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Technological advancements, particularly in microcontrollers and the Internet of Things (IoT), have brought significant changes to various aspects of life. Microcontrollers such as the ESP32, DS18B20 sensor, water pH sensor, and other supporting sensors enable the development of efficient automation systems. This research addresses issues related to the design and development of IoT devices for water quality monitoring, as well as the integration of these devices with web-based systems. The objective is to develop a device capable of monitoring water quality parameters such as pH, temperature, turbidity, dissolved materials, salinity projection, and dissolved oxygen projection, while providing automatic notifications under certain conditions. The development process applies the Agile methodology, which allows for rapid and adaptive iterations. Theoretically, this study contributes to improving understanding of IoT implementation and information systems, while practically, it provides a technological solution to support Koi fish farmers in monitoring and managing pond water quality. The expected outcome is a web-based water quality monitoring and management device for Koi ponds that can deliver real-time information and condition notifications, thereby reducing aquaculture risks and improving productivity.

This study examines the phenomenon of creator teachers on TikTok as a form of digital professionalism that represents the integration of ethical values, aesthetics, and educational philosophy. The focus of the research lies in how teachers negotiate moral responsibility and creative expression in the algorithmic culture of social media. The aim of this research is to analyze the philosophical meaning behind teachers' digital representations as well as interpret how moral and aesthetic values are reflected in their pedagogical practices. The method used is digital netnography with four stages: online observation, digital documentation, audience interaction analysis, and researcher reflection. A total of eight teacher accounts were analyzed with a total of 80 videos using a categorization of themes that focused on ethics, aesthetics, and professionalism. The results showed that 62.5% of the content was educational and featured learning innovations, while the other 37.5% contained elements of entertainment and social interaction. High audience interaction shows public appreciation for the creativity and integrity of teachers. Popularity is not solely generated by algorithms, but by the appreciation of moral values and pedagogical beauty in the actions of teachers. Based on the framework of arete and phronesis from Aristotle and the concept of aesthetic experience from Dewey (1934), this study concludes that the digital professionalism of teachers is a form of reflective praxis that combines ethical responsibility and creative expression. This research makes a theoretical contribution by integrating digital netnography and educational philosophy, and shows that teachers in the digital era play the role of moral and creative agents who maintain the dignity of their profession in the algorithmic space.

Quality control is a crucial aspect in various fields, such as education, the food industry, and manufacturing, as it functions to maintain the consistency of service or product quality. Inaccuracy in managing quality can cause financial losses, damage an institution's reputation, and reduce stakeholder trust. Based on this urgency, this study reviews recent literature to answer the main question of how quality control strategies can be effectively applied in diverse organizations. The review was conducted through a qualitative literature review approach by exploring scientific publications via Google Scholar and the Publish or Perish (PoP) application. Article selection was based on the relevance of keywords related to quality control and was limited to publications from 2020–2025. Out of 24 articles found, filtering was done until 5 of the most relevant articles remained for in-depth analysis. The analysis reveals three main findings. In higher education, a strong internal quality system and a sustainable quality culture are needed. The food industry emphasizes the standardization of raw materials and optimization of production processes. Meanwhile, the manufacturing sector makes extensive use of statistical techniques and tiered inspections. Overall, the effectiveness of quality control requires a combination of technical, managerial, and organizational culture aspects. Future research is recommended to explore the integration of digital technology and sustainability principles in quality control practices.

This study aims to analyze the process of acculturation between Buddhism and local culture in Indonesia, particularly in the context of the formation of a unique and historically relevant Nusantara Buddhist identity. The focus of the study includes the integration of the Tri Pitaka teachings with local cultural values, practices, language, art, and rituals to create a form of religious practice that is adaptive and meaningful for the local community. The research method used is a descriptive qualitative approach, with data collection techniques through observations of religious practices, interviews with religious and community leaders, and literature studies of relevant texts, inscriptions, historical artifacts, and scientific works. Data were analyzed interpretively through reduction, thematic grouping, and narrative construction that connects field phenomena to historical, social, and cultural contexts. The results show that the acculturation of Buddhism in Java is harmonious and multidimensional. The integration of Buddhism with local culture is manifested in the adaptation of ritual language, temple relief sculptures, ritual traditions such as Javanese puja bhakti (prayer offerings) and slametan (celebration ceremonies), and practices of respect for parents that align with Buddhist teachings. The Buddhist identity of the Indonesian archipelago is created through a synthesis of universal Buddhist values ​​and local culture, strengthening social cohesion and serving as a means of moral education for a multicultural society. This research contributes to the understanding of religious and cultural acculturation and opens up space for further study of the dynamics of religious integration in Indonesia.

In the digital era, the erosion of moral values among young people has become a pressing challenge for Islamic Religious Education (PAI). Folktales, as part of Indonesia’s cultural heritage, offer universal moral lessons that resonate with Islamic principles. This study investigates the potential of folktales as instructional media for instilling Islamic values while addressing the demands of digital-based learning. A qualitative descriptive method was applied, involving textual analysis of folktales, classroom observations, and interviews with teachers and students. The selected stories Malin Kundang, Bawang Merah Bawang Putih, Timun Mas, and Lake Toba were examined to identify moral values consistent with Qur’anic and prophetic teachings. Data were analyzed using reduction, presentation, and conclusion drawing, supported by triangulation to enhance validity. The results reveal that folktales embody key Islamic values such as filial piety, honesty, patience, courage, and loyalty to promises. Their integration into PAI classes not only increased student attention and emotional engagement but also encouraged deeper moral reflection. Moreover, digital adaptations through animations, videos, and digital storytelling expanded their relevance to contemporary learners, although challenges remain in teachers’ digital literacy and the need for contextual reinterpretation. This study concludes that folktales are more than cultural narratives; they are strategic tools for moral education. By leveraging digital innovation, folktales can reinforce character formation, sustain the relevance of PAI, and prepare Muslim students to be adaptive and value-driven in navigating modern society.

This study aims to examine how the concept of deliberative democracy is perceived and constructed within the intellectual discourse of Indonesian Muslim scholars. Employing a qualitative approach through literature analysis, data were gathered from academic works, including books, journal articles, and relevant conference proceedings. The analysis was conducted thematically to identify key patterns, categories, and overarching themes. The findings reveal three main points. First, the literature highlights the compatibility between Islam and deliberative democracy through the reinterpretation of shūrā, which is framed as a normative foundation aligned with modern practices of consultation. Second, the study identifies structural and cultural barriers—such as political polarization, elite dominance, and limited public space—that hinder substantive deliberation. Third, it highlights the potential for strengthening deliberative democracy through the integration of Islamic values, particularly by emphasizing maqāṣid al-sharīʿah, the ethics of justice, and the recognition of pluralism. In addition, the research introduces new categories, namely ethical deliberation and the rise of digital deliberation, both of which enrich the Indonesian model of deliberative democracy. Ultimately, the study concludes that deliberative democracy grounded in Islamic ethics is not merely a localized adaptation of Western theory but also makes a significant theoretical contribution to the broader development of deliberative democracy in the global context.

Natural Science (IPA) learning is an important foundation in developing students' scientific literacy, critical thinking skills, and scientific attitudes. However, the learning process still faces many challenges related to low learning interest, the dominance of conventional methods, and limited use of technology. This article aims to analyze the effectiveness of innovative approaches in science learning through a systematic review of 25 national and international journal articles published in 2020–2025. The systematic review method was carried out through the stages of identification, selection, data extraction, and thematic analysis. The results of the analysis show that the Problem-Based Learning (PBL), Inquiry-Based Learning (IBL), STEM Learning, and digital technology integration (PhET Simulation, mobile learning, gamification, blended learning) approaches have been proven to have a positive impact on learning outcomes, critical thinking skills, creativity, and student motivation. The thematic analysis resulted in four main themes: (1) strengthening critical thinking skills through PBL, (2) developing creativity and scientific literacy through IBL, (3) STEM integration to improve collaboration and scientific attitudes, and (4) utilizing digital technology for motivation and understanding abstract concepts. This study concludes that a combination of various innovative approaches is needed to make science learning more relevant to the demands of the 21st century.

This study aims to analyze the application of deep learning in the transformation of religious moderation education in the digital era and its implications for the development of modern Islamic education. The research employs a qualitative descriptive approach using library research, reviewing literature on Islamic education, religious moderation, and artificial intelligence in learning contexts. Data were collected from academic books, scientific journals, articles, and other credible sources, then analyzed using content analysis to identify patterns, concepts, and relationships between technology and the strengthening of moderation values. The results indicate that the implementation of deep learning can transform Islamic education from a traditional rote-based model to a reflective, contextual, and interactive learning process. This technology enables the analysis of students’ thinking patterns and behaviors, the reinforcement of moderation values, character formation, and the development of moderate digital literacy in a personalized and adaptive manner. The integration of technology and spirituality in digital Islamic education creates transformative learning experiences that strengthen empathy, ethical awareness, and students’ reflective capacities. The study implies the importance of developing curricula, learning strategies, and teacher competencies based on artificial intelligence to produce a generation of students who are moderate, tolerant, and competent in facing the challenges of the digital era.

This study aims to analyze the strategic role of the shipping agent, specifically PT. Naval Global Trans Belawan Branch, in ensuring the smooth flow of the maritime logistics chain. The shipping agent functions as a crucial intermediary coordinating contasiner distribution, bridging the interests of cargo owners, shipping companies, and the Belawan Port authority. The research utilizes a descriptive qualitative approach, with data collection performed through field observation and documentary study within the Belawan Port environment. The findings identify that the shipping agent holds broad responsibilities, commencing with container booking according to the required type and size, scheduling vessel arrivals and departures, managing customs and port documentation, and monitoring container movements (from the depot to loading onto the vessel). This role is highly instrumental in determining port throughput efficiency. However, in carrying out its functions, the shipping agent encounters several significant challenges. These constraints include limited container availability, disruptions in the port information system which is not yet optimally integrated, and dynamic changes in export-import regulations. These obstacles potentially cause operational delays and an increase in logistics costs. The study concludes by emphasizing the importance of better information technology integration between the shipping agent and the port authority. Furthermore, enhancing the quality of human resources (HR) through training and certification is key to ensuring that agents can respond to regulatory changes and operational challenges quickly and professionally.

This study aims to design and develop a web-based information system for managing socialization services at the Regional Disaster Management Agency (BPBD) of Banyuwangi Regency. The existing problem is that socialization data management is still carried out using Google Forms and Google Sheets separately, which causes difficulties in integration, monitoring, and reporting activities. This study uses the Research and Development (R&D) method with the Waterfall software development model which includes the stages of needs analysis, design, implementation, testing, and system maintenance. The results show that the developed web-based information system allows input, storage, and presentation of socialization activity data in real-time in one integrated dashboard. This system can simplify the process of monitoring, evaluation, and preparation of activity reports, while increasing the efficiency and accuracy of data management. With this system, BPBD Banyuwangi is expected to provide socialization services to the community in a more effective, transparent, and timely manner.

Wonogiri Regency in Central Java Province has great potential for sustainable tourism development, particularly through the integration of nature and religious tourism. This study aims to analyze the development strategy of the Watu Cenik Tomb in Sendang Village as a pilgrimage destination, which involves the historical value of the tomb of the Kyai Solo Sumarto IX family, the natural landscape of the Gajah Mungkur Reservoir, and cultural traditions such as Grebeg Syawalan. Using Richard Butler's Sustainable Tourism theory with the Tourism Area Life Cycle (TALC) model, this study applies a descriptive qualitative method through intensive interviews, observations, and documentation of stakeholders such as tourism managers, local communities, and tourists. The results of the study show that Watu Cenik has the potential to be an attractive pilgrimage destination, but its appeal is not yet optimal, with visits limited to private pilgrimages and the local community. The efforts of BUMDes Sendang Pinilih, such as the construction of homestays, shuttle services, and social media promotion, have increased visitor numbers, but additional facilities such as souvenir kiosks, local culinary offerings, photo spots, tour guides, and infrastructure improvements are still needed to attract more visitors and support the creative economy. The research conclusion emphasizes the importance of intensive digital promotion, integrated tour packages, and stakeholder collaboration to realize sustainable tourism that preserves cultural heritage while improving community welfare. Suggestions for further research include integrating mixed methods with quantitative analysis to measure economic impact and comparisons with similar destinations.

This research looks into the transparency and accountability in the promotion process for civil servants at the Regional Civil Service Agency (BKD) of Sidoarjo Regency as a component of the continual bureaucratic reform aimed at achieving clean and professional governance. Overall, the promotion process has embraced the digital-based Sidoarjo Smart ASN system and adheres to the merit principle, although obstacles persist in achieving completely transparent and accountable practices. The study centers on four key areas: transparency of public information, responsibility in decision-making, the validity of the merit system, and the efficiency of internal oversight and citizen engagement. A qualitative descriptive method utilizing a case study approach was employed, incorporating in-depth interviews, direct observations, and the analysis of official documents. The results indicate that transparency continues to be administrative in character, accountability is focused vertically instead of being horizontally accountable to the public, and the merit system encounters challenges linked to bureaucratic culture and the integration of competency data. Additionally, internal oversight does not have enough community engagement in assessing promotion procedures. The research suggests improving transparency via interactive publishing, establishing accountability systems based on performance, boosting independent evaluation capabilities, and incorporating digital oversight tools with public engagement. These results are anticipated to provide a basis for creating a civil service management model at the regional government level that is more transparent, accountable, and grounded in integrity.

Infertility is a reproductive health issue that not only affects biological aspects, but also causes significant psychological burdens, particularly anxiety in women. In the context of Saudi Arabian culture, which has strong pronatalist values, infertile women often face social and emotional pressures that can exacerbate their psychological condition. Social support is seen as a protective factor that plays an important role in helping individuals adapt to the stress of infertility. This study aims to analyze the relationship between the level of social support and the level of anxiety in Saudi women facing infertility at the Dr. Sulaiman Al-Habib Takhassusi Branch, Riyadh. This study uses a quantitative approach with a cross-sectional analytical observational design. The research sample consisted of 30 infertile women selected using consecutive sampling techniques. The levels of social support and anxiety were measured using a standardized questionnaire, then analyzed using Spearman's correlation test with a significance level of 0.05. The results showed that most respondents were aged 20–35 years and experienced primary infertility. The Spearman test showed a statistically significant relationship between the level of social support and the level of anxiety (p = 0.000) with a correlation coefficient of r = 0.625, indicating a moderate to strong positive relationship. This indicates that women with higher levels of anxiety tend to receive or seek more intense social support. In conclusion, social support plays an important role in the dynamics of anxiety in infertile women. The integration of structured psychosocial support into infertility services is essential to improve patients' psychological well-being and quality of life.

This study investigates the comparative effectiveness of three primary organizational structures—functional, product-based, and geographic—in facilitating global marketing strategies. Employing a qualitative methodology through in-depth case studies of six multinational corporations across the technology, pharmaceutical, and consumer goods sectors, the research highlights the nuanced interplay between organizational design and strategic marketing execution. Findings indicate that no single structure universally outperforms the others; rather, effectiveness is contingent upon specific contextual factors such as product complexity, market diversity, and the degree of global integration versus local responsiveness required. Functional structures tend to support centralized control and efficiency, while product-based structures enhance innovation and brand focus. Geographic structures, on the other hand, offer adaptability to regional market dynamics. The study underscores the importance of strategic alignment between organizational form and marketing objectives, suggesting that hybrid or flexible configurations may offer optimal outcomes in dynamic global environments. These insights provide actionable guidance for decision-makers in selecting or adapting organizational structures to better support international marketing efforts. Ultimately, the research contributes to a deeper understanding of how structural choices influence global competitiveness and responsiveness, offering a framework for organizational design that aligns with evolving market demands and strategic priorities.

This study investigates the simultaneous and individual effects of School-Based Management (SBM), principal supervision, transformational leadership, and work culture on the performance of junior high school teachers in Serang City, Indonesia. Against the backdrop of the Merdeka Curriculum and the shift to hybrid learning in the post-pandemic era, the research addresses persistent challenges such as hierarchical school cultures and technological disparities. Employing a quantitative ex post facto approach, data were collected from 316 teachers across public and private schools through structured questionnaires, classroom observations, and document analysis. Multiple linear regression analysis reveals that SBM, principal supervision, transformational leadership, and work culture each have significant and positive impacts on teacher performance, with transformational leadership and work culture exerting the most substantial influence. The results demonstrate that 74% of the variance in teacher performance can be explained by these four organizational factors, underscoring their critical role in shaping pedagogical competence, classroom management, and professional development. The study further highlights the necessity for comprehensive managerial training, the integration of technology in supervisory practices, and the cultivation of collaborative and innovative work cultures. Practical recommendations include enhancing principal leadership capacity, fostering instructional supervision, and investing in digital infrastructure to support sustainable improvements in teacher performance. The findings contribute to the body of knowledge on educational management in Indonesia and offer actionable insights for policymakers, school leaders, and educators aiming to strengthen teacher effectiveness amidst ongoing educational reforms and digital transformation.

The increasing demand for cloud computing services has led to the rapid expansion of cloud data centers, which consume significant amounts of energy and contribute substantially to global CO2 emissions. As the IT industry grows, the environmental impact of these data centers becomes an urgent concern. Green Cloud Computing (GCC) has emerged as a solution to mitigate this impact by focusing on energy efficiency and reducing carbon footprints while maintaining the necessary functionality and performance of cloud infrastructures. However, traditional blockchain consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) face limitations regarding energy consumption and scalability, which exacerbates the environmental burden. This study proposes a quantum-inspired blockchain consensus algorithm designed to optimize energy consumption and reduce latency in cloud data centers. By integrating quantum principles such as superposition and entanglement, the algorithm enhances task scheduling and resource utilization, enabling more energy-efficient operations without sacrificing performance. Simulations in a green cloud environment showed that the quantum-inspired algorithm resulted in up to a 30% reduction in energy usage compared to traditional consensus methods, with a 40% improvement in consensus processing time. These results suggest that quantum-inspired algorithms hold significant potential for enhancing the sustainability of cloud infrastructures by improving energy efficiency and scalability. Furthermore, this study discusses the feasibility of implementing quantum-inspired algorithms on classical hardware, addressing challenges in scalability and integration into existing blockchain frameworks. The findings provide valuable insights into the potential of quantum-inspired technologies to drive energy-efficient solutions in cloud computing.

The integration of Augmented Reality (AR) and Explainable AI (XAI) within Cyber-Physical Systems (CPS) design is transforming the industrial automation landscape. This study explores how combining AR’s immersive visualization with XAI’s decision transparency enhances collaborative design processes in CPS. The AR-XAI platform developed in this research improves team collaboration by offering real-time visual feedback and enabling interactive decision-making. The platform provides interpretable insights into AI-driven decisions, fostering trust among engineers and decision-makers. Key features of the platform include the ability to visualize complex CPS models, facilitating faster iterations, reducing design errors, and improving design accuracy. The integration of XAI ensures transparency in decision-making by offering clear explanations of AI predictions, which is essential for ensuring accountability and building trust in automated systems. Testing with industrial engineers confirmed that the AR-XAI platform significantly improved design outcomes, with a reduction in errors and enhanced team performance compared to traditional design methods. Moreover, the platform enabled faster decision-making and improved collaboration across diverse teams, demonstrating its potential to optimize CPS design workflows. This research provides valuable insights into the role of AR and XAI in advancing Industry 4.0 and paves the way for more advanced integrations of these technologies in industrial settings. Future research should focus on developing scalable solutions for various industrial applications and exploring more sophisticated AR-XAI integrations for emerging fields like smart cities and autonomous manufacturing.

The integration of blockchain technology with Multi-Agent Reinforcement Learning (MARL) presents a promising solution for optimizing resource allocation and ensuring security in decentralized network environments, particularly in 5G and 6G network slicing. This research proposes a model that combines the security features of blockchain with the adaptive, decentralized decision-making capabilities of MARL. Blockchain ensures the integrity and transparency of resource allocation by providing a secure, tamper-proof ledger for transaction validation, while MARL allows agents to dynamically allocate resources based on real-time network conditions. The simulation results demonstrate significant improvements in resource allocation efficiency, fairness among users, and resilience to cyberattacks. By combining these two technologies, the proposed model overcomes many of the challenges posed by traditional centralized systems and offers an enhanced, secure, and fair solution for resource distribution in future mobile networks. However, scalability remains a challenge, especially in large-scale networks where transaction processing and consensus overhead can create bottlenecks. Additionally, training complexity in MARL models presents computational challenges, particularly in highly dynamic network environments. The model's performance trade-offs, including the balance between high security and system overhead, are also discussed. Future research should focus on optimizing blockchain consensus mechanisms to improve scalability and enhancing MARL model training techniques to reduce computational costs and improve real-time decision-making. This integration holds significant potential for revolutionizing resource allocation in 5G and 6G networks, enabling more efficient, secure, and fair management of network resources in the increasingly complex and decentralized digital ecosystem

The rapid advancement of intelligent systems has accelerated the adoption of data-driven solutions across diverse industries, creating an increasing need for models that are both efficient and privacy-preserving. While traditional centralized machine learning approaches offer strong predictive capabilities, they often struggle with challenges related to data privacy, network latency, and computational inefficiency-especially in distributed environments with heterogeneous devices. To address these limitations, recent research has explored hybrid learning frameworks that integrate federated learning, edge computing, and dynamic model optimization techniques. These hybrid approaches enable models to process and learn from data closer to the source while maintaining stringent privacy requirements by keeping raw data localized. Additionally, the incorporation of pruning strategies, adaptive model compression, or multimodal data fusion contributes to improved speed, scalability, and accuracy in real-time inference tasks. Such frameworks have demonstrated notable promise in settings characterized by high data volume, operational complexity, and the necessity for fast anomaly detection or decision-making. However, despite these advancements, several challenges remain, including synchronization delays across edge nodes, variability in hardware capabilities, and the need for more efficient aggregation algorithms. Future developments may involve leveraging next-generation pruning techniques, energy-aware edge scheduling, decentralized orchestration protocols, or the integration of digital twin technologies to further enhance performance. Overall, hybrid distributed learning frameworks represent an important evolution toward more intelligent, secure, and autonomous computational ecosystems capable of supporting the next wave of smart applications.

The increasing integration and digitization of smart grid systems have exposed them to a variety of security threats, necessitating robust security measures to ensure their reliability and efficiency. This paper proposes a novel Digital Twin-Based Cyber-Physical Security Framework, incorporating AI-driven predictive maintenance and zero-trust architecture to address the evolving challenges of securing smart grids. By leveraging digital twin technology, this framework creates a real-time virtual representation of physical systems, enabling continuous monitoring and simulation for enhanced security and operational performance. Zero-trust security principles are integrated to ensure that no entity, whether inside or outside the network, is trusted by default, thus significantly reducing the risk of cyber-attacks. Additionally, AI-driven predictive maintenance enhances the framework’s reliability by proactively identifying potential failures before they occur, reducing downtime and improving system resilience. Through the development and simulation of this framework, including attack and failure scenarios, the paper demonstrates that the proposed system outperforms traditional methods in terms of anomaly detection, system downtime, and response times. The integration of predictive maintenance allows for early identification of component failures, thus enhancing the overall resilience of the grid. The zero-trust architecture further strengthens the cybersecurity posture, preventing unauthorized access and attacks. The study also identifies challenges, such as data synchronization and scalability, which must be addressed for broader implementation in large-scale smart grid systems. The findings suggest that the proposed framework could play a critical role in the future evolution of smart grid security, offering valuable insights for researchers and practitioners.