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This study examines the implementation of Pancasila values-based Civic Education (PKn) learning in enhancing tolerance attitudes among fifth-grade students at UPT SD Negeri 064016. Using a descriptive qualitative approach with a case study design, data were collected through participatory observation, in-depth interviews, document analysis, and tolerance attitude questionnaires involving 28 students. Results indicate that contextual strategies—such as classroom deliberation simulations and collaborative projects based on local wisdom—significantly improved students' tolerance attitudes. Conceptual understanding of diversity increased by 34.5%, empathetic attitudes rose by 29.5%, and inclusive practices grew by 23.7% (composite score +29%, Cohen’s d = 1.45). Key supporting factors included the school’s commitment to integrating Pancasila values into the curriculum and innovative media (e.g., multicultural congklak, AR cultural maps). Primary constraints were limited instructional time and student ability heterogeneity. The study concludes that Pancasila values-based learning models, supported by teacher consistency and active student participation, effectively foster inclusive school environments.  

Ground-mounted solar panels are directly exposed to environmental conditions, particularly wind, making structural design essential. While wind tunnel experiments have been a primary research method, they are costly and time-consuming. Computational Fluid Dynamics (CFD) simulations provide an efficient alternative by accurately modeling fluid-structure interactions, allowing for detailed aerodynamic analysis without physical testing. This study examines a solar panel configuration of 2×18 (1700×1200 mm panels) under a wind speed of 30 m/s at a height of 10 m. Wind direction variations (0°, 30°, 60°, 90°, 120°, 150°, 180°) significantly impact aerodynamic behavior. Drag Force analysis reveals that frontal wind (0°) generates the highest drag, while lateral wind (90°) has the least effect. Surface Pressure and Surface Coefficient (Cp) analysis indicate maximum pressure at 0°, where Cp values are highest, highlighting a pronounced pressure differential. At 90°, pressure distribution is more uniform, reducing aerodynamic impact. At 180°, rear-side pressure remains influential but lower than frontal exposure.

Mental health issues among adolescents are often not handled properly due to low psychological literacy and strong social stigma. This community service activity aims to provide psychoeducation on the importance of mental health to SMK Taman Harapan students. The methods used include interactive lectures, group discussions, and simple simulations to increase students' awareness and understanding of mental health issues that are common in adolescence. The theme "Talking About Mental Health Doesn't Have to Wait Until You're Crazy First" was chosen to emphasize that discussions about mental health should be part of everyday life, not taboo. The results of the activity showed high student enthusiasm and increased understanding of the importance of maintaining mental health and seeking help when needed. This activity is expected to be the first step in creating a school environment that is more open and supportive of mental health issues.

Organic waste management is an important issue in addressing environmental problems. One potential solution is bioconversion technology using Black Soldier Fly (BSF) maggots that can break down organic waste and produce larvae with economic value as animal feed. To increase the selling value and extend the shelf life, BSF larvae need to be dried using tools such as rotary dryers. This study aims to design and analyse the strength of a rotary dryer machine frame for maggot drying with a Finite Element Analysis (FEA) approach based on SolidWorks software. Simulations were carried out on several materials: ASTM A36, AISI 1020 Steel, and AISI 1045 Steel. The analysis results show that all materials are within safe limits based on Von Mises stress, deformation, and safety factor. AISI 1045 steel material gives the best performance with Von Mises stress of 14.238 MPa, deformation of 0.59 mm, and safety factor of 7.2. These results show that AISI 1045 steel is the most recommended material for the rotary dryer frame.

This study discusses how to apply a deep learning approach to support mathematics learning in elementary schools. Where this study uses a qualitative method. This study obtains data from literature reviews, researchers examine various relevant national scientific sources to identify the benefits, challenges, and opportunities for integrating deep learning technology in mathematics learning. The results of the study show that the application of deep learning to mathematics studies has a positive impact on student understanding. This method encourages active student involvement through various interactive activities, such as simulations and experiments, so that the learning process becomes more meaningful and enjoyable. However, the application of this method is also faced with a number of challenges, such as limited time to complete the curriculum and unequal access to technology among students.

The purpose of this study is to evaluate how well interactive learning materials can raise elementary school pupils' motivation and interest in learning. Animation films, instructional games, and simulations are examples of interactive learning materials that offer students a familiar, dynamic, and developmentally appropriate learning experience. Using a qualitative approach and a literature review strategy, the study examined material from a range of pertinent sources, including books, journals, and research reports. According to the study's findings, students who actively interact with interactive media can become more involved in the learning process. Additionally, it offers instant feedback, which increases self-confidence, helps pupils understand their progress, and fortifies their enthusiasm to learn.

Educational transformation through the use of interactive technology is an integral part of the implementation of the Merdeka Curriculum, especially in Mathematics learning in Elementary Schools (SD). This curriculum emphasizes a contextual, student-centered, and adaptive learning approach to the challenges of the digital era. This study aims to analyze the role of interactive technology in improving the effectiveness of Mathematics learning and developing 21st-century skills in elementary school students. Various digital media such as GeoGebra, gamification applications, and visual simulations are used to help students understand abstract concepts in a concrete and enjoyable way. The results show that technology integration supports the achievement of the Pancasila Student Profile by increasing creativity, independence, and critical thinking skills. Challenges such as limited infrastructure and teacher competency can be overcome through continuous training and development of relevant local content.

Science education in elementary schools plays a crucial role in shaping students’ early understanding of natural phenomena, including the concept of force and its effects on objects. However, many teachers still face challenges in delivering the material in a contextual and engaging way, which affects student participation in learning. This study aims to analyze the relevance of the science content on the theme “the effect of force on objects” and to evaluate the effectiveness of simulation-based learning in improving concept comprehension among fourth-grade students. A descriptive quantitative method was used with a simple experimental approach involving one class. The research instruments included observation, documentation, and posttest assessments. The results showed that 92.6% of students achieved the minimum mastery criteria after participating in the simulation-based learning process. These findings indicate that the use of simulations helps students better understand changes in motion and shape caused by force. The implication of this study highlights the importance of integrating interactive media and experiential learning approaches in science education at the elementary level to enhance student engagement and significantly improve learning outcomes.

The purpose of this community service activity is to increase knowledge for mothers at the Garuda 04 Posyandu in Harapan Jaya Bekasi on how to use income to manage a balanced life between the needs of early childhood or toddlers and family needs. The results show that most members of the Garuda 04 Posyandu do not understand properly and correctly how to manage family income properly and correctly from the financial income they earn, such as the difference between needs and wants, budgeting, and the importance of saving and managing the fulfillment of toddler needs for the children they have. The training was conducted in one day with a participatory-educational approach and socialization. This method includes providing materials, group discussions, simulations, and reflections from each individual. The activities showed high active participation from participants and were actively involved in the discussions that were carried out. This socialization provides evidence that an experience-based approach can effectively increase understanding and awareness of the importance of financial management that they are facing.

A reliable electrical grid the power plant scheduling system needs to optimize the plant's performance by considering the economic value and the value of emissions generated by the plant, in addition to the reliability and economic sectors. This system should also take into account the environmental impact, as well as the CO2 and CH4 emissions produced by the plant. This research will use the Dragonfly Algorithm with weighting parameters to schedule hydro and thermal facilities' emissions and economic activities. That the weighting value impacts production costs and emissions is demonstrated by the data acquired from the Dragonfly Algorithm simulation. If economic considerations take precedence in assigning weights, then low-cost generating will result in high-value emissions, and vice versa. The plant's Emission Intensity rating also meets the standards established by the government.

Violent behavior is a major challenge in the care of patients with mental disorders, particularly in acute conditions such as schizophrenia and bipolar disorder. Families and caregivers often lack the knowledge and skills needed to handle crisis situations, thereby increasing the risk of injury and patient relapse. The aim of this program was to enhance the capacity of families and caregivers in managing violent behavior through de-escalation technique training. Used was a two-day face-to-face training (May 2–3, 2025) at RSKD Dadi Makassar involving 10 participants. Activities included interactive lectures, group discussions, simulations, and pre- and post-test evaluations. The training materials were designed based on evidence-based practices, covering empathetic communication, emotional regulation, and conflict management strategies. Of the program showed an increase in understanding of de-escalation techniques from 30% to 90%, improved conflict response ability from 20% to 80%, and a reduction in violent incidents from 12 to 4 occurrences in the week following the training. All participants also expressed satisfaction with the training. De-escalation technique training proved effective in increasing the preparedness of families and caregivers in dealing with violent behavior in patients with mental disorders. This approach is essential for creating a safer, more humane, and recovery-oriented care environment

The vehicle ownership transfer form submission service at the Samsat Tandes Office in West Surabaya is a vital public service that frequently encounters issues such as long queues and extended waiting times. These conditions lead to user dissatisfaction and reduce the operational efficiency of the institution. This study aims to optimize the existing queuing system through a simulation-based approach to enhance service effectiveness and efficiency. The methodology includes mapping the current service process, collecting data on service times and customer arrivals, and modeling the queuing system using simulation software. Subsequently, several improvement scenarios were analyzed, including the addition of server resources. The simulation results indicate that the scenario involving the addition of one extra server during peak hours yields the most significant impact—reducing average customer waiting time by up to 20% and increasing the number of customers served per day. These findings demonstrate that simple interventions based on simulation analysis can produce substantial improvements in public service quality. In conclusion, a simulation-based approach proves to be effective in supporting strategic decision-making for queue system optimization and is highly recommended for implementation in other public service units facing similar challenges.

Energy efficiency in air conditioning systems is a critical factor in reducing energy consumption and environmental impact. This study aims to analyze the energy performance of an air conditioning system using the thermodynamic cycle method. The analysis focuses on the refrigeration cycle, particularly the vapor compression cycle commonly used in residential and commercial systems. Key parameters such as coefficient of performance (COP), refrigerant flow rate, and enthalpy at each cycle point were examined to determine overall efficiency. Data were collected through simulations and experimental measurements under standard operating conditions. The results show that optimizing system components, especially the compressor and expansion valve, can significantly improve energy efficiency. The COP increased by 12% when a high-efficiency compressor was utilized. In addition, the selection of eco-friendly refrigerants contributed to better thermal performance and reduced environmental risks. This research highlights the importance of thermodynamic analysis in designing and improving air conditioning systems for sustainable energy usage. Future studies are recommended to incorporate real-time monitoring and adaptive control systems to further enhance system performance and energy savings.

The use of foreign languages in the hospitality industry is very important considering the development of globalization and the increasing need for cross-country communication. This article aims to analyze the implementation of the use and assess the effectiveness of the use of foreign languages in the hospitality department of STIEPAR YAPARI Bandung so that challenges and obstacles in learning and application can be identified which will affect the skills and readiness of students in the Hospitality Industry. The research method used in this study is through a descriptive quantitative approach using a survey questionnaire to students majoring in Hospitality. The results showed that foreign languages have been integrated in the hospitality study program, the use of foreign languages is implemented through practice-based learning, hotel service simulations, and conversation habituation in foreign languages. However, challenges such as lack of student motivation and limited practice environment are still encountered. The implications of this study suggest the need to increase the intensity of language practice with more interactive teaching methods, as well as the provision of facilities that support foreign language learning, in order to improve students' language skills in the field of hospitality and prepare them to face the demands of the global hospitality industry.

Microplastics have emerged as a serious threat to tropical marine ecosystems in Indonesia, particularly in coastal areas with dense populations, major river estuaries, and busy shipping routes. This study aims to develop a predictive model of microplastic dispersion using partial differential equations based on ocean current data. The data set includes ocean currents derived from satellite imagery, global oceanographic models, and field observations, combined with information on microplastic sources from coastal human activities. The modeling process was conducted through numerical simulations using the finite difference method, taking into account geographic boundary conditions and numerical stability. The results indicate that the spatial distribution of microplastics is strongly influenced by seasonal current patterns closely associated with the Asian-Australian monsoon system. Microplastic concentrations tend to increase in areas with closed circulation and complex marine topography, with the highest accumulation identified in the Makassar Strait and the Java Sea. These findings highlight the critical role of ocean currents and other oceanographic factors in governing the transport and accumulation of microplastics in tropical seas. Ecologically, the outcomes suggest serious risks for coastal ecosystems, marine biodiversity, and the fisheries sector that supports Indonesia’s coastal communities. The implications of this study emphasize the need for more comprehensive marine environmental management strategies, strengthened field monitoring, and the integration of scientific models into plastic pollution control policies.

This study analyzes the influence of weather conditions on the efficiency of ship maneuvering in narrow waters. Maneuvering in confined areas such as rivers, straits, or ports becomes increasingly complex due to external environmental factors, particularly weather elements such as wind speed, wave height, and current direction. The research aims to identify and quantify how these weather variables affect the time, accuracy, and safety of maneuvering operations. A combination of field observations, ship maneuvering simulations, and data analysis was used to assess vessel performance under varying weather scenarios. The findings reveal that strong crosswinds and high waves significantly reduce maneuvering efficiency by increasing turning radius and delaying response times. These results imply the need for enhanced decision-making strategies and weather-adaptive navigational planning in narrow waterways. The study provides practical insights for shipmasters, pilots, and maritime authorities in optimizing maneuver operations under adverse weather conditions.

Entrepreneurship plays a crucial role in driving economic growth, with individual entrepreneurial intentions serving as a key supporting factor. Despite this, student involvement in entrepreneurial endeavors remains relatively low. This research seeks to examine how emotional intelligence and self-leadership influence entrepreneurial intentions among students at the University of Lampung. Employing a quantitative method with a causal approach, the study gathered primary data through questionnaires distributed to 183 sixth-semester students across various faculties. The research instruments underwent validity, reliability, and normality testing, and the data were analyzed using multiple linear regression. The findings confirmed the proposed hypotheses. Based on these results, the study recommends that higher education institutions, particularly the University of Lampung, implement character development initiatives and foster a positive student mindset. It also suggests creating more opportunities for reflection and open dialogue, incorporating problem-based learning models, and providing training in persuasive communication and soft skills. Furthermore, it emphasizes the importance of enhancing entrepreneurship curricula with practical experiences such as business incubators and simulations, while also improving student access to entrepreneurial support systems, including funding, mentoring, and market networks. These measures aim to boost student confidence in launching businesses and to strengthen the campus entrepreneurial ecosystem.

The threat of Distributed Denial of Service (DDoS) is increasing develop along with increasing use of the Internet of Things (IoT) and Software-Defined Networking (SDN) architecture . Although SDN provides convenience in management network , properties its centralized control make it prone to to flooding attacks that can paralyze controller performance . Detection method conventional , such as approach statistics and machine learning, still own limitations in matter accuracy , high false positive rate , and dependence on extracted features manually . To overcome problem said , research This propose a hybrid deep learning based DDoS detection and mitigation model that combines Convolutional Neural Network (CNN) to extraction feature spatial from RGB and Gated Recurrent Unit (GRU) images for understand temporal correlation between traffic data network . System tested through network test-bed Mininet based with Ryu/Floodlight controller, using simulation DDoS attacks (Hping3, LOIC) and normal traffic (video streaming, HTTP server). Traffic data cross recorded in PCAP format, processed become RGB image measuring 200×200 pixels, and labeled based on type traffic . Evaluation results with metric accuracy , precision, recall, F1-score, and MCC show that the CNN–GRU model has performance more superior compared to baseline approaches such as CNN-only, GRU-only, as well as classical ML methods such as SVM and Random Forest. In addition , the system capable apply mitigation adaptive through automatic flow rule creation on edge switches. Findings This confirm that effective deep learning- based spatial -temporal hybrid approach in increase detection early and response DDoS attacks on SDN networks adaptive and real-time.  

Bridge infrastructure is a vital component of transportation systems that is vulnerable to structural damage caused by dynamic loads, environmental factors, and aging. Early crack detection is crucial to prevent structural failures that may lead to catastrophic consequences. This study aims to develop a non-destructive detection method based on acoustic sensors to identify cracks in bridge structures with higher sensitivity and accuracy compared to conventional visual inspections. The research was conducted through laboratory experiments and field tests using acoustic sensors, data acquisition devices, and signal analysis software. The procedure included sensor installation on a bridge model, simulation of artificial cracks with varying sizes and positions, recording of acoustic wave signals, and data analysis using frequency spectrum, amplitude, and waveform pattern approaches. The results show significant differences between normal and cracked conditions in the frequency spectrum, where cracks produced amplitude anomalies at specific frequencies. Amplitude analysis revealed a positive correlation between crack size and acoustic signal intensity, while waveform pattern analysis demonstrated the influence of crack position on distortion levels. Cracks located at the center generated the highest distortion, followed by joints and edges. These findings confirm that acoustic sensors, particularly fiber-optic-based ones, offer advantages such as high sensitivity, reliability under complex environmental conditions, and the ability to detect subsurface cracks. The implications of this research highlight the potential development of an acoustic sensor-based structural health monitoring system integrated with real-time analysis software, thereby supporting preventive maintenance, extending infrastructure lifespan, and enhancing transportation safety.

The use of artificial intelligence (AI) in education holds significant potential to enhance the quality of learning and the effectiveness of teaching. This study aims to evaluate a teacher competency development program through the integration of AI, particularly in the development of AI-based teaching materials utilizing the Kelas Ajaib feature in the Canva application. The training involved 40 teachers from SMP Negeri 1 Kota Ambon and was conducted through workshops and interactive simulations. Evaluation results indicated an 85% level of participant enthusiasm and 86% satisfaction, reflecting a highly positive response to the program. However, teacher competence in creating AI-based instructional media reached only 75%, suggesting a need for further mentoring and improved supporting infrastructure. The main challenges identified included limited hardware availability and difficulties in adapting to new technologies. Therefore, follow-up training, enhanced technical support, and improved school facilities are recommended. Collaboration among educational stakeholders is essential to ensure the sustainability of AI integration in the learning process. Further research is recommended to examine the long-term impact of AI implementation on teaching quality and student engagement.