understanding. Learning success is measured by changes in students' thinking, which becomes increasingly critical, reflective, and contextual in responding to educational issues and social justice issues.

The era of digitalization demands that the world of education adapt quickly to technological developments. One of the basic skills that elementary school students need to have is the ability to operate a computer, particularly in typing and using word processing applications. Community service research was conducted at the Kemala Bhayangkari Foundation 1 Medan with the aim of improving students' digital literacy thru typing training using Microsoft Word and the interactive media 10fastfingers.com. The training method is conducted using a workshop model, which consists of two main topics. The first material is a basic introduction to typing using the ASDF;LKJ pattern and the use of important keyboard keys. The second material is an introduction to basic Microsoft Word features, such as changing font type and size, using Bold, Italic, Underline, changing text color, and highlighting. Additionally, students are trained to use 10fastfingers.com to interactively improve their typing speed and accuracy. The research instruments are pretest-posttest, observation, and student response questionnaires. The research results show a significant improvement in typing skills. Average speed increased from 8–10 words per minute to 20–25 words per minute, with over 85% accuracy. Student responses were also very positive; they felt more confident, more motivated, and able to use Microsoft Word more effectively. This training program has proven effective in improving digital literacy among elementary school students while also fostering an interest in technology-based learning.

This study develops a computational-based system to identify individual potential through the analysis of signature patterns using Artificial Neural Networks (ANN) and the Backpropagation algorithm. The research aims to explore and examine the effectiveness of applying ANN in recognizing and identifying signature patterns that are assumed to be related to an individual’s potential. In the data processing stage, Principal Component Analysis (PCA) is employed as a dimensionality reduction and feature extraction technique to optimally obtain the main characteristics of signature images. The system performance evaluation is conducted using a total of 80 signature images, consisting of 60 training data and 20 testing data. This study analyzes two network architecture configurations, namely a model with one hidden layer and a model with two hidden layers. The experimental results show that both network configurations achieve the same accuracy level of 92.5%. These findings indicate that the use of Artificial Neural Networks with the Backpropagation algorithm is effective in producing high accuracy in the signature pattern recognition process. Furthermore, the developed system has broad potential applications in the field of personal identification, such as employee evaluation, selection systems, and other applications across various organizational and industrial sectors.

User experience (UX) evaluation plays a crucial role in understanding how users interact with digital platforms and in improving product design. Traditional UX evaluation methods, such as surveys and interaction logs, often rely on a single data source, which limits the depth of analysis. This study explores the integration of multimodal data processing techniques in UX research, aiming to enhance the accuracy and comprehensiveness of UX evaluations. By combining interaction logs, visual attention data, and physiological measurements, this approach provides a more holistic understanding of user behavior, emotional responses, and satisfaction. Interaction logs offer objective data on user actions, while eye-tracking and physiological data capture users' emotional states, providing richer insights into usability and user experience. This study highlights the effectiveness of multimodal integration in identifying patterns that traditional methods overlook, such as emotional responses to interface elements and real-time feedback from users. The findings reveal that multimodal data processing improves the precision of UX assessment by combining objective behaviors with subjective emotional responses, offering a more complete view of user interactions. The study also discusses the challenges of data synchronization and the potential ethical concerns related to the use of physiological data. The integration of these data sources shows great potential for enhancing the design process, allowing designers to make informed decisions based on comprehensive insights. Finally, this research underscores the future potential of multimodal analytics in UX research, suggesting further exploration of additional data modalities and real-time applications in various digital environments.

Sleep is a fundamental biological need for adolescents and plays a crucial role in supporting cognitive function, emotional regulation, and overall mental health. Despite its importance, sleep quality among adolescents has increasingly declined due to the interaction of individual characteristics, social environments, and daily sleep behaviors. This article aims to analyze the factors influencing adolescent sleep quality using the Social Cognitive Theory framework through a literature review of national and international journals published between 2021 and 2025. The findings show that adolescent sleep quality is shaped by personal factors, including attitudes toward sleep, self-efficacy, and psychological conditions. Environmental factors, such as parental support, peer influence, and academic demands, also significantly affect sleep patterns. In addition, behavioral factors, particularly sleep hygiene practices, play a key role in determining sleep quality. Consistently, unhealthy sleep behaviors are associated with poor sleep quality. Therefore, comprehensive interventions are needed, involving the improvement of sleep habits, strengthening adolescents’ self-regulation abilities, and enhancing family and school support to promote better sleep quality.

This study aims to describe the lexical variations that emerge based on gender factor within the sociolinguistic context of SMP Bintang Persada Denpasar. This research employs a descriptive qualitative approach using the observational method and note-taking technique by presenting a list of glosses to 20 eight-grade students, consisting of 10 male and 10 female participants. The lexical data were analyzed using the intralingual and extralingual comparison methods. The findings reveal significant lexical differences between the two speaker groups. Female student tend to use more varied, complete, and expressive lexical forms, including full words and phrasal expressions. In contrast, male students show a tendency to use shorter, more efficient lexical forms dominated by abbreviations and rough expressions. These findings highlight that gender functions as a linguistic marker shaping distinct communicative patterns among adolescents, with female students prioritizing social expression and affection, while male students emphasize practicality and efficiency in language use.

This study explores the role of visual analytics in enhancing decision-making processes within creative industries, focusing on its application to large-scale multimedia datasets. Visual analytics integrates interactive visualization techniques with computational algorithms, enabling users to explore complex datasets intuitively and derive actionable insights. The research centers on the design and implementation of interactive dashboards tailored to the creative sector, particularly film, music, and advertising industries, to facilitate real-time data exploration. The study also investigates the usability of these tools through expert-based evaluations, aiming to assess their effectiveness in supporting informed and timely decision-making. The findings reveal that interactive visualizations significantly improve insight discovery and pattern recognition, enabling decision-makers to uncover hidden trends in large multimedia datasets. However, challenges related to scalability, user acceptance, and real-time processing were encountered during the implementation phase. The research highlights the practical benefits of integrating visual analytics into industry workflows, which include enhanced content creation, audience engagement, and strategic planning. Furthermore, the study identifies key visual analytics techniques such as dynamic dashboards, pattern recognition, data mining, and clustering, which are essential for analyzing multimedia data. The study concludes by emphasizing the potential for wider applications of visual analytics in other sectors, suggesting future research directions to improve tool performance, scalability, and user accessibility, as well as exploring the integration of emerging technologies like artificial intelligence and virtual reality.

This research examines the coordination efforts of the Karanganyar District Disaster Management Agency (BPBD) in managing disasters, identifying obstacles, and exploring efforts to strengthen these coordination efforts. Utilizing a qualitative approach with a case study method, the study aims to investigate the mechanisms of cross-sector coordination, communication patterns, and division of labor within BPBD. Data was gathered through in-depth interviews, observations, and document studies, and analyzed using an interactive model. The findings indicate that BPBD's coordination is relatively effective, demonstrated through unified action, a multi-channel communication system, and a clear division of labor. However, challenges remain, including the complexity of cross-sectoral coordination, differences in capacity and authority, and the pressure of emergency situations. The study concludes that improving coordination requires enhancing staff discipline, developing human resource capacity, and strengthening an integrated work system. These efforts are vital for improving the overall effectiveness of disaster management at the local level, ensuring a more efficient and comprehensive response to disasters in the future.

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.

Malnutrition in children remains a serious public health challenge in Indonesia because it directly impacts growth, cognitive development, and the child's future quality of life. Parents play a crucial role in maintaining children's health, particularly in providing balanced nutrition and preventing nutritional problems such as stunting and malnutrition. This study aims to analyze the role of parents in maintaining children's health due to malnutrition based on a literature review. The method used is a qualitative literature study, through a search of various written sources in the form of scientific journals, articles, and relevant books obtained from Google Scholar. The results of the study indicate that the level of knowledge, education, parenting patterns, socioeconomic conditions, and active involvement of parents in monitoring children's growth significantly influence children's nutritional status and health. Parents play a role as providers of nutritious food, nutrition educators, role models of healthy lifestyles, and regular monitors of children's growth and development. Parents' lack of understanding of balanced nutrition, the habit of consuming instant foods, and minimal participation in health programs are risk factors for malnutrition in children. Therefore, increasing parental education and involvement through a family-based approach is an important strategy in efforts to prevent and address child nutrition problems sustainably.

The rapid proliferation of Internet of Things (IoT) devices across diverse industries has significantly increased the vulnerability of IoT edge networks to sophisticated cyber threats. Traditional intrusion detection systems (IDS), such as signature-based and anomaly-based approaches, are often insufficient in addressing the dynamic and evolving nature of these threats. This study proposes a hybrid intrusion detection system (IDS) framework that combines supervised machine learning (ML) techniques with deep reinforcement learning (DRL) to enhance detection performance in real-time, resource-constrained IoT environments. The proposed framework utilizes supervised learning for initial traffic classification and DRL for adaptive decision-making, enabling the system to continuously learn and optimize its detection policies based on new attack patterns. The hybrid approach significantly improves detection accuracy and reduces false positives when compared to conventional signature-based and single-model ML systems. In addition to improved detection capabilities, the framework's computational efficiency allows it to operate effectively within the constraints of IoT devices, ensuring that it is suitable for large-scale deployments. Benchmark evaluations using publicly available datasets, such as NSL-KDD, IoT-23, and BoT-IoT, show that the hybrid IDS framework outperforms traditional methods, providing a more robust and adaptive solution to cybersecurity challenges in IoT edge networks. The findings of this study suggest that combining machine learning with deep reinforcement learning offers a promising approach to secure IoT environments and address the limitations of existing IDS techniques. Future work will explore enhancing real-time adaptability, scalability, and the detection of zero-day attacks in evolving IoT ecosystems.

This study aims to develop an effective predictive model for identifying students at risk of academic dropout using the Decision Tree and Linear Regression algorithms. The data used are sourced from the public Kaggle dataset Students Dropout and Academic Success, which includes demographic, socioeconomic, and academic performance variables for each semester. The research method includes data preprocessing stages, such as data cleaning, label encoding for categorical variables, numeric feature normalization, and target class adjustment to focus on binary classification, namely Dropout and Graduate. The modeling process is carried out by comparing the performance of the two algorithms using evaluation metrics of accuracy, precision, and recall. The results show that the Decision Tree algorithm has superior performance compared to Linear Regression in mapping non-linear patterns in student data. Feature importance analysis revealed that the number of curricular units in the second semester and tuition payment status are the main predictors of dropout risk. These findings are expected to assist educational institutions in implementing early interventions to improve student academic success.  

Psychological well-being is a fundamental construct in individual development; however, within guidance and counseling practice it is often positioned merely as an indirect outcome of problem-focused interventions. Philosophically and empirically, psychological well-being holds substantial potential to be established as a primary goal of guidance and counseling services. This article aims to examine psychological well-being as an axiological objective of guidance and counseling through a philosophy of science perspective supported by recent empirical evidence. The method employed is a literature review of scholarly publications from the last eight years retrieved through Google Scholar. Eleven relevant articles were selected and analyzed using thematic synthesis to identify conceptual patterns and empirical findings related to psychological well-being in the context of guidance and counseling. The results indicate that psychological well-being is conceptualized as a long-term developmental outcome reflecting holistic human functioning, encompassing dimensions such as autonomy, purpose in life, personal growth, environmental mastery, self-acceptance, and positive relations with others. Various guidance and counseling interventions particularly those based on mindfulness and positive psychology interventions have been empirically demonstrated to effectively enhance eudaimonic well-being. From an axiological perspective, psychological well-being possesses strong value foundations and aligns with the ethical mandate of guidance and counseling to promote optimal human development. This article underscores the necessity of a paradigm shift in guidance and counseling practice, moving from a predominantly problem-oriented approach toward a well-being-oriented framework in which psychological well-being is positioned as a central and explicit goal of professional services.