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This Research and Development (R&D) study aimed to develop a project-based learning (PjBL) hyper-content e-module to support students’ Self-Regulated Learning (SRL) in higher education. Utilizing the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation), the research addressed the need for innovative digital resources in the Learning Resource Center Management Course at Educational Technology Study Program Lambung Mangkurat University. Unlike previous studies that focused on isolated variables, this research integrates development, PjBL implementation, and SRL impact analysis. The hyper-content e-module incorporates multimodal features, including audio, video, infographics, and QR codes, to facilitate independent exploration. Validation by experts yielded high feasibility scores: 89% from material experts, 87% from media experts, and 88% from instructional design experts. Through qualitative content analysis conducted during the analysis and evaluation phase, the results confirmed that the PjBL-integrated e-module effectively improved students' learning independence by providing structured, project-oriented digital pathways. The results confirm that the e-module is a feasible and effective tool for modernizing instructional delivery. This study contributes an innovative framework for digital resource management and provides a foundation for future applied research in enhancing educational quality through self-regulated, technology-enhanced learning environments.

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.

This study aims to describe in detail the implementation of the SMART-TENDIK PAUD innovation as a model for managing educators and educational personnel based on reflection, collaboration, and the use of simple technology, as well as to analyze its impact on improving teacher professionalism in early childhood education settings. This study employs a qualitative approach using a literature review method to explore relevant theories and previous research findings. Data collection techniques include document analysis and systematic online searches from various credible academic sources. Data analysis is conducted through the stages of data reduction, data display, and conclusion drawing to ensure comprehensive and accurate interpretation. The results indicate that the implementation of SMART-TENDIK PAUD enhances teachers’ reflective awareness, strengthens collaboration through active participation in learning communities, and improves the effectiveness of educational personnel management through the practical use of simple and accessible technology. Furthermore, this innovation contributes significantly to improving the quality of learning, making it more creative, adaptive, and innovative. Therefore, SMART-TENDIK PAUD can serve as an alternative model of effective, applicable, and sustainable management innovation in enhancing the professionalism of early childhood education teachers.

The rapid development of information technology has provided significant opportunities to improve the efficiency of academic administration in schools. One of the common problems faced by educational institutions is the manual process of subject scheduling, which is time-consuming and prone to schedule conflicts among teachers, classes, and learning time. This problem is also experienced by SMPK Flos Carmeli, where the preparation of subject schedules has not yet been supported by an integrated computerized system. This study aims to design and develop a web-based subject scheduling application at SMPK Flos Carmeli using the Model–View–Controller (MVC) architecture. The research method employed is Research and Development (R&D) with the Waterfall software development model, which includes the stages of requirements analysis, system design, and application implementation. Data were collected through interviews, observations, and literature review to obtain system requirements that align with the school’s conditions. The application was developed using native PHP with the implementation of the MVC pattern to produce a structured, maintainable, and flexible system. The results show that the developed application is able to support the subject scheduling process in a faster, more accurate, and well-organized manner. The system provides features for managing teacher data, class data, time slots, schedule arrangement, and schedule printing, thereby minimizing schedule conflicts and improving the efficiency of school administrative work. Therefore, this subject scheduling application is expected to support the digitalization of academic administration and enhance the effectiveness of the teaching and learning process at SMPK Flos Carmeli.

This study conducts a qualitative literature review on students' awareness in following school rules as a reflection of high internal motivation forming self-discipline without pressure, and examines the influence of time management discipline on the effectiveness of achieving Islamic Education learning outcomes. The analysis reveals that awareness in following rules develops through a long process of value internalization, starting from external compliance due to fear of punishment, shifting to compliance due to understanding the benefits of rules, and finally reaching a stage where rules are followed because their values have merged with self-identity. Factors such as dialogical rule socialization, teacher role modeling, conducive social environment, educational sanction systems, and consistent implementation significantly determine the success of this internalization. Meanwhile, time management discipline significantly influences the effectiveness of Islamic Education learning outcomes. Students with time management skills can organize study schedules, allocate time for reflection and appreciation of religious material, and consistently perform worship. The impact is seen not only in cognitive aspects through academic grades, but also in affective aspects through religious awareness and psychomotor aspects through regular worship behavior. These findings imply the need for schools to shift disciplinary development paradigms from authoritarian approaches focused on supervision and punishment toward humanist approaches focused on value internalization.

Physics learning requires students’ multirepresentational ability to understand concepts through verbal, mathematical, pictorial, or graphical forms. However, instruction at SMAN 1 Natal is still dominated by conventional methods, resulting in less active student participation and low multirepresentational skills. This study aims to determine the improvement of students’ multirepresentational ability after the implementation of the Problem Posing learning model on the topic of sound waves. The research employed a quantitative approach with a quasi-experimental design. The sample consisted of class XI MIPA 1 as the control class and class XI MIPA 2 as the experimental class. The research instrument was a multirepresentation test administered through pre-test and post-test. Data were analyzed using the Shapiro–Wilk test, the Mann–Whitney test, and the N-Gain test. The results of the normality test indicated that the data were not normally distributed; therefore, hypothesis testing was continued using the Mann–Whitney test, which yielded a significance value of 0.00 < 0.05. This result indicates a difference in the improvement of multirepresentational ability between the experimental and control classes. The N-Gain result for the experimental class was 49.40%, categorized as moderate. Thus, the implementation of the Problem Posing learning model in the experimental class resulted in an improvement that was lower than that of the control class

Tafsir tarbawi is an approach to interpreting the Qur’an that emphasizes the extraction of educational values to shape holistic human character. This study aims to analyze the implementation of tafsir tarbawi in the process of Islamic education and examine its relevance in shaping students’ character in the modern era. The research employs a qualitative method with a library research approach, where data are collected through the analysis of various academic sources such as books, scholarly journal articles, and relevant previous studies. The findings indicate that tafsir tarbawi can be effectively implemented through the integration of Qur’anic values into educational curricula, the application of value-based learning methods, and the reinforcement of teachers’ exemplary behavior as role models. Furthermore, this approach encourages the internalization of spiritual, moral, and social values within students. Therefore, tafsir tarbawi plays a strategic role in developing learners who are not only intellectually competent but also possess strong character, noble morals, and the ability to face life’s challenges wisely.

This study aims to describe the implementation of innovative learning strategies through the Game-Based Learning (GBL) model to enhance the active participation of tenth-grade students in Islamic Religious Education (PAI) at MA Hasyimiyah. The research is motivated by the prevalence of conventional teacher-centered learning, which results in low student engagement and enthusiasm. Employing a descriptive qualitative approach with a case study design, the research subjects included tenth-grade students at MA Hasyimiyah and Field Experience Practice (PPL) students as key informants who conducted the lessons directly. Data collection techniques included classroom observations, semi-structured interviews with PPL students, and documentation gathered during a one-month PPL period. The results indicate that the application of the GBL model utilizing digital media such as Quizizz, Wordwall, Zep Quiz, and Spinner, as well as manual media like question-and-answer cards, significantly increased learning motivation, classroom interaction, and active participation. This improvement was evidenced by students' increased confidence in expressing opinions and intensive involvement in group discussions. Although challenges such as limited infrastructure, unstable internet connections, and restricted student device access were identified, these obstacles were effectively overcome through adaptive strategies by PPL students, who modified digital games into manual formats. This study confirms that innovative and adaptive learning strategies play a crucial role in enhancing student participation levels, particularly within the context of schools with limited facilities.

The development of the digital era demands that youth possess practical and applicable information technology (IT) skills to enhance competitiveness in the workforce and entrepreneurship. However, the gap between theoretical knowledge and basic technical skills—such as computer assembly, installation, and troubleshooting—remains a real challenge among youth, particularly in community settings such as the Patitech Academy in Pati Regency. The training program was implemented using experiential learning methods and a participatory approach over three days. A total of 25 participants engaged in a series of activities, including socialization, technical training, intensive mentoring, and evaluation. Measurement instruments included written pre- and post-tests, practical performance observation, and satisfaction questionnaires. Data analysis showed a significant improvement in participant competencies. The average post-test score increased by 40.2% compared to the pre-test, with 85% of participants demonstrating mastery in assembling computers, installing operating systems, and performing basic troubleshooting independently. The troubleshooting aspect recorded the highest increase (45%). The success of the program was supported by direct learning methods, an ideal participant-instructor ratio, and a curriculum relevant to industry needs. Hands-on training proved effective in significantly improving youth technical IT competencies. The program not only built hard skills but also increased participants' self-confidence and independence. For sustainability, it is recommended to develop advanced modules, strengthen industry networking, and establish a digital alumni forum. The findings of this study can serve as a model for developing youth empowerment programs based on digital skills in other communities.

This study aims to identify students' learning obstacles in the process of understanding one-variable linear equations in grade VII, develop an appropriate learning trajectory using a Realistic Mathematical Education (RME) approach, and produce an effective learning design to reduce these obstacles through generative models. The research adopts a design research methodology consisting of three main stages. The first stage, preparation for the experiment, includes a literature review and analysis of teachers’ instructional practices to develop a Hypothetical Learning Trajectory (HLT) for one-variable linear equations. The second stage, design experiment, involves testing the designed learning activities through a pilot experiment and teaching experiment. The third stage, retrospective analysis, compares actual classroom observations with the initial HLT to refine and validate the learning trajectory. The research subjects include seven grade VII students in the pilot experiment and 44 students from SMP Negeri 2 Mataram in the teaching experiment. Data collection methods include tests, observations, interviews, and documentation, with retrospective analysis used to generate a validated Local Learning Trajectory (LLT). The findings reveal several epistemological obstacles experienced by students, such as difficulties in applying fundamental arithmetic concepts (addition, subtraction, multiplication, division) within the context of linear equations. Students also struggled with concept recognition, representation, and interpretation of linear equations in various forms. The developed LLT proved effective, as students demonstrated improved understanding and were able to follow the learning sequence meaningfully. Retrospective analysis confirmed that the LLT successfully addressed and reduced students’ learning obstacles in mastering one-variable linear equations.

Oral communication is a core competency in 21st-century education; however, instructional materials in elementary schools tend to emphasize reading and writing rather than structured speaking practice. This gap highlights the need for innovative learning resources that explicitly foster students’ oral communication skills. This study aimed to develop and evaluate a Project-Based Learning (PjBL) module designed to enhance the oral communication skills of fourth-grade elementary school students. The research employed a Research and Development (R&D) approach using the ADDIE model, encompassing analysis, design, development, implementation, and evaluation stages. The participants were 30 fourth-grade students, and the developed module was validated by three experts in material, media, and language. Data were collected through validation sheets, teacher and student response questionnaires, and pretest–posttest performance assessments.The expert validation results indicated high feasibility, with scores of 95% (material), 94% (media), and 96% (language), yielding an overall average of 95%. Teacher and student responses demonstrated strong practicality (92% and 88%, respectively; average 90%). The effectiveness test revealed a significant improvement in students’ oral communication performance, with mean scores increasing from 67 (pretest) to 86 (posttest), resulting in an N-Gain of 0.65, categorized as moderately high effectiveness. These findings suggest that the developed PjBL module is feasible, practical, and effective in improving elementary students’ oral communication skills. The study contributes to the field of communication-oriented instructional design by demonstrating how structured project-based modules, supported by simple digital enhancements such as QR-linked instructional videos, can systematically integrate speaking practice into Indonesian language learning at the primary level.

This study aims to develop an Indonesian traffic sign detection system using a transfer learning approach to improve road safety and traffic efficiency. The dataset was obtained from Kaggle and consists of 2,100 images across 21 traffic sign classes. The research stages include data collection, preprocessing to reduce noise and normalize image brightness, object detection using YOLOv5, and classification based on transfer learning with ResNet, VGG-16, and MobileNet architectures. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. Experimental results indicate that the YOLOv5 model is capable of detecting traffic sign objects; however, the classification performance remains relatively low, with a mean Average Precision (mAP) value of 0.17. These findings suggest that further optimization is required in data preprocessing, dataset quality, and model parameter tuning to achieve better performance. This study demonstrates that transfer learning has significant potential for developing computer vision-based traffic sign detection systems, although further improvements are necessary to ensure robustness under real-world Indonesian traffic conditions.

This study aims to examine the effect of the Jigsaw learning model on X grade students of the Electrical Installation Engineering program at SMKS Raden Paku, enhanced with the use of the Kahoot! platform. The research employs a quantitative method with a quasi-experimental design and a nonequivalent control group design. The subjects of the study were divided into two groups: the control group, which applied the Jigsaw learning model using PowerPoint media, and the experimental group, which applied the Jigsaw model using the interactive Kahoot! media. Data were collected through pretest and posttest, as well as observation sheets to assess students' learning outcomes in the affective and psychomotor aspects. Data analysis techniques included normality test, homogeneity test, paired sample t-test, independent sample t-test, and normalized gain (N-Gain) analysis. The findings showed that the average learning outcomes difference between the control group (71.5%) and the experimental group (72.3%) was in the moderately effective category. However, the use of the Jigsaw learning model with Kahoot! had an effect on student learning outcomes, but the influence was not very large. This study provides insights into the effectiveness of using Kahoot! in the Jigsaw learning model.

This study aims to evaluate the effectiveness of the Structural Analytic Synthetic (SAS) method in enhancing the early reading skills of first-grade students in Catholic Religious Education at SD YPPK Yohanes Paulus II Obaa, Mappi Regency, South Papua Province. The study employed a Classroom Action Research approach using a cyclical model comprising the stages of planning, implementation, observation, and reflection, conducted over two cycles. The research subjects consisted of 25 students, and data were collected through reading tests, classroom observations, and documentation. The results indicated a significant improvement in students’ early reading skills, with learning mastery increasing from 61% in the first cycle to 100% in the second cycle. This success was associated with the implementation of the SAS method through structured learning stages, progressing from sentences to words, syllables, and letters, accompanied by the use of varied media and intensive teacher guidance. In addition to improving reading skills, the SAS method was also found to enhance students’ interest, participation, and learning motivation. Therefore, the SAS method is recommended as an effective strategy for teaching early reading to young elementary school students, particularly within the context of Catholic Religious Education.

Flood disasters that struck Cikahuripan Village significantly affected the physical, psychological, and learning motivation conditions of elementary school students, particularly at SD N 1 Cikahuripan. In the post-disaster period, students experienced a decline in learning motivation caused by psychological trauma, loss of a sense of security, and limited learning facilities. This Community Service Program (Pengabdian kepada Masyarakat/PkM) aimed to restore students’ psychological conditions while strengthening their learning motivation through an integrated psychosocial and pedagogical approach. The implementation methods included an initial assessment of students’ conditions, trauma healing activities based on play therapy, and the application of Fun Learning methods combined with the “Tree of Dreams” activity to rebuild students’ intrinsic motivation. The program was conducted from 15 to 22 November 2025 and involved 31 elementary school students as well as teachers as sustainability partners. The evaluation results showed significant positive changes, indicated by increased cheerfulness, active participation, confidence in social interaction, and improved learning focus among students. In addition, teachers’ capacity to implement trauma-sensitive teaching practices also improved. This program demonstrates that post-disaster learning motivation recovery requires a holistic approach integrating psychological and academic recovery, and it has the potential to serve as a replicable model for educational interventions in disaster-prone areas.

Household plastic waste remains a serious challenge in urban environments, including Jl. Assofa II, Kebon Jeruk, West Jakarta, which is characterized by high population density and intense socio-economic activities. The low level of public awareness in sorting and managing plastic waste, particularly bottle caps, highlights the need for educational approaches from an early age. This community service activity aimed to enhance environmental awareness, creativity, and character development among children through the “Recycled Keychain” project, which involved recycling plastic bottle caps into keychains. The activity was implemented using a Project-Based Learning (PjBL) approach and involved 12 children aged 7–9 years as the main participants. The implementation methods included education on waste management based on the principles of reduce, reuse, and recycle (3R), collection and sorting of bottle caps, and the process of creating creative products. The results showed an increase in children’s environmental awareness and environmentally responsible behavior, the creation of eco-friendly educational products, as well as improvements in creativity, motor skills, and teamwork abilities. In addition, this activity supported the strengthening of the Pancasila Student Profile, particularly in the dimensions of cooperation, critical thinking, creativity, and independence. Overall, the Recycled Keychain project proved to be an effective model of contextual, participatory, and sustainable environmental education in instilling environmental care values from an early age in urban communities.

Rainfall is a crucial factor in the stability of the Earth's ecosystem and has a significant impact on agriculture, forestry, energy, and water management. However, increasingly unstable climate change makes rainfall patterns difficult to predict accurately using traditional methods. The city of Medan, the capital of North Sumatra Province, has a tropical rainforest climate with an average annual rainfall of approximately ±2200 mm and an average temperature of 27°C. Significant weather fluctuations in this area can trigger flooding when rainfall increases and cause water shortages when rainfall decreases (BMKG, 2021). Therefore, a prediction approach that can manage non-linear and dynamic data is needed. Artificial Neural Networks (ANN) are one of the reliable machine learning methods for detecting data patterns. By using the backpropagation algorithm, the model can gradually reduce prediction errors, making it widely used in weather forecasting applications. In this regard, this study uses ANN with the backpropagation method to forecast monthly rainfall in Medan City by utilizing data from 2022–2024 as training and testing data.

The development of academic writing skills among university students remains a serious challenge in higher education, particularly in Indonesian language courses that are often perceived as theoretical and procedural. This study aims to reconstruct Indonesian language learning through an Outcome Based Education (OBE) approach to strengthen students’ scientific writing skills at Universitas Muhammadiyah Maumere. Employing a qualitative research design, data were collected through classroom observations and in-depth interviews with students and lecturers over a three-week period. The findings reveal that OBE based learning encourages clearer learning objectives, increases students’ awareness of academic writing standards, and fosters reflective and critical writing practices. Students demonstrated improved understanding of scientific text structures, argument development, and academic language conventions. Furthermore, the learning process shifted from teacher centered instruction to a more participatory and student oriented model, allowing students to actively construct knowledge through observation, discussion, and writing practice. The study also highlights that the integration of contextual learning and continuous feedback plays a crucial role in enhancing students’ confidence and motivation in academic writing. These findings imply that OBE based Indonesian language instruction can serve as an effective pedagogical strategy to cultivate academic literacy, critical thinking, and responsible scholarly attitudes among university students. The study recommends broader implementation of OBE principles in language education to support sustainable improvement in higher education learning outcomes.

This study is motivated by the increasing need for accurate modeling and classification of one-dimensional signal data in intelligent systems. The rapid development of deep learning has led to the adoption of more adaptive and complex neural network architectures capable of capturing both temporal dependencies and local patterns in sequential data. This research aims to analyze and compare the performance of several deep learning models, namely Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid Convolutional Neural Network–GRU (CNN–GRU) model for signal data classification. The research method employs a quantitative experimental approach involving data preprocessing, windowing, model training, and performance evaluation. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the hybrid CNN–GRU model outperforms the other models, particularly in capturing local features and long-term temporal dependencies within signal data. These findings suggest that the integration of convolutional layers and recurrent mechanisms enhances feature representation and learning stability. This study is expected to contribute both theoretically and practically to the development of deep learning models for signal processing and time-series-based intelligent applications.

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.