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Postpartum depression is a postpartum mental health disorder that significantly impacts maternal well-being, infant development, and family functioning. The high prevalence of postpartum depression in Indonesia is due to limited access to health services, low mental health literacy, and social stigma in the community. This indicates a significant gap between the need for maternal mental health services and the availability of existing interventions, making education a crucial component in efforts to prevent postpartum depression early. This study aims to analyze the prevention of postpartum depression in postpartum mothers through telenursing-based education and screening using the Edinburgh Postnatal Depression Scale (EPDS) in the community. A descriptive case study design was used, involving one respondent, a 25-year-old primigravida mother residing in the Bantul area. The intervention was implemented online via WhatsApp and video calls, including structured health education on postpartum psychological changes, adaptive coping strategies, and the importance of social support. The intervention also included daily remote monitoring of the respondent's condition via the WhatsApp mobile application. The EPDS was administered as a pre-test and post-test to evaluate changes in the respondent's psychological condition. The findings showed a significant decrease in the EPDS score from 16 (moderate depression) to 6 (minimal depression), indicating significant psychological improvement. These results imply that integrating EPDS screening, structured health education, and daily monitoring is an effective and accessible community-based approach to preventing postpartum depression, particularly for mothers with limited mobility and access to health services.

This study aims to analyze the effect of information technology (IT)-based learning media on improving students' academic performance. With the advancement of digital technology, the use of IT-based media such as interactive presentations, educational videos, Learning Management Systems (LMS), and online quiz applications has become part of modern teaching strategies. This study uses a quantitative approach with a quasi-experimental method. The subjects of the study were secondary school students divided into experimental and control groups. The instruments used include learning achievement tests to measure academic performance and observation sheets to assess the implementation of IT media usage. Data were analyzed using t-tests and simple regression analysis. The results show a significant difference in academic performance between students who used IT-based learning media and those who used conventional methods. The experimental group showed a higher average score compared to the control group. These findings indicate that the use of IT-based learning media, when planned and implemented systematically, can improve students' motivation, engagement, and understanding of learning materials. Therefore, the integration of information technology into the learning process is recommended as an innovative strategy to enhance 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.

The increasing sedentary lifestyle in the digital era has the potential to cause various health problems due to lack of physical activity. One approach that can be taken to encourage physical activity is through the use of digital games with body movement-based control mechanisms. This study aims to develop a body gesture-based game character control system using a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model. CNN is used to extract spatial features from each video frame, while LSTM serves to model the temporal relationship between frames so that movement patterns can be recognized sequentially. The research method used refers to the Machine Learning Lifecycle stages, starting from data collection, preprocessing, model development, to implementation in the endless runner game genre. Testing results show that the CNN–LSTM model is capable of classifying body gestures and generating outputs that can be used as commands to control game characters. The implementation of this system enables more natural and interactive game interactions without conventional input devices, and has the potential to encourage players to lead a more active lifestyle.

Sentiment analysis on social media is widely used to represent public perceptions of sports performance, particularly in international competitions. This study aims to analyze the sentiment of YouTube user comments regarding the performance of the Indonesian National Football Team during the FIFA World Cup 2026 Asian Qualifiers. The data were collected from user comments on videos related to the matches and analyzed using a machine learning–based sentiment analysis approach. Sentiment classification was performed using the Naive Bayes algorithm. The results indicate that the proposed approach is able to effectively identify public sentiment toward the national team’s performance during the qualification matches. The findings of this study are expected to provide insights into public perceptions and contribute to sentiment analysis research in the field of sports.

Academic stress is a prevalent issue among Indonesian students, affecting both their academic performance and mental well-being. This study investigates the effectiveness of short educational videos on social media in improving students' knowledge about academic stress. A descriptive quantitative approach was used, with a sample of 35 Nursing students from the 2024 cohort at Malahayati University. The data was collected through questionnaires administered before and after students were exposed to 1-3 minute educational videos. The results showed a notable increase in the average knowledge score, from 82.71 to 85. The findings suggest that short videos, which are visually engaging and easy to access, are highly effective for Generation Z learners. Social media platforms, particularly TikTok and Instagram, can be valuable tools for early psychological intervention, providing students with accessible resources to manage academic stress on their own. This study highlights the potential of leveraging digital platforms to support student well-being and offers insights into innovative approaches for addressing mental health challenges in educational settings.

Balatindak is a traditional art that has existed since the time of the Banggai Kingdom. In its development, Balatindak presented in the regions, and each region has its own characteristics in its performance. In Banggai Laut Regency, Bangkurung District, Balatindak is performed upon the arrival of visiting distinguished guests, and on Eid al-Fitr. In Lantibung village, Balatindak is not only entertainment but also as part of the pakanggi umat ceremony carried out by the community. This study aims to describe the form of Balatindak presentation in the process of implementing pakanggi umat. This study uses a descriptive qualitative research method. In collecting data, researchers conducted interviews, and observations of the implementation of pakanggi umat, as well as documenting it in the form of photos and videos. The results of the study found that Balatindak was performed four during the pakanggi umat. The first was at the beginning of the procession performed by two men (talapu), then in the middle was presented by several male and female talapu. The costumes worn by male talakus are daily clothes consisting of long or short-sleeved shirts, black trousers, and white headbands. Meanwhile, female talapu wear long-sleeved shirts, sarongs, scarves, and white head coverings. The Balatindak is unique with movements dominated by rapid foot stomping, and both arms play props depicting machetes and shields. Balatindak is accompanied by batong music. The venue is the Bangkurung traditional house called Kusali. The Balatindak performed in this tradition classified as a ritual performing art.

The Integration of technology in the education sector is a crucial strategy for addressing the challenges of the Industrial Revolution 4.0. This study aims to develop and examine the effectiveness of "Physical Changes of the Earth’s Environment" learning media by utilizing the interactive features of the ClassPoint platform and Edpuzzle videos in 5th-grade elementary school. The method employed is library research with a qualitative-descriptive approach, conducted through content analysis of various relevant scientific literatures from the last five years. The research findings indicate that the synergy between ClassPoint and Edpuzzle is capable of transforming abstract science materials into more concrete and engaging content for students. ClassPoint plays a role in creating a participatory digital classroom through various real-time interaction formats, while Edpuzzle reorients video-viewing activities into an active learning process through embedded question features that stimulate critical thinking. Overall, the use of these interactive media has positive implications for the escalation of active participation, concentration, and the depth of students' conceptual understanding. This study concludes that the development of ClassPoint and Edpuzzle-based learning innovations is an effective and relevant strategic step in improving the quality standards of science education in elementary schools.

Science learning in elementary schools, especially regarding the material on changes in the state of matter, requires media that can present concepts in a concrete and interesting way so So that it is easy for students to understand. This research aims to develop a science learning medium about changes in the states of matter through BrainPOP animated videos equipped with interactive questions for fourth-grade elementary school students, and to evaluate the level of feasibility and studentThis research focuses on students’ feedback toward the developed learning media. It adopts a The research and development (R&D) methodology based on the ADDIE model includes steps such as needs analysis, instructional design, product development, implementation, and evaluation. The students involved in the research were in fourth grade  elementary school students, fourth-grade teachers, and validators from material experts and media experts. The process of data collection involved multiple methods such as direct observation, in-depth interviews, and the distribution of questionnaires obtained were analyzed using quantitative and qualitative descriptive techniques. The results of the study indicate that the developed learning media is classified as very feasible based on validation provided by material experts and media experts. In addition, the results of limited trials indicate that students gave a very positive response to the use of these learning media. Therefore, science learning media based on BrainPOP animated videos and interactive questions can be considered a feasible alternative to increase the interest and understanding of fourth-grade elementary school students.

This research was motivated by the low level of children’s speaking ability in learning activities. This study aims to improve the speaking skills of children aged 5–6 years at Raudhatul Athfal Mas’udi and to examine how animated video learning is implemented to enhance the speaking skills of children aged 5–6 years at Raudhatul Athfal Mas’udi. The method used in this study is a qualitative method with the type of Classroom Action Research (CAR). The subjects of this study were Group B students of Raudhatul Athfal Mas’udi Pontianak, totaling 17 children. There are three aspects examined in this study, namely understanding information that is heard, repeating more complex sentences, and answering more complex questions. To obtain the data, this research used observation, interviews, and documentation. The results of the study show that children’s speaking skills before and after each cycle experienced a very good improvement. Thus, animated videos are proven to be effective in improving children’s speaking skills.

Historical video games are one of the entertainment screen media genres that represent actual historical events influencing the players to learn interactively. Moreover, in an era where technology is increasingly advanced the presence of pop culture that is included in history-based games leads people to get interested more in things that were initially boring to follow. “Sengoku BASARA” (戦国BASARA) is a successful action game featuring a main character based on Japanese feudal warlords wrapped in fictional and dramatic form published by CAPCOM which is very popular in Japan. Yet, Indonesia hasn’t developed a game based on the history of their ancient kingdom with good qualities to bring their interest to learning. The research methodology in this study using a qualitative approach includes content analysis using the 5 W 1 H technique to explore how the historical events and characters in the game are visualized and how it brings or gives the player an understanding of the history. This study aims to delve into two main points: 1. Understanding how “Sengoku BASARA” adapts the elements of their history, 2. The potential of this game as an educational tool is to introduce the historical characters as well as their story events. In conclusion, “Sengoku BASARA” does not have perfect accuracy in visualizing the original history yet it can be the first step to learning more about history interestingly and entertainingly.

Background: Compliance with routine infant immunization is essential for the success of vaccination programs and the prevention of vaccine-preventable diseases. However, adherence to immunization schedules remains suboptimal due to limited parental knowledge, concerns about vaccine safety, and the limited effectiveness of conventional health education. Audio-visual media offer a promising solution by delivering information in a more engaging, clear, and consistent manner. Objective: This study aimed to evaluate the effectiveness of audio-visual educational media in improving adherence to basic immunization among infants in the service area of the Rum Balibunga Community Health Center. Methods: A quasi-experimental design with a one-group pretest-posttest approach was used. The sample included 40 mothers with infants aged 0-12 months selected through purposive sampling. Participants received an educational video on basic immunization. Adherence was assessed before and after the intervention based on completeness and timeliness according to the national schedule. Data were analyzed using univariate and bivariate methods, with the McNemar test for paired categorical data. Results: There was a significant improvement in immunization adherence after the intervention. Statistical analysis confirmed a meaningful difference before and after exposure, indicating the effectiveness of audio-visual media. Conclusion: Audio-visual education is an effective strategy to improve infant immunization adherence and can be widely applied in primary healthcare settings.

Background: Clean and Healthy Living Behavior in Indonesia includes household.. In Indonesia, the level of knowledge and handwashing behavior of is still relatively low, an indication can be seen from the high prevalence of diarrhea. Research Objective: to determine the Relationship of Information Sources to Knowledge and Behavior of Adolescents About Clean Living in Nunkurus Village, East Kupang District. Research Method: This type of research uses Quasi Experiment One Group PreTest-PostTest Non Control Group, namely research with one subject who is given treatment or intervention before and after treatment. The population in this study is the community in this case adolescents in Nunkurus Village, East Kupang District, totaling 45 people. Sampling uses a total sampling technique. There are 3 research instruments used in this study including: respondent characteristic questionnaire, PHBS knowledge and health promotion educational video about PHBS. Data analysis using univariate in percentage and bivariate using Willcoxon Test. Results: the results of the study revealed the level of knowledge of the community before health promotion regarding PHBS, of the 45 respondents studied as many as 2 respondents (4.4%) had insufficient knowledge, 14 respondents (31.1%) had sufficient knowledge, and 29 respondents (64.4%) had good knowledge. From the results of the study, it was known that the level of knowledge of the community after health promotion regarding PHBS, of the 45 respondents studied as many as 17 respondents (37.8%) had good knowledge, 20 respondents (44.4%) had sufficient knowledge, and 8 respondents (17.8%) had insufficient knowledge. This is demonstrated by the results of the Wilcoxon ρ test (Asymp. Sig. 2-tailed) = 0.000 <0.05, indicating a relationship.

This community service activity aims to improve the capacity and strengthen the digital literacy of Micro, Small, and Medium Enterprises (MSMEs) in Klambir Lima Kebun Village, Hamparan Perak District, in utilizing digital technology as a means of marketing their products. The main problems faced by MSME players in this village are a low understanding of digital marketing strategies, limited effective use of social media, and a lack of ability to manage digital content that is attractive and suitable for the target market. Through this community service activity, participants were equipped with basic knowledge and digital literacy, digital marketing strategies, the use of e-commerce platforms, and techniques for creating photo and video-based promotional content. The implementation methods included socialization, practical training, and mentoring for community service participants. The results of the activity showed an increase in the understanding and skills of MSME actors in managing digital business accounts and utilizing social media such as Instagram, Facebook, and WhatsApp Business as effective marketing tools. With this activity, it is hoped that MSME actors in Klambir Lima Kebun Village will be able to expand their market reach, increase sales, and adapt to the development of the digital economy in a sustainable manner.

The increasing intensity of traffic object movement in urban areas has not been accompanied by adequate road infrastructure, resulting in traffic congestion, air pollution, and a higher risk of traffic accidents. One of the primary causes of accidents is traffic violations, particularly wrong-way driving behavior. This study develops a video-based automated traffic violation detection system using the YOLOv5 algorithm. A computer vision approach is employed to detect, classify traffic objects, and count wrong-way violations in real time. Due to limited access to real-world traffic violation footage, simulated traffic scenarios are used as testing data. The system is evaluated on four traffic object classes: motorcycles, cars, buses, and trucks. Experimental results demonstrate strong performance, achieving a precision of 90%, a recall of 92%, and an F1-score of 91%, while the traffic object counting accuracy reaches 89%. These findings indicate that the proposed system has significant potential to support traffic analysis and assist authorities in making more effective decisions to reduce congestion and traffic accidents.

Indonesia merupakan negara yang rawan gempa bumi, seperti yang terjadi di Yogyakarta tahun 2006 yang menimbulkan banyak korban jiwa dan kerusakan besar. Hal ini menunjukkan pentingnya kesiapsiagaan bencana di perguruan tinggi. Mahasiswa sebagai agen perubahan berperan penting dalam mitigasi bencana. Self efficacy atau keyakinan diri menjadi salah satu faktor yang memengaruhi kesiapsiagaan mahasiswa. Penguatan self efficacy di kalangan mahasiswa sangat penting untuk membangun kesiapsiagaan bencana di perguruan tinggi. Penelitian ini bertujuan untuk mengetahui pengaruh pemberian mini video edukasi penanganan kegawatdaruratan gempa bumi terhadap self efficacy mahasiswa keperawatan anestesiologi. Metode penelitian ini menggunakan desain pre-eksperimental dengan pendekatan pretest and postest design tanpa kelompok kontrol. Teknik sampling menggunakan Simple Random Sampling dengan instrumen berupa lembar angket kuisioner. Hasil bivariat menggunakan uji Wilcoxon.  Hasil analisis bivariat menggunakan uji wilcoxon menunjukan perbedaan yang signifikan antara self efficacy sebelum dan sesudah pemberian edukasi video yaitu didapatkan nilai signifikansi atau sig (2-tailed) sebesar 0.000 <0.05. sehingga H0 ditolah dan Ha diterima. Kesimpulannya terdapat pengaruh pemberian mini video edukasi penanganan kegawatdaruratan gempa bumi terhadap self efficacy mahasiswa keperawatan anestesiologi.

Choking is a dangerous thing for children, especially children with special needs who require proper handling, and parents as the closest people to the child must have first aid skills for choking. The purpose of this study is to determine the effect of ANSIVI (Animation and Simulation Video) Choking Management on parents' ability in first aid for choking. The research design was a pre-experimental design with a one-group pretest-posttest approach without control. The purposive sampling technique obtained 36 respondents. The research instrument used an observation sheet for first aid for choking. The statistical test was the Wilcoxon Signed Rank Test with α 0.05. The results of the study before being given the ANSIVI (Animation and Simulation Video) Choking Management intervention showed that all (100%) respondents had insufficient ability, and after the intervention the majority (52.8%) of respondents had sufficient ability. The results of the statistical analysis obtained a p-value of 0.013 < α 0.05, so there is an effect of ANSIVI (Animation and Simulation Video) choking management on parents' ability in first aid for choking. The ANSIVI method (Video Animation and Simulation) combines two methods so that it is more interesting, interactive, and effective because the video is captured by the eyes and ears and then will be detected and converted into signals to the optic nerve and auditory nerve and forwarded to the brain, program area, and frontal area to be associated so that it will affect the respondent's ability. The ANSIVI method can be used in education for all parents and school residents as a first aid effort for choking, especially for children with special needs.

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.

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.