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Polysemy is an important semantic phenomenon in Indonesian language learning in elementary schools because one word form can have more than one interrelated meaning. Understanding polysemy affects students' reading skills, text comprehension, and literacy development. However, studies that specifically examine polysemy in elementary school Indonesian language materials are still limited. This study aims to examine the forms of polysemy, how they are presented in Indonesian language textbooks for elementary schools, and their implications for student understanding. The study uses a qualitative approach with a literature review design. Data were obtained from semantics books and national and international journal articles published between 2017 and 2024 that were relevant to the research topic. Data analysis was conducted using content analysis techniques. The results of the study show that polysemy in elementary school Indonesian language materials appears in the form of context-based, functional, and extended meanings, with a presentation that is not yet fully systematic, thus potentially causing misconceptions and affecting students' reading comprehension.

Polysemy is an important semantic phenomenon in Indonesian language learning in elementary schools because one word form can have more than one interrelated meaning. Understanding polysemy affects students' reading skills, text comprehension, and literacy development. However, studies that specifically examine polysemy in elementary school Indonesian language materials are still limited. This study aims to examine the forms of polysemy, how they are presented in Indonesian language textbooks for elementary schools, and their implications for student understanding. The study uses a qualitative approach with a literature review design. Data were obtained from semantics books and national and international journal articles published between 2017 and 2024 that were relevant to the research topic. Data analysis was conducted using content analysis techniques. The results of the study show that polysemy in elementary school Indonesian language materials appears in the form of context-based, functional, and extended meanings, with a presentation that is not yet fully systematic, thus potentially causing misconceptions and affecting students' reading comprehension.

Working memory (WM) has been extensively studied as a cognitive factor influencing second language acquisition (SLA), but many studies treat it as a static, trait-like capacity. This approach provides limited insight into how WM works across different stages of development, proficiency levels, and learning contexts. This article combines theoretical and empirical research on working memory in SLA from a dynamic and developmental perspective, analyzing how the influence of WM varies over time and interacts with other cognitive and contextual factors. Referencing Baddeley's multicomponent model, complex dynamic systems theory, and longitudinal research, this article examines evidence regarding the role of WM in various language domains, including vocabulary learning, grammar processing, and language production. It also investigates how WM works differently at various proficiency levels and developmental periods, from childhood to adulthood. Evidence suggests that WM plays a very strong role in the early stages of learning when processing is effortful and controlled, but becomes less central as linguistic knowledge becomes automated. The relationship between WM and SLA appears to be bidirectional, with sustained language learning contributing to the development of specific WM components, particularly executive control. The influence of WM varies significantly based on task characteristics, teaching context, and learner profiles. Understanding WM as a dynamic resource rather than a fixed constraint has important pedagogical implications. Instructions that manage cognitive load, provide support, and encourage metacognitive awareness can help learners with diverse cognitive profiles. A developmental approach in WM research requires longitudinal designs and task-aligned methodologies to capture changes over time, thereby advancing theory and practice in SLA.

Instilling local wisdom values in early childhood is crucial for strengthening cultural identity and contextual learning. Learning media based on local wisdom needs to be developed and its effectiveness evaluated in early childhood education. This study aims to evaluate the quality of local wisdom-based instructional media for early childhood education across five aspects: systematics, language, substance, graphics, and usefulness. A descriptive quantitative survey was conducted with 100 early childhood teachers in Surakarta. The instrument was a validated questionnaire using a four-point rating scale. Reliability testing confirmed internal consistency, and ethical protocols (informed consent, anonymity) were observed. The research results show that, Findings reveal that systematics and usefulness scored highest, showing that the media is well-structured and supportive for teaching practice. In contrast, the substance and graphic aspects scored lower, indicating limited content depth and visual quality. Divergent views were noted on the use of foreign terms. Local wisdom-based instructional media is highly relevant and useful, but improvements are required in substance integration and visual design. This study contributes novelty by providing a comprehensive evaluation framework for media grounded in local culture. Practical implications highlight the importance of contextualizing media development for teachers, while future research should examine direct impacts on children’s learning outcomes.

This study examines students’ understanding and application of Qawāʿid al-Fiqhiyyah in their daily muamalah practices and its implications for their ethical behavior. Using a descriptive qualitative approach, the research involved twenty students who provided data through questionnaires, in-depth interviews, and observations. The findings indicate that most students possess a solid understanding of the function of legal maxims as general principles guiding Islamic legal reasoning and as analytical tools for addressing contemporary issues. They are able to apply Qawāʿid al-Fiqhiyyah in various modern activities, such as digital transactions, social interactions, and financial management, which helps them act with greater caution, fairness, and responsibility. Nevertheless, several challenges remain, including difficulties in understanding Arabic terminology, limited contextual examples, and environments that do not always support consistent application. This study concludes that strengthening practical understanding and contextual learning is essential for Qawāʿid al-Fiqhiyyah to function effectively as a moral and Sharia-based guide for students navigating the complexities of modern life.

This research is based on the problem of declining morals of third-grade students at SD IT Baitul Muslim, which has implications for daily behavior, particularly in Pancasila Education learning. Students tend to exhibit attitudes that are inconsistent with positive character values, such as a lack of tolerance and a low sense of love for the homeland. The purpose of this study is to identify the significant influence of educators' roles in shaping the character of third-grade elementary school students in Pancasila Education subjects. The method used is an ex post facto method with a quantitative approach and a purposive sampling design. The study population consisted of 10 educators and 95 students, with a sample of 10 educators and 40 students from two selected classes. Data collection techniques were carried out through questionnaires and documentation that had been tested for validity using Aiken's V and reliability with Cronbach Alpha. Hypothesis testing using simple linear regression analysis showed a significance value of 0.044 which is smaller than 0.05 and a calculated F value of 5.692 which is greater than the F table of 2.27. Thus, the null hypothesis is rejected and the alternative hypothesis is accepted. The research findings confirm the significant influence of educators, particularly as demonstrators, classroom managers, facilitators, and evaluators, in shaping students' character in Pancasila Education. The implication of these findings is that educators need to optimize role models to improve students' character development.

This study is grounded in the issue of low student discipline and learning motivation in elementary schools, which requires teachers to apply more effective and context-based instructional strategies. The purpose of this research is to describe how teachers utilize social learning theory to enhance students’ discipline and motivation, as well as to analyze the impact of these strategies on classroom behavior and student engagement. This research employed a descriptive qualitative approach, with data collected through observations, interviews, and documentation involving teachers and students. The findings show that teacher strategies integrating modeling, positive reinforcement, and collaborative learning successfully create a more conducive learning environment. The use of teacher and peer role models was found to increase compliance with classroom rules, while the provision of positive feedback encouraged students to participate more enthusiastically in learning activities. Moreover, socially interactive learning helped students develop confidence and active engagement. The implications of this study affirm that social learning theory can serve as a strong foundation for teachers to design strategies that promote positive behavior and intrinsic motivation, making it highly relevant for integration into daily classroom practice.

The success of education delivery depends heavily on the quality of supporting elements, particularly educational facilities, which play a strategic role in supporting learning activities and achieving human resource development goals. This research is motivated by a gap in understanding regarding the effectiveness of the management process for facilities and infrastructure in improving learning quality, as well as the need to adapt to the dynamics of modern education. The purpose of this research is to examine the management process for educational facilities and infrastructure and its contribution to improving learning quality, based on the results of a literature review. The method used in this research is a descriptive qualitative approach with a literature review method, where data was obtained through critical analysis of scientific journals and academic literature. The research findings indicate that the management of educational facilities and infrastructure includes the stages of planning, procurement, inventory, utilization, maintenance, supervision, and disposal. Each stage is interrelated and plays a strategic role in supporting a more effective, efficient, and sustainable learning process. The implications of this research indicate that the management of educational facilities and infrastructure, carried out through a planned and sustainable process, plays a crucial role in supporting the improvement of learning quality.    

The increasingly rapid digital transformation demands that MSMEs optimize technology not only in business processes but also in human resource management. Although HR digitalization is believed to improve organizational effectiveness, research on the psychological mechanisms and role of leadership in the context of e-commerce MSMEs is still limited. This study used a quantitative approach with an explanatory survey method and involved 366 respondents from e-commerce MSMEs in various regions of Indonesia. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) techniques to test direct relationships, mediation, and moderation. The results showed that digital HR practices have a positive and significant effect on employee performance. The digitalization of HR functions, such as e-recruitment, e-learning, HRIS, and digital performance management, can improve work effectiveness and the quality of work output. Furthermore, work engagement was shown to mediate this relationship, meaning that employees perform better when they feel more passionate, dedicated, and involved in their work. This mediating role emphasizes the importance of psychological aspects in the successful implementation of digital HR. Leaders who possess a digital vision, provide technological support, and encourage innovation have been shown to increase employee motivation and comfort in working using digital systems. Overall, this study confirms that the success of digital transformation in e-commerce MSMEs is determined not only by the technology used, but also by leadership support and employee engagement. These findings provide important contributions to the digital HR management literature and offer practical implications for MSME owners in increasing competitiveness in the digital era.

Islamic Religious Education (PAI) learning has a strategic role in shaping the character of students who are religious, tolerant, and have noble morals. Amidst the reality of Indonesian multicultural society, PAI learning is required to be able to internalize the values of religious moderation as an effort to prevent extreme, radical, and intolerant attitudes. Religious moderation is an important paradigm in Islamic education to instill a balanced and contextual religious attitude. This proceedings article aims to examine the concept, strategy, and implications of moderation-based Islamic Religious Education learning through the Systematic Literature Review (SLR) approach. The SLR method is used to examine journal articles, scientific books, and proceedings relevant to the topic of PAI learning and religious moderation in the last ten years. The results of the study indicate that moderation-based PAI learning is based on the values of wasathiyah, tawazun, i'tidal, and tasamuh which are integrated into the curriculum, learning methods, and the role models of educators. The implementation of moderation-based PAI learning has a positive impact on the formation of inclusive, tolerant attitudes and the ability to live peacefully together in students. This article is expected to be an academic reference for educators and researchers in developing Islamic Religious Education learning that is relevant to the social challenges and diversity of Indonesian society.

This study aims to analyze in depth the quality of Early Childhood Education (ECE) teachers in the learning process at schools and its implications for early childhood development. The quality of educators is viewed as one of the key factors determining the success of learning implementation and the achievement of educational objectives at the early childhood education level. This study employs a literature review method, which involves collecting various relevant scientific articles, books, and other academic sources related to the research topic, followed by systematic analysis to obtain a comprehensive understanding and conclude the findings. The results indicate that the quality of educators has a significant influence on teachers’ success in performing their roles as facilitators, mentors, and educators in supporting children’s cognitive, social, emotional, and motor development. Therefore, the quality of early childhood educators needs to be continuously developed and improved through education, training, and professional development to maintain and enhance the quality of learning activities in schools. In addition, support from various stakeholders, including the government, educational institutions, schools, and parents, plays a crucial role in efforts to improve the quality of early childhood educators in an optimal and sustainable manner.

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.

Distributed software systems face significant challenges related to data quality due to their complex, decentralized architecture. These systems often involve multiple nodes responsible for processing and storing data, making it difficult to maintain consistency and ensure accurate data across the entire network. In particular, issues like data inconsistency, latency, and data fragmentation are prevalent in distributed environments. To address these challenges, this study proposes an integrated data quality governance strategy that combines real time monitoring and automated anomaly detection using machine learning models. The proposed strategy aims to improve data consistency, enhance anomaly detection capabilities, and reduce the need for manual intervention, ultimately improving overall data governance in distributed systems. Real time monitoring ensures immediate identification of data issues as they occur, while machine learning models, such as autoencoders and Isolation Forests, automate the detection of anomalies based on high reconstruction errors and data isolation techniques. The study evaluates the proposed strategy through real-world distributed system scenarios, comparing its effectiveness to traditional approaches like periodic audits and manual validation. Results demonstrate that the integrated approach leads to faster anomaly detection, reduced data inconsistencies, and improved overall system performance. The use of advanced machine learning techniques and real time analytics significantly enhances the system's ability to maintain high data quality standards across multiple distributed nodes. This strategy has wide-ranging implications for industries that rely on distributed systems, such as finance, healthcare, and IoT, where data integrity is essential for operational success. Future research can focus on integrating more advanced machine learning techniques and optimizing the real time monitoring framework to handle larger and more complex systems.

Explainable Artificial Intelligence (XAI) has become a critical area of research within artificial intelligence, focusing on improving the transparency and interpretability of machine learning (ML) models, often referred to as "black-box" models. The need for XAI techniques arises from the inherent complexity of ML models, which can make their decision-making processes difficult for users to understand. This study investigates various XAI techniques, including LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations), to assess their impact on model interpretability without significantly compromising predictive performance. A comparative experimental design was used, applying these XAI methods to different ML models, including deep neural networks and ensemble methods, within large-scale enterprise data analytics systems. The results indicate that XAI methods significantly enhance model transparency and decision traceability, allowing users to understand the influence of individual features on predictions. While a slight reduction in predictive accuracy was observed, especially with simpler models, the trade-off between interpretability and performance was deemed acceptable, particularly in fields requiring transparency, such as healthcare, finance, and autonomous systems. The use of XAI in enterprise data systems has practical implications for fostering trust and enabling informed decision-making among stakeholders. Furthermore, the study discusses the challenges and limitations of applying XAI techniques, such as complexity, scalability, and model-specific limitations. Future research is suggested to focus on developing more scalable and efficient XAI methods, enhancing their applicability across various model types, and addressing the challenges of real-time applications. This will be crucial in ensuring the widespread adoption of XAI in critical domains, promoting the ethical use of AI while maintaining predictive accuracy.

The high unemployment rate in Indonesia highlights the importance of enhancing work readiness among young people from an early educational stage. Work readiness is influenced by several factors, including learning motivation, communication skills, and parental support. This study aims to examine the relationship between learning motivation, communication skills, and parental support with work readiness among twelfth-grade students at SMAK Kasih Anugrah. This research employed a quantitative approach with a cross-sectional design. The population consisted of all 30 twelfth-grade students, and a saturated sampling technique was applied. Data were collected using structured questionnaires and analyzed through univariate and bivariate analysis using the Chi-Square test. The results indicate a significant relationship between learning motivation and work readiness (p-value = 0.021), communication skills and work readiness (p-value = 0.014), and parental support and work readiness (p-value = 0.005). These findings suggest that learning motivation, communication skills, and parental support play a crucial role in improving students’ readiness to enter the workforce. The results of this study are expected to provide practical implications for schools and parents in strengthening students’ preparation for the world of work

  Abstract. This study aims to develop and evaluate an artificial intelligence–based expert system to support fault diagnosis in Air Handling Units (AHUs). Early fault identification in AHU systems is often constrained by reliance on technician experience, which may lead to inconsistent diagnostic outcomes. The proposed system is intended to provide a consistent, explainable, and practical decision-support tool to assist maintenance personnel, particularly less-experienced technicians, in identifying AHU faults accurately. Methodology: The research adopts a rule-based expert system approach using forward chaining inference. Knowledge acquisition was conducted through structured interviews with experienced HVAC technicians and supported by technical documentation. The resulting knowledge base consists of observable symptoms, diagnostic rules, and corresponding corrective actions. The system was implemented as an Android-based mobile application to enable direct field usage. System validation was performed using real operational fault scenarios, with expert diagnoses serving as the reference standard. Findings: Evaluation results indicate full agreement between the system-generated diagnoses and expert assessments across all tested scenarios. This demonstrates that the proposed system is capable of producing accurate and consistent diagnostic outcomes within its defined knowledge domain. Implications: The system operates using deterministic rules without incorporating uncertainty modeling or probabilistic reasoning. Additionally, validation was limited to a finite number of real-world scenarios, which may affect generalizability to broader AHU configurations. Practical implications: The expert system can be utilized as a practical diagnostic aid in routine AHU maintenance, improving response time, diagnostic consistency, and technician training effectiveness. Originality: This study contributes a mobile-based, explainable expert system specifically tailored for AHU fault diagnosis, emphasizing practical deployment and rule transparency rather than data-intensive learning models.

This study examines deep learning as an educational approach within the Indonesian education system by exploring its conceptual foundations, policy frameworks, and practical implementation. The background of the study arises from ongoing challenges in Indonesian classrooms, where teacher-centered instruction and surface learning practices remain dominant, limiting students’ critical thinking, engagement, and real-world application of knowledge. The study aims to analyze how deep learning, characterized by mindful, meaningful, and joyful learning, is conceptualized in educational theory, reflected in national education policies, and implemented in classroom practices. Using a qualitative literature review method, data were collected from peer-reviewed national and international journal articles, academic books, and research reports related to deep learning in education. The data were analyzed through thematic synthesis to identify patterns concerning implementation strategies, learning outcomes, and implementation challenges. The findings indicate that deep learning contributes positively to students’ cognitive development, motivation, engagement, and 21st-century skills, particularly critical thinking, collaboration, and creativity. However, its implementation in Indonesia faces several obstacles, including limited teacher competence, inadequate assessment systems, insufficient contextual learning materials, and unequal technological infrastructure. The study concludes that successful deep learning implementation requires integrated policy support, continuous teacher professional development, contextualized curriculum design, and equitable access to learning resources. These findings provide practical implications for educators, curriculum developers, and policymakers in strengthening sustainable and humanistic education in Indonesia.

This research is motivated by the importance of studying characterization in novels as a means of understanding human values ​​and character education relevant to social reality. Tere Liye's novel "Moga Bunda Disayang Allah" presents characters with complex characters that reflect empathy, compassion, and struggles facing limitations and social stigma. This study aims to comprehensively describe the characterization contained in the novel. The method used is a qualitative descriptive method with a structural literary analysis approach, specifically Nurgiyantoro's characterization theory. The research data, consisting of narrative excerpts and dialogues depicting the characters' characters, were collected through reading and note-taking techniques. Then, they were analyzed based on the categories of main and supporting characters, protagonist and antagonist, simple and round characters, static and developing characters, and typical and neutral characters. The results show that this novel displays diverse and dynamic characterization, with most of the characters experiencing significant character development and playing a crucial role in conveying moral values. The implications of this research are expected to enrich the study of Indonesian literature and be used as an alternative teaching material in character education-based literature learning.

This study's objective is to describe the implementation of teaching modules as a Christian Religious Education learning strategy at Palangka Raya Christian High School. Teaching modules are used as learning tools in the Merdeka Curriculum to help teachers design structured, contextual, and student-centered learning. Seventeen students in the tenth grade served as research subjects for this study, which employed a descriptive qualitative method. Data collection was carried out thru observation of the learning process, analysis of learning documents, and evaluation results of student learning. The study's findings show that the implementation of teaching modules is able to support the systematic implementation of learning, increase students' active participation in discussions and group activities, and help achieve fairly good assessment results. Nevertheless, some constraints were found in the implementation of learning, such as time limitations and supporting facilities. Overall, the implementation of the teaching module has positive implications for improving the quality of the Christian Religious Education learning process and outcomes, and has the potential to be developed sustainably to shape students' character based on Christian values.  

Abstract: Character education has become a critical challenge in secondary education, particularly in learning contexts that emphasize cognitive achievement over affective and behavioral development. Although Project-Based Learning (PjBL) is widely recognized for its potential to foster collaboration and responsibility, character outcomes are often treated implicitly and rarely evaluated systematically. This study aims to develop and evaluate a character-oriented Project-Based Learning framework using a Design-Based Research (DBR) methodology in Islamic secondary education. The research was conducted through iterative design cycles involving problem analysis, instructional design, implementation, evaluation, and refinement. Explicit character indicators were embedded into each phase of the PjBL process and assessed using quantitative and qualitative instruments. Statistical analysis of pretest and posttest data revealed significant improvements in students’ character-related outcomes following the implementation of the proposed framework. Qualitative findings further indicated enhanced student engagement, collaboration, and social responsibility during project activities. The results demonstrate that integrating explicit character indicators into PjBL through a DBR approach enhances the effectiveness of character education beyond conventional instructional practices. This study contributes to the literature by providing a structured and empirically validated framework that bridges Project-Based Learning, Design-Based Research, and character education. The proposed framework offers practical implications for educators seeking to integrate affective learning objectives into active learning environments.