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Indonesian as the national language of the Indonesian nation is also a language studied in various countries. The Indonesian Language Program for Foreign Speakers (BIPA) is a program aimed at teaching Indonesian to foreign speakers. One of the learning models applied in the BIPA program is the AKIK Learning Model (active, communicative, interactive and collaborative). This research aims to: (1) describe the application of the AKIK learning model in BIPA teaching. (2) Analyzing student responses to the AKIK learning model. (3) Identifying the obstacles faced in implementing the AKIK learning model. (4) Evaluate the results of Indonesian language learning using the AKIK learning model. The research results show that the implementation of the AKIK learning model is effective in improving the communication skills and understanding of Indonesian at Normal University South Luzon students. Students responded positively to the AKIK learning model, feeling more motivated and active in learning. However, several obstacles are faced, such as cultural and language differences and limited learning facilities that support technology. This research contributes to the development of the BIPA curriculum by recommending more effective teaching strategies. The results can be used as a reference for teachers and researchers in the field of foreign language teaching, especially Indonesian.

In the industrial era 4.0 and advanced technology like today, teachers are faced with very tough challenges, especially PAI teachers, whose learning requires a clearer and more concrete picture. In this era, sources of information or learning are very easy to obtain, learning models and media are very innovative and formal education is required to produce quality students. This research is about how the independent learning program and its implementation in PAI learning for class X at SMA Darul Hikmah Burneh Bangkalan , aims to find out about the independent learning program and its implementation in PAI learning in increasing the critical thinking of class X students at SMA Darul Hikmah Burneh Bangkalan . This study uses a descriptive qualitative approach with field study methods and data collection techniques through observation, interviews and documentation. The results of the research on the implementation of the independent learning program in PAI class X at SMA Darul Hikmah Burneh Bangkalan , learning includes 3 aspects (intracurricular, co-curricular and extracurricular). With learning media using teaching modules, power points and computers.  

Improving the quality of learning is something that must be done well in school education, students who have diverse learning styles must be the main factor of teacher attention in order to be able to give meaning to learning well. To improve learning outcomes, one of them is through the application of the quantum learning model in the teaching and learning process. This research aims to find answers to the question of the effectiveness of using quantum learning in schools. Penalitian conducted by reviewing a variety of relevant literature both from journals and direct findings in the field. The results of the study found that the implementation of quantum learning can improve the quality of learning and maximum student understanding, given the different learning styles of students can be facilitated through the implementation of quantum learning models, so that learning styles are very supportive of quantum learning models and get perfect learning outcomes than conventional learning models.    

Religious moderation in early childhood is an effort to instill moderate religious values ​​in children from an early age. These values ​​include an attitude of tolerance, being fair, balance and also an attitude of equality. One way to instill the values ​​of religious moderation in young children is through the habituation method. This research aims to find out how the habituation method is implemented in instilling the values ​​of religious moderation in early childhood at Kartika Kindergarten Banda Aceh. What will be discussed in this research is how to implement the habituation method in instilling the values ​​of religious moderation in early childhood at Kartika Kindergarten Banda Aceh. This research uses descriptive qualitative research. Data collected through interviews and documentation. The data obtained will be analyzed descriptive qualitatively. The research results showed that the forms of implementation of the habituation method in instilling the values ​​of religious moderation in Kartika Kindergarten Banda Aceh were ablution, prayer practice, repeating and memorizing short surahs and daily prayers, introduction to places of worship from various religions. Apart from that, learning is carried out by instilling values ​​such as honesty, courtesy, mutual help and mutual respect. The steps for implementing the habituation method in instilling the values ​​of religious moderation in children at Kartika Kindergarten Banda Aceh include teachers as models, preparing learning tools, involving parents, holding religious activities.

This research describes the application of collaborative learning in Indonesian language courses at universities, identifies its benefits, and identifies the challenges faced in its implementation. This research also aims to formulate solutions that can overcome these challenges, thereby strengthening the effectiveness and success of collaborative learning in the context of teaching Indonesian in higher education. Based on the results and discussion, the conclusion that can be drawn is that collaborative learning has a strong theoretical basis from social constructivism, constructivism, social learning, and cooperative theory (Vygotsky, Piaget, Bandura, Johnson & Johnson). The implementation of collaborative learning provides significant benefits for students and lecturers, including increased motivation, material knowledge, engagement, and better interpersonal relationships. Effective implementation strategies include clarifying learning objectives, forming effective groups, providing structured assignments, facilitating interaction, and providing fair assessments. Further training and provision is needed for students and lecturers in implementing collaborative learning effectively. The development of assessment instruments that are more detailed and sensitive to individual contributions in the group can increase the objectivity of the assessment. Further research is needed to identify more efficient strategies for overcoming challenges in collaborative learning. Stronger support from universities in providing the training and resources needed to optimize the implementation of collaborative learning models  

This research is a conceptual study of the implementation of the Project Based Learning learning model as an effort to grow the character of students according to the 6 dimensions of the Pancasila Student Profile in the independent curriculum. The Project Based Learning learning model is one of the learning models that can foster Pancasila values in students. By using qualitative descriptive methods through library research, this study aims to find out how the implementation of the Project Based Learning learning model as an effort to grow the character of students according to the 6 dimensions of the Pancasila Student Profile in the independent curriculum. The results of this study show that the Project Based Learning learning model is a strategy that is in accordance with the values contained in the Pancasila Student Profile.

This research aims to develop and apply a Convolutional Neural Network (CNN) algorithm to detect handwritten Roman numerals. Handwriting recognition is a classic challenge in the fields of image processing and machine learning, especially for less common characters such as Roman numerals. In this research, we use data augmentation techniques to increase the diversity and number of datasets used in model training, which is expected to increase model accuracy and generalization. The dataset used consists of 1,120 images for testing and 280 images for validation, each of which is divided into 14 classes of Roman numerals I, II, III, IV, V, VI, VII, VIII, IX, X, L, C, D , and M. Image data was created directly using simple software, namely Paint version 6.3. This research uses the Python programming language and Google Colab as a computing platform. Model training was carried out for 300 epochs and showed significant accuracy in the 150th to 300th iteration. The results at the 300th epoch show an accuracy of 0.9607 and a loss of 0.1162. The implementation of this algorithm shows significant potential in practical applications, such as in the fields of education and historical documentation. The conclusion of this research is that data augmentation is an effective technique to improve the performance of CNN models in detecting handwritten Roman numerals.

This research aims to determine various school literacy movement programs in fostering students' interest in reading. This type of research is qualitative (descriptive) research. Data collection techniques use listening and understanding techniques. The data validation technique uses data source triangulation. Data analysis uses data reduction, data display and drawing conclusions. The results of this research show the implementation of the school literacy movement in fostering students' interest in reading with models of implementing the school literacy movement such as adding interesting books, reading activities 15 minutes before learning, utilizing the school environment for literacy movements or reading that is rich in expanding students' knowledge and conducting questions and answers. and convey the material that is understood

This research is a conceptual study of the implementation of the Project Based Learning learning model as an effort to grow the character of students according to the 6 dimensions of the Pancasila Student Profile in the independent curriculum. The Project Based Learning learning model is one of the learning models that can foster Pancasila values in students. By using qualitative descriptive methods through library research, this study aims to find out how the implementation of the Project Based Learning learning model as an effort to grow the character of students according to the 6 dimensions of the Pancasila Student Profile in the independent curriculum. The results of this study show that the Project Based Learning learning model is a strategy that is in accordance with the values contained in the Pancasila Student Profile.

This article is a report study on the development of a learning school management model of Lhokseumawe Sukma National School and the promotion of educational standards with the aim of sustainable educational development. The research focuses on the school profile of Sukma Nation students and the achievements and challenges of the program in its implementation. The study is qualitative and uses survey methods. Information gathered through documents and interviews with relevant authorities, including focus group observations. The study also presents various manifestations of Sukma Bangsa school innovations. The results specifically show that institutional leadership is related to the implementation of five main categories of learning schools, which are personal leadership, shared vision, mental models, situated thinking and group learning. The order of applications according to the system can be seen in the changes in the behavior of the individual regarding information management, information sharing, interpretation and information search. In addition, the student and school management model has become an important part of achieving school effectiveness.

The rapid growth of data-intensive applications has posed significant challenges for classical machine learning (ML) algorithms, particularly in terms of computational efficiency and scalability. This study explores the role of quantum computing in optimizing machine learning performance through the implementation of Quantum Machine Learning (QML), specifically using the Quantum Support Vector Machine (QSVM) model. The research adopts a Design Science Research approach, involving problem identification, model development, system implementation, and performance evaluation. Both classical Support Vector Machine (SVM) and QSVM models are developed and tested using benchmark classification datasets. The results indicate that QSVM outperforms the classical SVM model across multiple evaluation metrics, including accuracy, precision, recall, and F1-score. Additionally, QSVM demonstrates improved computational efficiency by reducing training time, particularly when handling high-dimensional data. These improvements are attributed to the ability of quantum computing to utilize quantum kernel methods and map data into higher-dimensional feature spaces, enabling better pattern recognition and classification performance.  Despite these promising outcomes, the study also identifies several limitations related to current quantum hardware, such as noise, decoherence, and limited qubit availability, which may affect scalability and practical implementation. Therefore, further research is required to enhance quantum hardware reliability and develop hybrid quantum-classical models. In conclusion, quantum machine learning offers a promising solution to overcome the limitations of classical approaches, providing enhanced performance and efficiency for complex data processing tasks in future intelligent systems.

The rapid growth of digital technologies has significantly increased the complexity and frequency of cyber threats, making network security a critical concern in modern information systems. Traditional security approaches, such as rule-based and signature-based systems, are often limited in detecting sophisticated and unknown attacks. Therefore, this study proposes an Anomaly-Based Intrusion Detection System (AbIDS) utilizing machine learning and deep learning techniques to enhance detection capabilities. The research adopts a Design Science Research approach, involving stages of problem identification, data collection, preprocessing, model development, system implementation, and evaluation. Several models, including Decision Tree (DT), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are implemented and compared. The results indicate that deep learning models, particularly LSTM and CNN, outperform traditional machine learning methods in terms of accuracy, precision, recall, and F1-score, while maintaining a lower false positive rate. Additionally, the integration of incremental learning enables the system to adapt to new attack patterns without requiring complete retraining, improving scalability and real-time performance. Despite the promising results, challenges such as computational complexity and false positives remain. Overall, the proposed IDS model demonstrates strong potential as an effective and adaptive solution for enhancing network security in dynamic environments.

This study aims to determine the implementation of blended learning in improving the scientific literacy of SMA/MA students in Indonesia. This research is a type of meta-analysis research. The sample of this research comes from the analysis of 14 articles that have been published from 2017-2022. The sampled articles have been indexed by SINTA, DOAJ, Google Scholar, Scopus and Copernicus. Research sample search through google scolar and sciencedirect. The sampling technique is purposive sampling technique. The data that can be sampled only has a relationship between the independent variable and the dependent variable, namely blended learning and students' scientific literacy. The data analysis technique in this study is a quantitative data analysis technique with SPSS 21 and JSAP applications with a value of sig.0.005. The application is to calculate the value of Effect Size (ES), Mean and Standard deviation (SD). The results of this study concluded that the application of blended learning was able to increase the scientific literacy of SMA/MA students in Indonesia with an Effect size (ES) of 0.494 and an n-Gain of 0.391. So, teachers in the 4.0 revolution era must be able to apply blended learning models to students so that students are able to face current global competitors.

This study explores the integration of predictive analytics into supply chain management within national e-commerce enterprises. Predictive analytics, which utilizes historical data combined with machine learning algorithms, regression analysis, and time series forecasting, has shown significant improvements in operational efficiency. The study focuses on four key areas: demand forecasting, inventory management, transportation optimization, and customer satisfaction. By predicting demand more accurately, e-commerce platforms can reduce stockouts and overstock situations, streamline logistics routes, and lower logistics costs. The implementation of predictive analytics led to a 20% reduction in delivery times and a 15% decrease in logistics costs, thereby enhancing customer satisfaction. However, the study also highlights challenges in integrating real-time data from multiple sources and scaling predictive models across diverse product categories and geographic regions. The results emphasize the need for e-commerce platforms to invest in technology that enables seamless data integration and the development of region-specific predictive models. The findings are compared with industry benchmarks, showing that the improvements in logistics and supply chain performance align with global trends. Based on these results, the study recommends best practices for implementing predictive analytics, including effective data collection, machine learning model training, and scalability considerations. By following these practices, e-commerce companies can optimize their supply chains, reduce operational costs, and increase customer satisfaction, positioning them for greater competitive advantage in the marketplace.

This study is motivated by the limited research on holistic education in developing 21st-century skills to address the challenges of the digital era, despite its significant implications for future human resource quality. The objective of this research is to explore the concept of holistic education based on 21st-century skills and its relevance in the digital era through a literature review approach. The method employed is qualitative, focusing on an analysis of academic literature, including documents, journals, books, and various scholarly sources. The analysis was conducted thematically to investigate the principles, models, and practices of holistic education that support the development of critical thinking, creativity, communication, and collaboration skills. The findings indicate that holistic education can serve as a key approach to prepare younger generations to navigate the complexity of the digital era with adaptive, ethical, and innovative thinking skills. This review enriches the literature on holistic education and highlights the importance of an integrated approach that intertwines cognitive, emotional, social, and technological dimensions within the context of modern learning. Practical implications include recommendations for educators and policymakers to design curricula based on 21st-century skills and integrate digital technologies into building holistic learning processes. This study also offers opportunities for further research on the implementation of holistic education in diverse cultural and geographical contexts.

This research aims to evaluate the effectiveness of the Missouri Mathematics Project (MMP) Learning Model in improving mathematics learning outcomes for junior high school students. This study employs a comparative approach, comparing mathematics learning outcomes between students taught using MMP and those taught using conventional teaching models. Data were collected through hypothesis testing of mathematics learning outcomes for both groups. The data analysis results indicate a significant difference in mathematics learning outcomes between the two groups, with a significance value (sig.) smaller than the commonly used significance level. These findings suggest that the implementation of MMP effectively improves mathematics learning outcomes for junior high school students. The practical implications of these findings are discussed in the context of developing more effective and inclusive mathematics teaching strategies.

This study examines the impact of differentiated learning models in inclusive educational settings, focusing on their effect on student participation, motivation, and academic performance. Differentiated instruction (DI) adapts content, teaching methods, and assessments to meet the diverse learning styles, interests, and abilities of students. Using a mixed methods approach, the research combines quantitative and qualitative data to explore how DI influences engagement and academic outcomes in diverse classrooms. The findings show that DI significantly increased student participation, as lessons tailored to individual strengths encouraged more active involvement. Motivation also improved, with students displaying higher intrinsic motivation when engaging with relevant material at their own pace. Additionally, academic performance improved, especially for students who had struggled with traditional teaching methods. These results suggest that DI is an effective strategy for inclusive education, particularly for students with special educational needs and disabilities (SEND). The study emphasizes the importance of teacher training and ongoing professional development for successful DI implementation. The implications are significant for global educational settings, where classrooms are becoming more diverse. By adopting differentiated strategies, educators can create more equitable and inclusive learning experiences. Future research should explore the long-term effects of DI in various cultural and educational contexts.

The rapid spread of infectious diseases remains a major global health threat, and early detection is vital to minimize their impact. This research investigates the role of predictive modeling using big data in the early detection of infectious disease outbreaks. The primary objective of this study is to assess the effectiveness of big data systems in forecasting potential outbreaks and the implications of these forecasts for public health systems. The study employs machine learning-based predictive models to process large health datasets, including electronic health records, sensor data, and social media information. The results demonstrate that the predictive model achieved an accuracy rate of 87%, significantly surpassing traditional methods in terms of early detection. By integrating various data sources such as medical records, sensor networks, and real-time digital traces, the system is capable of providing more accurate, timely predictions, which can greatly improve the ability of public health authorities to respond effectively to emerging health threats. Furthermore, the application of big data in public health not only improves the speed of response but also enhances the allocation of resources, allowing for more targeted and efficient interventions. Despite these successes, challenges remain, particularly in relation to data quality, privacy, and regulatory issues, which could hinder the broader implementation of such systems. Thus, collaboration between government agencies, healthcare institutions, and technology developers is essential to overcome these obstacles and ensure the sustainable integration of big data into public health infrastructures. This research highlights the significant potential of big data to transform public health responses, offering valuable insights for future epidemic management strategies.  

This research used an experimental design, and the data were processed using SPSS version 25 for Windows, with a sample of 20 Grade V students. Data collection for this research used Pretest, Treatment/Action in the form of implementing the board game "Cultural Exploration of Panrita Lopi". After the action was completed, a Posttest was conducted to measure the students' reading comprehension skills once again. This data was used to compare the results before and after the intervention.The results of the research clearly show that there was a significant improvement in the reading comprehension skills of Grade V students at SDN 131 Bontobana after the implementation of the board game "Cultural Exploration of Panrita Lopi." This indicates that the game can be used as an effective learning tool in improving students' reading comprehension skills.This research can contribute to knowledge in the field of education and learning. Through this research, new information about the use of the cultural exploration game of Panrita Lopi in improving the reading comprehension skills of Grade V students can be collected and presented, thus helping to expand our understanding of effective learning strategies. This research can also provide a better understanding of the relationship between cultural exploration games and reading comprehension skills. The results of this research can be used to develop better theories and learning models that can be used by educators and researchers in the future.

This study examines the impact of blended learning on student engagement and academic achievement in secondary schools during the recovery phase of the pandemic. A quantitative research approach was employed, utilizing a comparative design to assess the differences between blended learning and conventional learning models. Data were collected through student engagement surveys and academic performance records from secondary school students exposed to both learning models. The results indicated that students in the blended learning model exhibited significantly higher levels of engagement across behavioral, emotional, and cognitive dimensions compared to those in the conventional model. Academic achievement was also notably higher in the blended learning group. Statistical analysis, including t-tests and linear regression, revealed a strong positive correlation between student engagement and academic performance. The study concluded that blended learning significantly enhances student involvement and performance, particularly when supported by adequate technological infrastructure and teacher preparedness. These findings suggest that blended learning should be integrated as a permanent strategy in post-pandemic education to support student success and engagement. The study also emphasizes the importance of continuous teacher training and technological support in maximizing the benefits of blended learning.