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This study aimed to develop a flipbook-based multimedia teaching material for the Tennis Learning course. The research employed a Research and Development (R&D) approach using the ADDIE model as the development framework, which consists of five stages: (1) Analysis, (2) Design, (3) Development, (4) Implementation, and (5) Evaluation. The research subjects included students of the Physical Education, Health, and Recreation Study Program, Faculty of Sports and Health, Universitas Pendidikan Ganesha, as well as subject matter experts, instructional design experts, instructional media experts, and field practitioners. The product was evaluated through individual trials (3 students), small group trials (7 students), and large group trials (21 fourth-semester students). The validation results indicated feasibility percentages of 96% from the subject matter expert, 97% from the instructional design expert, 100% from the instructional media expert, and 97% from the field practitioner. Meanwhile, student trial results showed feasibility percentages of 97% in the individual trial, 96% in the small group trial, and 97% in the large group trial. Therefore, the flipbook-based multimedia teaching material on officiating in the Tennis Learning course was categorized as excellent and highly feasible for use as a supporting instructional resource in both classroom and field learning activities.

This study aims to develop flipbook-based multimedia instructional materials for the basic techniques of forehand and backhand volley in the Tennis Learning course. This research employed a Research and Development (R&D) approach using the ADDIE model, which consists of five stages: analysis, design, development, implementation, and evaluation. The validation subjects included a content expert, a learning media expert, an instructional design expert, and a field practitioner. Product trials were conducted with students of the Physical Education, Health, and Recreation Study Program, Faculty of Sports and Health, Universitas Pendidikan Ganesha, through individual trials involving three students, small-group trials involving seven students, and large-group trials involving twenty-one students. Data were collected using questionnaires with rating scales and were analyzed using descriptive qualitative and quantitative analysis in the form of percentages. The results indicated that the content expert validation achieved 98%, the media expert 93%, the instructional design expert 97%, and the field practitioner 98%, all categorized as very good. The individual trial obtained 97%, the small-group trial 98%, and the large-group trial 96%, all classified as very good. Therefore, the flipbook-based multimedia instructional materials on basic volley techniques are considered highly feasible for use as learning resources in tennis instruction.  

This systematic literature review analyzes previous studies on impact of educational technology on students’ behavioural engagement in English language learning. The integration of educational technology in English classroom has increased significantly in order to address students’ low participation, limited attention, and passive learning behaviour. Various digital tools such as digital storybooks, digital storytelling, multimedia learning platforms, and interactive online applications have been implemented to promote students’ active participation. This review followed the prefered Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to ensure a systematic and transparent review process. Relevant journal articles published between 2020 until 2025 were identified through Google Scholar, ResearchGate, and Publish or Perish. A total of 15 articles met the conclusion criteria and were analysed in this study. The findings indicate that educational technology positively influences students’ behavioural engagement, which is reflected in increased participation, attention, interaction, and task completion in English leraning contexts.The review higlights that the appropriate intergration of educational technology can support more interactive and learner-centred English language learning environments.

This study is motivated by the development of digital technology, which has driven a transformation in the learning paradigm from conventional models to more flexible, interactive, and innovative technology-based learning. Changes in student characteristics in the digital era require adaptive learning strategies that are able to improve both the efficiency of the learning process and learning outcomes. This study aims to describe and analyze digital learning strategies in enhancing learning efficiency and their impact on student achievement. The research employs a qualitative approach using a literature review by examining various relevant scientific sources related to the concepts, characteristics, implementation, and impacts of digital learning. The data were analyzed using content analysis techniques to produce a systematic conceptual framework. The findings indicate that systematically designed digital learning strategies can improve conceptual understanding through interactive content delivery, strengthen students’ motivation and independent learning, and enhance retention and learning mastery. Learning efficiency is reflected in flexible access, time optimization, and technology-based assessment. However, its implementation still faces challenges such as limited infrastructure and digital literacy. Therefore, careful planning and the improvement of digital competencies are necessary to ensure that digital learning can be implemented effectively and sustainably in improving the quality of education.

This study aims to analyze how the TikTok and Instagram Reels algorithms play a role in the distribution of multimedia content and their implications for content visibility, user engagement, and digital marketing practices. The research method used is a qualitative approach through a Systematic Literature Review by analyzing articles from accredited national journals and reputable international journals published in the period 2020-2025. The literature search process was carried out systematically through openly accessible scientific databases, then selected using inclusion and exclusion criteria to ensure the relevance and quality of the sources. The research findings show that the TikTok and Instagram Reels algorithms both rely on analysis of user behavior, initial engagement levels, and the characteristics of short-form audiovisual content in determining content distribution. TikTok emphasizes an interest-based recommendation system that allows content from new creators to gain broad reach, while Instagram Reels combines algorithmic recommendations with established social networks. The implications of this study emphasize that understanding the mechanics of algorithms is a strategic factor for content creators, business actors, and digital marketing practitioners in designing effective, adaptive, and sustainable multimedia content distribution strategies.

This study is based on the fact that history learning in secondary schools is still dominated by a memorization-based approach, which does not fully encourage deep understanding or interest in learning among students, while the characteristics of the digital generation demand more interactive, visual, and participatory strategies. This study aims to examine the urgency of utilizing interactive media in history learning, identify relevant forms of media, and explain their implications for the quality of the learning process and outcomes. The method used is a literature study examining various recent studies on the use of interactive multimedia, digital e-books, historical videos and simulations, and educational games in history learning. The results of the study show that the use of interactive media contributes to increasing interest and motivation in learning, strengthening understanding of concepts and the chronology of events, and developing students' critical and historical thinking skills, while encouraging a shift in the role of teachers to become facilitators and innovators of learning. Therefore, its integration needs to be designed in a targeted and contextual manner to be in line with the characteristics of students and the demands of 21st-century learning.

The development of multimedia-based interactive games requires a system capable of effectively managing game logic, character behavior, and the integration of visual and animation elements. This study aims to implement GDScript in the development of a 2D RPG game using the Godot Engine. The research method was carried out through the design of scene and node structures, the implementation of game logic using GDScript, and the application of Finite State Machine (FSM) to regulate enemy behavior. GDScript is used to control character movement, animation systems, and interactions between players and objects in the game. The implementation of FSM allows enemies to have dynamic behavior through state settings such as idle and wander. Functional testing results show that the game system can run according to the design and is capable of producing responsive interactions. In addition, the use of modular architecture in the Godot Engine facilitates system development and maintenance. Based on the research results, the Godot Engine and GDScript are considered effective for developing multimedia-based interactive games.

The interactive learning video innovation "Human Blood Circulation" through Edpuzzle, with embedded questions, is designed to address the difficulties faced by fifth-grade elementary school students in understanding abstract biological concepts. Science education in elementary schools often encounters challenges in explaining invisible processes, such as the heart's working mechanism and blood circulation, leading students to struggle with comprehension or merely memorize the material. Conventional learning videos tend to make students passive, necessitating media that can transform the learning process into an active one. Edpuzzle, as an educational platform, allows teachers to insert questions at critical points in the video, requiring students to answer before continuing to watch. This innovation aligns with the cognitive development stage of fifth-grade students, who are in the concrete operational stage.The research objectives include product development, validity and feasibility testing, analysis of conceptual understanding improvement, influence on focus and learning independence, and student responses. Media development refers to Mayer's cognitive theory of multimedia and the characteristics of interactive videos according to Heinich et al. Additionally, media development models such as ADDIE and Dick and Carey are discussed. The main benefits of using Edpuzzle include increasing engagement, facilitating real-time formative assessment, and enhancing learning motivation. However, challenges exist such as technology access, teacher readiness, the risk of technology dependency, and long-term evaluation. The practical implications can support digital learning and the transformation of elementary science education.

This study was motivated by the low levels of student motivation and cognitive learning outcomes in the Islamic Education (PAI) subject at SMK Pasundan 1 and SMK Bunga Persada Cianjur. The phenomenon was identified through preliminary observations showing that 45% of students scored below the Minimum Mastery Criteria (KKM) and demonstrated low engagement during the learning process. The school’s efforts to improve student motivation and learning outcomes have not been optimal, as teaching methods and media are still largely limited to conventional approaches. Therefore, innovation in learning through the use of technology-based interactive multimedia such as Google Classroom, YouTube, and Quizizz is needed to create more engaging and effective learning experiences. The objectives of this study were to identify: (1) the implementation of Google Classroom, YouTube, and Quizizz multimedia in PAI learning; (2) students’ learning motivation; (3) students’ cognitive learning outcomes; (4) the influence of multimedia implementation on students’ learning motivation; (5) the influence of multimedia implementation on students’ cognitive learning outcomes; and (6-8) the qualitative findings that expand and deepen the quantitative results regarding multimedia implementation, learning motivation, and cognitive learning outcomes at SMK Pasundan 1 and SMK Bunga Persada Cianjur. This research employed a Mixed Methods approach using a sequential explanatory design, combining quantitative and qualitative methods in sequence. Data were collected through questionnaires, interviews, observations, and document analysis.

The study titled “Designing a Web-Based E-Module for Empowering Tenth-Grade Students’ Writing Skills in Descriptive Text” aims to develop a digital learning medium to improve students’ descriptive writing abilities. The research applies a Design and Development (D&D) approach using the ADDIE model, consisting of analysis, design, development, implementation, and evaluation, supported by a descriptive quantitative method. The study addresses limitations of traditional, teacher-centered instruction that relies heavily on printed materials by integrating technology into the learning process. The research begins with an analysis of existing teaching practices and learning resources for descriptive text writing. Based on this analysis, a web-based e-module is designed to provide a more interactive and engaging learning experience. The module includes structured materials such as definitions, purposes, text structures, language features, examples, and practice exercises. The e-module is then implemented in a tenth-grade classroom setting, followed by an evaluation of its effectiveness using quantitative data. The results indicate that the web-based e-module effectively improves students’ descriptive writing skills. Interactive features, including multimedia content, self-paced activities, and immediate feedback, enhance students’ motivation and active participation. Teachers and students report positive perceptions regarding the practicality, accessibility, and usefulness of the e-module. Pre-test and post-test results also show a clear improvement in students’ writing performance. Overall, the study concludes that web-based e-modules are a promising instructional medium for enhancing writing skills and supporting student-centered, technology-integrated English language learning.

Mathematics is a core subject that develops critical thinking skills; however, many third to fifth-grade elementary school students face difficulties with conventional teaching methods that tend to be uniform and less adaptive. This study aims to develop and implement a mobile-based educational game, "Ethno Run," which integrates the Bayesian Knowledge Tracing (BKT) algorithm to provide an adaptive learning experience. The method used is Research and Development (R&D) with the Multimedia Development Life Cycle (MDLC) framework. The system uses BKT to track students' mastery in real-time by analyzing their responses to pre-tests and exercises within the game, which then adjusts the difficulty level and focuses the post-test on areas identified as weak, such as arithmetic operations and geometry. The findings show that this adaptive approach significantly improves learning outcomes, with the average score increasing from 44.33 on the pre-test to 85.33 on the post-test among 30 students. This study concludes that the integration of Artificial Intelligence through BKT effectively personalizes learning, enhances student motivation, and provides data-driven insights for teachers regarding students' progress. The implication of this research is that adaptive game-based learning serves as a feasible interactive solution to bridge the gap in conventional basic mathematics education.

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 study explores the integration of deep learning based approaches in real time video content analysis for intelligent human computer interaction (HCI) in multimedia systems. Traditional video analysis techniques, such as rule-based methods and offline processing, struggle with real time performance and adaptability to complex video data. In contrast, the deep learning model used in this research, particularly Convolutional Neural Networks (CNNs), provides high accuracy in object detection, feature extraction, and real time processing. The integration of CNNs with interactive visualization modules enables dynamic adjustments to video content based on user interactions, ensuring a seamless and engaging user experience. The system was benchmarked in terms of its processing speed, accuracy, and responsiveness, showing significant improvements over traditional approaches in real time video analysis. Moreover, the study demonstrates that combining deep learning with real time visualization enhances the efficiency of interactive multimedia applications, making it suitable for dynamic environments such as surveillance, security monitoring, and interactive media. Despite the system's strong performance, challenges such as computational demands in high-resolution video processing were identified, highlighting the need for further optimization. Future work will focus on optimizing the system for different hardware platforms, incorporating multimodal inputs, and refining deep learning models to address computational bottlenecks. This research contributes to advancing HCI by providing insights into the integration of deep learning for real time video content analysis, which is pivotal for enhancing the interactivity and adaptability of intelligent multimedia systems.

The integration of Augmented Reality (AR) technology into higher education has emerged as a promising approach to enhance collaborative learning experiences. This study aims to design and evaluate an AR multimedia framework that facilitates real time interaction and spatial visualization, creating immersive and engaging learning environments for students. The AR framework was developed with a focus on improving student engagement, collaboration, and learning outcomes through interactive 3D models and real time feedback. By leveraging AR technology, the study sought to address common challenges in traditional learning environments, such as limited student interaction and engagement, and lack of real time feedback. The experimental evaluation involved two student groups: one using the AR-based system and the other using conventional multimedia tools. Findings revealed that students using the AR framework showed significant improvements in engagement, interaction frequency, and collaborative task performance. Additionally, the AR framework contributed to better learning outcomes, including enhanced comprehension, retention of complex concepts, and improved problem-solving skills. The study also highlighted the importance of incorporating a user-centered design approach in developing AR applications to ensure that the system meets the needs and preferences of learners. Qualitative feedback from students indicated that the AR system provided an enriched learning experience, although challenges such as interface navigation were noted. Overall, the study demonstrates the effectiveness of AR in fostering collaborative learning and offers practical insights for its integration into higher education curricula. Future research should explore the integration of AR with other immersive technologies to further enhance collaborative learning experiences.

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.

This research explores the impact of Cache Aware optimizations on signal processing pipelines in High Throughput computing systems. The growing demand for efficient memory management in modern computing systems, especially for data-intensive applications such as artificial intelligence (AI) and multimedia processing, necessitates the development of optimized memory hierarchies. Traditional memory systems often suffer from memory bottlenecks, significantly reducing the performance of these systems. This study investigates how memory hierarchy optimizations, particularly cache line aware optimization, dependency-aware caching, and adaptive cache replacement algorithms, can mitigate these challenges and improve system performance. Through analytical modeling and experimental benchmarking, this work evaluates various memory hierarchy configurations, including processing-in-memory (PIM) and three-dimensional integrated circuits (3D ICs), comparing them to conventional systems. The results demonstrate that Cache Aware optimizations lead to a reduction in memory access latency by up to 30%, while throughput improved by up to 40%. Additionally, cache hit rates increased by 25%, and energy consumption was reduced by up to 20%, highlighting the effectiveness of optimized memory management. The research contributes to the field by providing valuable insights into the design and implementation of efficient signal processing pipelines. It also identifies key challenges, including the need for dynamic occupancy mechanisms and DAG-aware scheduling algorithms, and suggests potential areas for future research, such as the exploration of collaborative caching approaches and further optimization of cache-adaptive algorithms. This work lays the foundation for more efficient, high-performance computing systems that can handle large datasets and complex tasks in real-time applications.

This study explores the integration of adaptive streaming models with edge computing to optimize multimedia delivery, particularly in real-time applications such as video conferencing, live streaming, and virtual reality. The proposed model leverages adaptive compression techniques, including scalable video coding (SVC) and hybrid adaptive compression (HAC), which adjust video quality based on real-time network conditions. The use of edge computing further enhances the model by processing and delivering content closer to the user, reducing latency and optimizing bandwidth usage. The research demonstrates that the edge computing-based adaptive streaming model significantly improves latency by up to 30%, reduces bandwidth consumption, and ensures higher visual quality during video playback, even under fluctuating network conditions. This model addresses key challenges in multimedia streaming, such as maintaining video quality in bandwidth-constrained environments and minimizing buffering times. Furthermore, it enhances the overall Quality of Experience (QoE) for users by providing smoother interactions and real-time responsiveness. The study highlights the potential impact of this model on various fields, including remote education, entertainment, and interactive applications, where low-latency content delivery and high-quality streaming are critical. The findings suggest that integrating AI algorithms for even more efficient compression and expanding edge computing infrastructures will further optimize multimedia streaming in the future, ensuring reliable and high-quality user experiences in increasingly connected environments.

Teaching fiction in Indonesian language classrooms is often constrained by text-centered instruction and limited use of engaging digital media. In the era of Generation Z learners who are visually and digitally oriented, innovative learning materials are needed to enhance motivation, interpretation, and comprehension of literary texts. This study aims to develop and evaluate a Scribus-based digital magazine for fiction learning by integrating the ADDIE model within a qualitative descriptive framework. The research adopted a qualitative descriptive design comprising five stages of the ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. The study was conducted at SMP Negeri 10 Semarang, involving one Indonesian language teacher and fifteen Grade VIII students, who were selected through purposive sampling. Data were collected through observation, interviews, and documentation, and analyzed using the Miles and Huberman model (data reduction, data display, conclusion drawing). Media and content experts conducted validation to assess the feasibility, usability, and pedagogical quality of the content. Findings revealed that the Scribus-based learning media effectively increased students’ engagement and comprehension in analyzing fictional elements such as plot, character, and setting. Expert validation results indicated a high feasibility level, with mean scores above 85% in design and content quality. Teachers reported improved classroom interaction and creativity, while students expressed enthusiasm for the visual and interactive format. The study concludes that open-source tools, such as Scribus, can provide cost-effective and pedagogically sound alternatives for developing literary learning media. The integration of ADDIE and multimodal design promotes contextual, engaging, and sustainable learning experiences. Future research should explore multimedia enhancements, such as audio storytelling and cross-curricular applications, to broaden the pedagogical impact.

Despite its cultural potential, Wetabar Village has not been supported by effective digital promotional media. Information access remains limited, and the lack of interactive promotional platforms has contributed to the low interest of tourists. Current promotional efforts rely heavily on conventional methods, resulting in decreased visitor numbers. The implementation of digital technologies such as Augmented Reality (AR) and Web-based 360° Virtual Reality Tours is considered an effective approach to increasing tourist engagement by offering immersive exploration experiences and interactive cultural content. This research aims to design and implement a web-based tourism promotion media that integrates local cultural content with AR and 360° virtual tour technologies. The development process follows the MDLC research method, utilizing the Lumi H5P platform and PHP for system implementation. The resulting system enables users to digitally explore Wetabar Village through panoramic views and interactive multimedia features. The findings show that the developed application runs smoothly on both Android devices and laptops and is capable of providing hotspot access to operate the virtual reality features. This innovation is expected to enhance tourist interest while supporting cultural preservation and promoting digital transformation within the tourism sector of West Sumba.

Steganography is a technique for hiding secret data within digital media such as images, audio, and video without causing noticeable visual changes. In video media, this technique offers advantages because each frame can be utilized dynamically, resulting in a larger data embedding capacity. However, conventional methods such as fixed-number Least Significant Bit (LSB) embedding still face limitations in balancing visual quality, embedding capacity, and resistance to compression or noise. To address these challenges, this study proposes an Adaptive Video Steganography Method based on Multi-Bit LSB that employs brightness, texture, and motion analysis for each frame to determine the number of embedding bits adaptively. The system adjusts the embedding capacity according to the local characteristics of the video: areas with high texture or rapid motion are assigned more bits, while static or low-texture areas use fewer bits to preserve visual quality. After the embedding process, the video quality is evaluated using PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measurement) to assess its similarity to the original video. Experimental results show a PSNR value of 45.86 dB and an SSIM value of 0.9441, Thus, the proposed adaptive method proves to be efficient, robust against disturbances, and capable of maintaining data security without compromising visual quality, making it highly suitable for implementation in multimedia-based information security systems.