Publication Search

The limited use of interactive learning media has made it difficult for students to visualize the functions and assembly flow of computer components. This study aims to design and develop an Android-based educational game called “Assemble & Learn” as an interactive medium for computer assembly lessons, specifically for vocational high school students at SMK Negeri 1 Tanjung Jabung Barat. The development process follows the Multimedia Development Life Cycle (MDLC), which includes the stages of concept, design, material collection, assembly, testing, and distribution. The learning content covers several core competencies: KD 3.2/4.2 on computer assembly, KD 3.3/4.3 on assembly testing, KD 3.4/4.4 on BIOS configuration, and KD 3.5/4.5 on operating system installation, with a focus on KD 3.2 and KD 3.5. Research instruments consist of validation questionnaires for subject-matter experts, media experts, and student trials using the System Usability Scale (SUS). Validation results show that the educational game received an average score of 94% from media experts and 100% from subject-matter experts, both categorized as “Highly Feasible.” Meanwhile, student trials indicated strong acceptance, with an average SUS score of 85% (excellent usability). In conclusion, the “Assemble & Learn” educational game offers an innovative solution to boost learning motivation, simplify material visualization, and provide flexible practice opportunities, thereby supporting the achievement of computer assembly competencies in an optimal and effective way.

The rapid development of information technology has had a significant impact on the world of education, particularly in the use of mobile applications as learning media. Developing Android-based applications using Flutter is one innovation that can increase efficiency and provide a more personalized and adaptive learning experience. In this context, educators are required to continue innovating to meet the increasingly diverse and dynamic needs of students in the digital era. The Multimedia and Information Technology Professional Association (PPMultindo), an organization that brings together technology professionals, is taking advantage of this opportunity by developing an Android-based learning platform. This platform is designed to provide easier, more flexible, and more interactive access to learning materials, as well as support the process of designing more engaging materials. Features such as learning data analysis, material recommendations, and automatic evaluation are expected to increase the effectiveness and efficiency of the teaching and learning process, while also providing a means for collaboration between members. However, the implementation of this technology still faces various challenges, such as limited technological competence of educators, inadequate infrastructure, and the need for curriculum adjustments. Therefore, collaborative efforts are needed to optimize the use of mobile technology to support educational transformation.

The development of information technology, particularly the use of smartphones, has changed human activity patterns and significantly impacted the education sector. The "one-stop-shop" concept reflects the use of mobile devices as centers for various activities, including learning. This situation drives the need for innovation in the development of adaptive and interactive learning media. One solution that can be developed is an Android-based mobile application using Flutter, which can increase the effectiveness and efficiency of the learning process. The Association of Multimedia and Information Technology Professionals (PPMultindo), an organization focused on technology, has developed an Android-based learning platform. This platform is designed to provide flexible access to materials, support interactivity, and facilitate collaboration between educators. Features such as learning analysis, material recommendations, and automatic evaluation are expected to improve the quality of the learning experience. However, the implementation of this technology still faces various challenges, including limited technological competence of educators, inadequate infrastructure, and adjustments to curriculum needs. Therefore, collaborative efforts are needed to optimize the use of mobile technology to support educational transformation in the digital era.

History education at the secondary level continues to face challenges in fostering higher order thinking skills, particularly students’ interpretative and critical analytical abilities, which are often constrained by textual and chronological instructional approaches. This study aims to conceptually examine the role of digital storytelling as a pedagogical strategy to strengthen historical interpretation and critical analysis within the frameworks of constructivism, historical thinking, and critical thinking theory. The research employs a qualitative approach based on literature review, utilizing descriptive and thematic analysis of scholarly works and educational policy documents. The findings indicate that digital storytelling promotes active cognitive engagement through processes of source selection, credibility evaluation, evidence based narrative construction, and multiperspective reflection. The production of digital narratives functions not merely as a creative activity but as a cognitive mechanism that trains logical argumentation and validation of historical evidence. Furthermore, the integration of multimedia elements enhances contextual understanding and deepens students’ meaning making of historical events. Nevertheless, its implementation encounters challenges related to teachers’ digital competence, students’ digital literacy readiness, infrastructural limitations, and instructional time allocation. The study implies that digital storytelling holds strategic potential as a pedagogical approach to develop historical thinking competencies in the digital era, provided that it is supported by systematic instructional planning and sustained capacity building in educational institutions.

This research investigates the effectiveness of digital storytelling as a supplementary tool for lexical fact retrieval and sustainable retention of EFL vocabulary among middle school learners. The research was conducted in particular Islamic School in Gresik, Indonesia. The selected participants were 38 eight-grade EFL learners, divided into experimental and control groups. Vocabulary knowledge was assessed through pre-test, immediate post-test, and delayed post-test conducted after two weeks. The independent sample t-test showed a significantly greater mean improvement in the digital storytelling (DST) group compared to the control group (MD = 8.04, p < .001). The vocabulary retention proved by the result of paired sample t-test which show consistency on the students’ delayed test result (p > .005). This study contributes to the growing literature on digital storytelling and its impact on lexical support. The method proved that DST is effective to enhance students’ vocabulary retention through related multimedia. Digital Storytelling enhance students’ focus and motivation to participate in class.

The development of digital technology has driven significant changes in modern learning methods by integrating various multimedia media. However, multimedia's ability to facilitate learning depends largely on the extent to which its presentation aligns with the principles of learning psychology, particularly those outlined in the Cognitive Theory of Multimedia Learning (CTML). This study aims to examine the role and effectiveness of multimedia in transforming modern learning methods by combining the results of recent empirical research from 2020 to 2024. This study used the Systematic Literature Review (SLR) method by analyzing 22 journal articles obtained from several databases such as Scopus, Web of Science, ScienceDirect, Google Scholar, and Sinta. Research shows that the use of interactive multimedia helps increase student enthusiasm for learning, participation, understanding of concepts, and the ability to remember course material. However, disorganized multimedia design can add unnecessary mental burden, thereby reducing learning effectiveness. These findings suggest that the successful use of multimedia depends not only on the level of technological advancement but also on the quality of learning design that applies cognitive theory. This study provides a comprehensive summary of the latest research and provides tangible benefits for educators in creating effective digital learning content.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.