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This study aims to analyze the comparison of the durability of natural fiber and synthetic fiber composites in a high-temperature production environment. Testing was conducted on carbon fiber, aramid (synthetic), ramie, and jute (natural) fiber-based composites with exposure to temperatures of 80-150°C for 500 hours. The parameters measured include tensile strength, elastic modulus, dimensional stability, morphological changes, and moisture absorption. The research results show that synthetic fiber composites have superior durability compared to natural fibers. Carbon fiber composites retain 87% of their initial tensile strength with only a 4.2% reduction in modulus, while flax fibers only retain 62% strength with a 26% reduction in modulus. Microscopic analysis revealed significant delamination in natural fiber composites with interface gaps of 15-25 μm, compared to 3-5 μm in synthetic fibers. Natural fibers undergo thermal degradation due to the decomposition of lignin and hemicellulose, resulting in significant color changes and a dimensional shrinkage of 3.2%. The moisture absorption of natural fibers increases to 8.5% after exposure, indicating damage to the cellular structure. This research concludes that synthetic fiber composites are more suitable for long-term high-temperature production applications, but natural fibers can still be considered for low-temperature applications with appropriate chemical modification.

This study aims to evaluate the effectiveness of the Artificial Intelligence-Based Learning Media Development Program (P3MP-AI) in enhancing teachers’ technological and pedagogical competencies at SMK Muhammadiyah 2 Malang. The program employed a descriptive approach using both quantitative and qualitative methods, including pre-test and post-test assessments, as well as direct observation of the training process. A total of 30 teachers from various disciplines actively participated in the program conducted on August 12, 2025. The evaluation results revealed an increase in the participants’ average scores from 100 to 130 out of a maximum of 150, indicating a significant improvement in their understanding of AI concepts and applications in education. Beyond competency enhancement, the training also fostered teachers’ confidence, creativity, and ability to integrate AI-based tools into interactive learning media. However, several challenges were identified, such as limited technological resources and time constraints in classroom implementation. Overall, this program has made a tangible contribution to strengthening teachers’ digital literacy and can serve as a replicable professional development model for other vocational schools seeking to advance AI-based educational transformation.

Bintan Island has abundant bauxite soil resources; however, its utilization as road construction material remains limited. The scarcity of high-quality granular material in the region necessitates the use of available local resources, particularly for pavement subgrade layers. This article aims to analyze the classification and mechanical properties of native soils in Bintan Island through a systematic literature review. The reviewed literature includes laboratory test results of bauxite soil. The findings indicate that bauxite soil exhibits low plasticity, relatively high CBR values (±35%), and is classified as CL (USCS) and A-2-4 (AASHTO). These results suggest that bauxite soil is suitable for subgrade applications, although require stabilization with binding agents. The implication of this review highlights that the utilization of local materials could support sustainable infrastructure development in island regions by reducing dependency on imported materials.  

This study aims to design and test a Dual Axis Solar Tracker to improve the energy absorption efficiency of solar panels on ships. The system is designed with a two-axis movement mechanism (horizontal and vertical) using a linear actuator motor controlled by Arduino Nano and ESP32. Testing was conducted on a 20 WP solar panel in Surabaya for 30 days, divided into three methods: 10 days using an LDR sensor, 10 days using an RTC, and 10 days in static conditions without a sensor. Voltage, current, and power data were measured every 30 minutes at 07.00–17.00 WIB. The test results show that the RTC method provides the highest and most stable output power, according to the sun's movement patterns in tropical areas, while the LDR method responds quickly to changes in light intensity but is less stable in changing weather. Static installation produces the lowest power. This system is able to maintain the panel orientation perpendicular to the sun's rays, thus increasing energy efficiency compared to static systems. These findings prove that dual-axis solar tracker technology, especially with an RTC sensor, is effective in dynamic maritime environments and can be a practical solution for optimizing renewable energy on ships. The most effective results using RTC sensors demonstrated the most stable and high power output, especially since the sun in tropical areas like Surabaya moves fairly consistently following a cyclical pattern. The success of this system not only increases the energy output of solar panels but also provides a practical solution for renewable energy applications in tropical climates.

This study aims to investigate the factors influencing the continuance intention of Al-Kautsar Senior High School students in using metaverse-based learning media. The background of this research lies in the rapid adoption of immersive technologies in education, while students’ levels of acceptance have not yet been fully understood. The objective is to identify the antecedents of satisfaction, which subsequently influence continuous intention. The research model examines the effects of perceived interactivity, perceived sociability, perceived enjoyment, perceived ease of use, perceived security, and social influence on satisfaction. A quantitative approach was employed by distributing questionnaires to students, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that satisfaction is a very strong and statistically significant predictor of continuous intention to use metaverse applications (β = 0.716, p < 0.001). The six hypothesized antecedent variables were not found to have a significant individual effect on satisfaction. In conclusion, for digital native students at Al-Kautsar Senior High School, factors such as ease of use, interactivity, and enjoyment have shifted from being drivers of satisfaction to becoming basic expectations (hygiene factors). Satisfaction itself emerges as the primary determinant, likely influenced by more substantive elements such as content quality or pedagogical design rather than merely the technical features of the platform.

Credit card fraud is a critical issue in digital financial transactions. This study aims to develop and evaluate fraud detection models using Logistic Regression and Gradient Boosting on an imbalanced dataset, where fraudulent transactions constitute only a small portion of the data. To address this imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied during preprocessing. Logistic Regression, used as a baseline model, achieved 95% accuracy, 78.6% precision, 55.9% recall, and a 65.3% F1-score. After applying class weighting and SMOTE, recall improved to 88.7%, but precision dropped to 52%, indicating that the model became overly sensitive and prone to false positives. Gradient Boosting initially produced better results, with 98% accuracy, 95.5% precision, 84.3% recall, and an 89.5% F1-score. After hyperparameter tuning and resampling, its performance improved further to 96.7% precision, 86.1% recall, and a 91.1% F1-score. These results indicate that Gradient Boosting is more effective in handling imbalanced data and offers greater reliability in detecting fraudulent transactions. The findings support the growing evidence in favor of ensemble learning techniques in fraud detection applications. This research contributes practical insights into improving the accuracy and security of machine learning-based fraud detection systems in financial services.

This study evaluates the efficiency of two artificial intelligence models, DeepSeek and OpenAI, in generating code for algorithmic systems. Efficiency is assessed through execution speed, code accuracy, and the number of code characters produced. Data were collected from 100 tests covering search, sorting, graph, dynamic programming, optimization, data processing, text, and machine learning algorithms. The objective is to compare the performance of both models to support the development of efficient information retrieval systems. The method involves algorithm testing with statistical analysis of execution time, accuracy, and code length. Results indicate that DeepSeek has an average execution time of 28.74 seconds, slightly slower than OpenAI’s 28.49 seconds. However, DeepSeek’s accuracy (85.88%) surpasses OpenAI’s (85.03%). The average number of code characters is identical at 96.35 characters. The study concludes that DeepSeek excels in accuracy, while OpenAI is faster in certain cases, providing valuable insights for developers in selecting AI models for information retrieval applications.

As a vocational education institution, SMK Swadhipa 1 Natar is required to provide adequate facilities to support the development of its students' technical and practical skills. Although some facilities are already available, student complaints remain regarding the condition, availability, and utilization of these services, particularly those related to information technology.This study aims to analyze the level of student satisfaction with information technology services at SMK Swadhipa 1 Natar using a combination of Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) methods. The study was conducted through a quantitative approach by distributing questionnaires to 100 respondents selected using stratified random sampling techniques. The data collected were analyzed to determine the overall satisfaction score and identify factors of information technology services that were a priority for improvement. The results of the CSI analysis showed that the level of student satisfaction with school information technology services was in the good category, with an average score of 82%. Furthermore, the results of the IPA analysis revealed that information technology services such as computer services in the school lab, wifi networks, and school websites consisting of school exam applications, student registration applications and information about the school on the website were in the top priority quadrant because they had a high level of importance but their performance was still low. Based on these results, it can be concluded that although in general students stated that they were quite satisfied with the information technology services available, there were several important aspects, especially technology-based information technology services, that needed more attention from the school. Thus, recommendations for improving technological infrastructure and periodic evaluation of educational information technology services can help SMK Swadhipa 1 Natar in improving the quality of educational services and student satisfaction. 

This study aims to analyze the process of processing fruit peel waste from juice traders into eco-enzymes as an effort to reduce environmental pollution. The research uses qualitative descriptive methods through direct observation, documentation, and literature studies. Fruit peel waste is fermented at a ratio of 1:3:10 (molasses : fruit waste : water) for three months under anaerobic conditions. The fermentation results show good eco-enzyme characteristics, characterized by a pH of 3, a fresh sour aroma, and a brownish color as an indicator of fermentation success. These findings show that the process of processing eco-enzymes from fruit peel waste can be done simply, cheaply, and environmentally friendly. In addition, the use of eco-enzymes has the potential to reduce the volume of organic waste disposed of in landfills and reduce water and soil pollution. The resulting eco-enzyme also has potential applications as natural cleaners, liquid fertilizers, and odor controllers. Thus, the treatment of fruit peel waste not only supports sustainable environmental management practices, but also encourages the implementation of the circular economy as well as community empowerment ecologically and economically.

Innovation in biology learning is increasingly necessary, as conventional instructional practices are often dominated by memorization-based methods that limit students’ active engagement and critical thinking development. Along with rapid advances in science and technology, digital applications offer new opportunities to enhance teaching and learning processes. One such application is Canva, a digital design platform that can be utilized as an effective learning media to support teachers and students in biology education. This study aims to describe the implementation of Canva-based learning media through a training program conducted at SMA Islam Terpadu Daarul Rahman and to examine its perceived usefulness for both teachers and students. The training involved teachers in developing biology learning materials using Canva by integrating visual elements, images, and videos to present complex biological concepts more clearly. The results of the training indicate that Canva is considered practical, user-friendly, and efficient by teachers in designing learning materials. Teachers reported that the application helped them present content in a more attractive and structured manner. Furthermore, students benefited from the use of Canva-based materials, as they demonstrated better understanding of the subject matter and increased interest in learning biology. The integration of visual and multimedia elements also supported the development of students’ critical thinking skills by encouraging analysis and interpretation of biological phenomena. Overall, the use of Canva as a learning medium shows potential to enhance the quality of biology learning and foster more meaningful learning experiences.

This study aims to examine the use of artificial intelligence (AI) in transforming Buddhist Sunday School education at the Shimakalingga Temple in Jepara in the digital era. Using a qualitative descriptive approach, data were collected through observation, interviews, and documentation studies. The results show that AI technology is beginning to be utilized in the learning process, such as the use of interactive visual media, Dharma quiz applications, and digital platforms for distance learning. The use of AI has been proven to increase student interest and understanding of Buddhist teachings, as well as support more inclusive and adaptive learning. However, challenges remain, including limited resources, lack of teacher training, and the need for ethical guidelines for the use of AI in the context of religious education. This study concludes that AI plays a significant role in supporting the transformation of Buddhist education, but its use must remain balanced with spiritual values and the role of teachers as moral guides. Therefore, collaboration between the temple, educators, and technology is needed to create a sustainable learning system based on Dharma values.

This study aims to analyze and synthesize research findings related to the integration of Buddhist values in the development of interactive learning media. The research employed a qualitative approach using a systematic literature review method on fifty selected articles published between 2018 and 2025. Data were collected through a structured process of identification, screening, and extraction from primary sources consisting of accredited national journals and reputable international journals. The data were analyzed using thematic and comparative synthesis techniques to identify patterns, effectiveness, and research gaps. The results show that interactive learning media based on Buddhist values can enhance students’ motivation, moral understanding, and engagement through the use of technologies such as gamification, educational animation, augmented reality, and mobile applications. The effectiveness of these media is strongly influenced by the alignment between Buddhist ethical principles, instructional design, and the cultural context of learning. Furthermore, the study reveals that the successful integration of spiritual values into digital media depends on educators’ readiness, digital literacy, and technological infrastructure support.

This study comprehensively evaluates the quality of biomass briquettes produced from blends of coconut shell charcoal and sengon sawdust, using both carbonized and non-carbonized materials. Composite briquettes were fabricated with varying compositions and characterized through proximate analysis, calorific value, density, and burning rate measurements to determine their suitability as solid fuel. The results indicate that adding non-carbonized sawdust increases volatile matter content and burning rate but reduces the calorific value of the briquettes. In contrast, incorporating up to 10% carbonized sawdust significantly improves the calorific value to 6119.2 cal/g, approaching that of pure coconut shell charcoal (6352.2 cal/g), while maintaining a relatively high burning rate. Briquettes containing carbonized sawdust also exhibit low ash content, below 3%, and moisture content under 8%, meeting standard solid fuel quality requirements. These findings demonstrate that a strategic combination of carbonized and non-carbonized materials can produce hybrid biomass briquettes with optimized thermal performance, providing a promising, sustainable, and environmentally friendly alternative fuel for domestic and industrial applications.

Lemongrass (Cymbopogon citratus) is a plant known to contain various bioactive compounds with potential antioxidant properties as well as xanthine oxidase (XO) inhibitory activity. This study aimed to evaluate the phytochemical content, antioxidant activity, and XO inhibitory potential of ethanol extracts from the leaves, stems, and their combination. Phytochemical screening revealed that all extracts contained alkaloids, flavonoids, and terpenoids, while phenolic compounds were detected only in the leaf extract and the combined leaf–stem extract. Antioxidant activity assays demonstrated that all extracts exhibited very strong antioxidant activity, with IC₅₀ values below 50 ppm, indicating a significant potential to scavenge free radicals. In the XO inhibition assay at a concentration of 200 ppm, the ethanol extract of lemongrass stems showed the highest inhibitory activity at 81.37%, followed by the leaf extract at 48.08% and the combined leaf–stem extract at 33.65%. Overall, these findings suggest that the ethanol extract of lemongrass stems is the most promising natural source of antioxidants and has the greatest ability to inhibit xanthine oxidase activity, indicating its potential development as a functional ingredient for health applications.

Heritage language loss among immigrant and diaspora communities represents a critical challenge to cultural identity, intergenerational communication, and cognitive diversity. Traditional heritage language maintenance approaches face significant barriers including limited resources, lack of qualified instructors, geographic dispersion, and competing demands of dominant language acquisition. This study investigates the effectiveness of bilingual digital story applications as innovative tools for heritage language maintenance among children aged 4-12 years. Through a 24-month longitudinal mixed-methods study involving 1,843 families across eight language communities (Spanish, Mandarin, Arabic, Korean, Tagalog, Vietnamese, Hindi, and Polish), we examined language proficiency development, cultural identity formation, family engagement patterns, and app usage behaviors. Quantitative analysis of pre- and post-intervention language assessments revealed statistically significant improvements in heritage language vocabulary (effect size d=0.68), listening comprehension (d=0.54), and oral production (d=0.47) among children using bilingual story apps for at least 20 minutes daily. Qualitative findings from parent interviews and child focus groups highlighted the apps' role in making heritage language learning enjoyable, facilitating parent-child interaction, connecting children to cultural narratives, and normalizing bilingualism. However, effectiveness varied substantially based on app design features, with interactive elements, culturally authentic content, parent involvement scaffolds, and adaptive difficulty showing strongest associations with outcomes. This research demonstrates that thoughtfully designed bilingual story apps can serve as accessible, scalable tools for heritage language maintenance, though they function most effectively as complements to rather than substitutes for rich home language environments and community connections. The study contributes empirical evidence to inform app development, family language planning, and policies supporting linguistic diversity in increasingly globalized societies.

This study examines the application of double integrals in calculating the volume of cylindrical concrete piles as a basis for estimating material requirements in building foundation structures. The volume calculation was carried out using a double-integral approach in polar coordinates for three pile segments with lengths of 4 m, 3.9 m, and 4 m, each having a diameter of 60 cm. The results were then validated using the standard geometric formula to ensure consistency and mathematical reliability. The obtained concrete volume was subsequently used to estimate material needs based on a 1:1.5:3 mix proportion consisting of cement, sand, and gravel. The findings indicate that double integrals can be effectively applied to generate accurate estimations of both volume and material requirements, supporting logistical planning in construction. This approach also highlights the strong connection between mathematical concepts—particularly multivariable calculus—and practical applications in civil engineering. Furthermore, the study emphasizes that double integrals may serve as a relevant alternative when structural modeling requires deeper analytical exploration or validation beyond conventional geometry. Therefore, the implementation of double integrals not only reinforces theoretical understanding but also enhances precision in evaluating structural components within building foundation planning.

This study aims to evaluate the public transportation service policy of Trans Jatim Bus Corridor 2, operating on the Mojokerto–Surabaya route, using the six evaluation indicators proposed by William N. Dunn: effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness. Employing a qualitative descriptive approach, data were collected through interviews, direct observations, and secondary data analysis. The findings reveal that the Trans Jatim Corridor 2 service has significantly contributed to improving accessibility and mobility for the people of East Java. In terms of effectiveness, the service meets transportation policy objectives by offering strategic routes, consistent schedules, and accessible bus stops. Efficiency is demonstrated through optimal utilization of limited fleets and operational costs, while still meeting high passenger demand. Regarding adequacy, the service is generally sufficient; however, overcrowding during peak hours indicates the need for capacity improvements. Equity is reflected in the widespread distribution of bus stops, although disparities remain in the availability of facilities and route information across several stops. The service shows high responsiveness through quick handling of passenger complaints via applications and social media. Additionally, service appropriateness is evident in its punctual operations supported by GPS-based monitoring and real-time information through the TRANSJATIM-AJAIB application. Overall, the evaluation shows that Trans Jatim Corridor 2 provides effective, efficient, and responsive public transport services, yet requires improvements in capacity and equitable distribution of facilities to achieve optimal service quality.

This community service aims to provide understanding and skills in using comics and AR media as well as understanding biology material by high school students. The community service was carried out at SMA Negeri 1 Raja Ampat involving 43 students. Measurement of student responses using a questionnaire with six statements on a scale of 1 - 4. The measurement data was calculated to obtain the average score and percentage of student responses. The results of the community service show that the average total score is 86.53 which indicates that overall the student response is very good to the community service activities that have been carried out. Student responses are dominated by agree and strongly agree. The largest percentage of disagree, namely 23.26%, is shown by students, especially in the statement that AR applications can be run easily, but the average total score still reaches the good category for this statement. The community service has provided students with an understanding of how to learn biology in an interesting way and provides benefits to improve their understanding. Students agree that the material presented adds to their insight regarding comics and AR, are able to install AR applications on their mobile devices, improve their understanding of biology material, is interesting and provides benefits for them.

This community service activity was conducted to assist banking institutions in the Surabaya region in enhancing the effectiveness of marketing strategies for savings products in order to increase the number of customers. The main problems faced by banks include the relatively low level of public interest in saving and the suboptimal implementation of promotional strategies, particularly in the utilization of digital media. This activity employed a collaborative approach through training, mentoring, and joint evaluation with marketing staff of banks in the Surabaya area. This activity commenced with an observation and interview phase to identify the marketing strategies that had been previously implemented. Subsequently, material delivery, technical assistance, along with an evaluation of promotional effectiveness. The results indicate that participants were able to implement more adaptive marketing strategies by utilizing digital media such as social media, website, and banking applications. The implementation of these strategies was shown to increase public interest in opening saving accounts. Furthermore, this activity contributed to enhancing the capacity of marketing staff to design data-driven strategies and to strengthening public financial literacy regarding saving products.

Activated carbon has been developed for supercapacitor electrode material due to their high degree of micro porosity and large surface area. The carbon source, preparation conditions such as temperature and atmosphere, and preparation method strongly influence the crystalline structure and the properties of carbon materials. This article is focused on the crystalline structure analysis of bamboo and coconut coir activated carbon The bamboo and coconut coir carbon were fabricated by using pyrolysis method. The activated bamboo carbon and activated coconut coir carbon were produced using a chemical activation method where H3PO4 solution as activator agent. Characterization of the physical/crystalline structure of the bamboo carbon (BC), and coconut coir carbon (CCC) and bamboo activated carbon (BAC), coconut coir activated carbon (CCAC) was determined using XRD measurement. The XRD spectra of BC and BAC indicate that the percentage crystallinity are 29.1%, and 18.4% respectively. For CCC and CCAC the percentage crystallinity are 11.3% and 13.2%, respectively. The interlayer spacing (dhkl) for BC is 4.05 Angstrom, and for BAC is 3,79 Angstrom. The crystallite height (Lc) for BAC is 6.64 Angstrom and for BC is 21.56 Angstrom. The interlayer spacing (dhkl) for CCC and CCAC are the same 4.05 Angstrom. The crystallite height (Lc) for CCAC is 4.96 and for CCC is 2.83 Angstrom.