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This report presents a comprehensive overview of the crucial role of Proportional-Integral-Derivative (PID) control systems in maintaining an optimal environment for premature neonates in modern infant incubators. The main focus is directed on the effectiveness of the PID system in regulating vital physiological parameters such as temperature, humidity, and stability of the baby's body temperature, which greatly determine the survival and development of the neonate. The PID control system is proven to be able to provide a fast and accurate response to changes in environmental conditions, thus maintaining parameter stability in real-time. The integration of PID technology with modern incubator devices enables precise automatic setup, supports energy efficiency, and improves patient safety and comfort. The report also discusses various PID tuning methods, such as Ziegler-Nichols and adaptive methods, which are used to improve the performance of the system in the face of environmental dynamics and individual characteristics of infants. Implementation challenges identified include system complexity, need for periodic calibration, and limited technical resources in healthcare facilities. However, continuous innovations in control design and algorithms have driven the evolution of incubator devices to be more intelligent and responsive. Thus, the PID control system plays a central role in supporting neonatal life-support technologies, while representing significant advances in biomedical engineering and intensive care of premature infants.

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.

Background: Maritime engineering has traditionally relied on reactive and preventive maintenance strategies, often leading to operational inefficiencies, unplanned downtime, and excessive costs. With the rise of smart ship technologies, predictive maintenance (PdM) has emerged as a data-driven solution, leveraging sensor-based monitoring and real-time diagnostics to optimize ship maintenance. However, its integration into maritime education remains underexplored, particularly in training vessels used for vocational learning. Original Value: This research contributes new insights into the feasibility, effectiveness, and educational relevance of predictive maintenance in maritime vocational training. Unlike previous studies that focus on commercial ship applications, this study examines PdM within the context of training vessels at Poltekpel SULUT, bridging the gap between academic training and industry expectations. Objectives: The study seeks to answer: How does predictive maintenance improve the efficiency, cost-effectiveness, and reliability of naval auxiliary systems in training vessels? Methodology: A qualitative approach was employed, integrating sensor-based performance analysis, structured interviews, and questionnaire surveys involving cadets, instructors, and industry professionals. Data were analyzed through thematic categorization, cross-group comparisons, and narrative synthesis. Results: PdM demonstrated high effectiveness in reducing downtime (92/100), optimizing maintenance efficiency (91/100), and aligning with industry practices (89/100). However, challenges in sensor accuracy (85/100) and training integration were identified. Conclusions: The findings highlight the necessity of incorporating predictive maintenance into maritime training curricula to equip future engineers with the skills required for Industry 4.0 maintenance solutions, ensuring better operational efficiency and sustainability in the maritime sector.

The Fangowai and Fame’e Afo traditions are important parts of Nias traditional wedding ceremonies, rich in symbolic and social values. However, modernization, time efficiency, and economic pressures have influenced their implementation. This study aims to describe the social dynamics in the implementation of Fangowai and Fame’e Afo in three villages in Botomuzoi District: Hiligodu, Ononamolo Talafu, and Lasara, with a focus on changes in the form of the procession, causal factors, and the transformation of symbolic meaning. The approach used is descriptive qualitative through observation and in-depth interviews with community leaders. customs, society, and youth, as well as field documentation. Data were analyzed through data reduction, presentation, and conclusion drawing, and their validity was tested through source triangulation. The results showed a simplification of the time and stages of the procession, a reduction in the number of traditional figures, and an adjustment of the number of sacrificial pigs to reflect economic capacity. Symbolic transformation also occurred with the addition of cigarettes to the Bola Nafo ceremony, but the meaning of betel as a symbol of respect and brotherhood was maintained. These changes reflect the adaptation of the Nias people to the modern social context without losing the core values of tradition.

The Web-Based Academic Service Management Information System at SMA Negeri 2 Kodi Utara was developed to improve the effectiveness and efficiency of academic data management at the school. Currently, academic data management, including grade input, class schedules, teacher information, and academic reports, is still done manually, often causing delays and potential errors in recording. This study aims to design and create a web-based information system that can assist educational institutions in managing academic services in an integrated and real-time manner. The software development method used is the Waterfall model, which includes the phases of needs analysis, system design, implementation, testing, and maintenance. The programming language used is PHP with a MySQL database system. The result of this study is an academic management information system that can facilitate various academic activities, such as managing student data, teacher data, grades, class schedules, and academic reports. This system also makes it easier for teachers to input grades and provides fast and accurate access to academic information for students and the principal. With this system, the academic administration process at SMA Negeri 2 Kodi Utara becomes more organized, efficient, and transparent.

This study aims to analyze the financial risk of PT Smartfren Telecom Tbk during the 2014–2023 period, focusing on both short-term and long-term liquidity aspects. The analysis employs financial ratios as measurement tools to assess the company’s financial stability and its ability to fulfill financial obligations within their respective time frames. The ratios used include the current ratio, quick ratio, interest coverage ratio, and cash flow-to-debt ratio. The results indicate that the company faces significant challenges in maintaining short-term liquidity, as reflected in the consistently low values of the current and quick ratios throughout the observation period. This condition suggests a limited ability of the company to meet its short-term obligations using available assets. In terms of long-term liquidity, although there are efforts to strengthen the capital structure, the company still encounters difficulties in meeting its long-term debt obligations. This is evident from the low interest coverage ratio and cash flow-to-debt ratio. Therefore, improving operational efficiency, implementing more effective cash management, and undertaking financial restructuring are essential measures to strengthen the company’s liquidity position sustainably.

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.  

SMA Negeri 1 Maumere as one of the secondary education institutions continues to show development through improving the curriculum, infrastructure, and extracurricular programs. However, the tuition payment system that is still carried out manually poses various challenges in managing school financial administration. This study aims to analyze the effectiveness of the manual tuition payment system using the SWOT approach to identify the strengths, weaknesses, opportunities, and threats that affect the process. The results of the analysis show that although manual systems have been in use for a long time and are easy for financial officers to understand, they are still vulnerable to recording errors, process delays, and the risk of inaccurate data accumulation. In addition, the study found that the evaluation of this manual system makes an important contribution to the development of management science, especially in understanding the dynamics of administrative control and decision-making processes. The findings of the study recommend the development of a technology-based tuition payment system, such as online payments or integrated applications, as a solution to improve the efficiency, accuracy, and quality of administrative services at SMA Negeri 1 Maumere..

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

Modern industries require automation to enhance operational efficiency and productivity. This study designs and implements an automatic sorting system based on the Internet of Things (IoT) using a mini conveyor, ESP32 microcontroller, TCS3200 color sensor, servo motor, and the Blynk application. The system is designed to accurately detect object colors, sort objects based on color, and enable remote monitoring and control via mobile devices. Testing results indicate that the system can detect and sort objects with a high level of accuracy, although some errors occur due to changes in lighting conditions. The conveyor speed is consistently recorded at 0.335 m/s, while the system's response time, including color detection, servo movement, and application updates, operates within an optimal range. The Blynk application enhances the flexibility of real-time system control. This study demonstrates that IoT-based sorting systems can serve as an efficient solution to support industrial automation. Further development is recommended to improve color detection accuracy and expand the system's application in more complex industrial scenarios.

The development of information technology has accelerated digitization in various sectors, including in the decision-making process. In the DayTrans Shuttle service, the selection of the best route is still done manually using Microsoft Excel. This process is time-consuming, inefficient, and has the potential to cause errors and subjectivity. The purpose of this study is to design and develop a web-based decision support system by applying the Weighted Product (WP) method to determine the most optimal shuttle route objectively and efficiently. The research data was obtained through interviews, observations, and literature studies, then analyzed according to system requirements. The development was carried out through the stages of requirements analysis, database and interface design, implementation, and testing. The developed system is equipped with features for managing criteria data, alternative routes, weight calculations, and real-time presentation of recommendation results. The research results show that the system functions well, is able to speed up the route selection process, and produces accurate and transparent recommendations. Thus, this system is expected to improve DayTrans' operational efficiency while supporting the quality of inter-city transportation services.

This research aims to:1) To understand and analyze development of revenue, hotel tax and restaurant tax in North Tapanuli Utara from 2015-2023. 2) To understand and analyze the effectiveness, hotel tax, restaurant tax effectiveness, hotel tax efficiency, and restaurant tax efficiency in North Tapanuli Regency. This study uses time series data from 2015-2023, wihich is secondary data, to assess the efectiviness of hotel tax and restaurant tax revenue on local revenue (PAD) in North Tapanuli Regency. The data collection method used is library research, which utilizes literature or library materials as the primary data source. Quantitative descriptive analysis methods are used determine the develoment of PAD, tax development, restaurant tax development, hotel tax effectiveness, tax efficiency, and restaurant tax efficiency. The results of this study provide an overview of the development of PAD, development of hotel taxes, the development of restaurant taxes, the effectiveness of hotel tax revenue, restaurant taxes, hotel tax efficiency towards the original regional income (PAD) of North Tapanuli Utara Regency in 2015-2023. The average development of PAD in North Tapanuli regency is 10 percent, the average development of hotel taxes is 4 percent and the average development of restaurant taxes is 19 percent. The average effectiveness is 89 percent, which is classified as quite effective, the effectiveness of restaurant taxes reaches 91 percent which is classified as effective. The efficiency of hotel taxes is 5 percent which is classified as inefficient, while the efficiency of restaurant taxes is 107 percent which is classified as very efficient.

Appropriate technology innovation (TTG) in agriculture is an important solution in improving farmers' work efficiency, especially in the fertilization process. In Pamotan Village, where the majority of the population are tobacco farmers, the fertilization method is still done manually by sowing on the soil surface. This method often causes uneven distribution of fertilizer, wastage of energy and time, and a lot of fertilizer lost by water or wind. This community service activity aims to introduce a manual fertilizer sowing tool made from PVC as a simple, cheap, and easy-to-use solution for farmers. The implementation method includes counseling, tool demonstration, and direct training to farmer groups as activity partners. Evaluation was conducted through observation and questionnaires before and after the activity. The results showed an increase in farmers' understanding of efficient fertilization, as well as a positive response to the tools that were considered practical and economical. The use of this seedling tool can save up to 30% fertilizer and speed up the fertilization process by 40%. Thus, this manual fertilizer seedling tool is effective in helping farmers improve work efficiency and productivity, and is very suitable for small-scale farmers in rural areas.

Livestock production in rural communities relies heavily on the availability and quality of animal feed. In Aek Korsik Village, Asahan Regency, farmers continue to use manual methods to chop forage, which are time-consuming, inconsistent, and physically demanding. To address these issues, a portable forage chopper machine was designed and introduced through a community service program (KKN). The machine features a compact mechanical system powered by a small motor, making it lightweight, mobile, and easy to operate in various conditions. The implementation process included three stages: machine development, field testing, and community training. During testing, the machine efficiently processed forage materials like grass, corn stalks, and agricultural residues, producing uniform feed sizes much faster than manual methods. Farmers reported reduced workload, improved availability of chopped forage, and better livestock feeding practices. The portable design allowed the equipment to be shared among farming groups, fostering cooperation. This study underscores the role of appropriate technology in addressing rural agricultural challenges. By integrating engineering innovation with community service, the portable forage chopper machine enhances technical efficiency and socio-economic empowerment for farmers. Future improvements should focus on durability, cutting capacity, and sustainable energy alternatives to better meet the needs of smallholder farmers.

The Population and Civil Registration Office of Situbondo Regency faces challenges in improving the efficiency of recording and reporting the performance of Non-ASN employees, which has so far been conducted through temporary notes and documents. This approach is prone to delays, input errors, and suboptimal data management. To address this issue, this study aims to design a web-based information system capable of recording, managing, and displaying Non-ASN employee performance reports in a structured and real-time manner. The system is developed using PHP programming language and MySQL database to support dynamic and integrated data management. The system development follows the V-Model approach, which emphasizes verification and validation at each development stage, including requirement analysis, system design, module design, implementation, unit and integration testing, and maintenance. The result of this study is an information system that facilitates performance data entry, accelerates report generation, and improves accuracy and transparency in evaluating Non-ASN employee performance. In addition, the system is designed with a responsive web interface that is easy for stakeholders to use.

Equal access to education is a crucial issue in Islamic educational institutions in Indonesia. Ensuring that all students, without exception, have equal access to quality education is vital for the advancement of education in the country. In this context, Management Information Systems (MIS) play a crucial role in enhancing the efficiency, effectiveness, and transparency of educational services. The implementation of MIS can streamline administrative processes, improve decision-making, and facilitate more equitable access to educational resources. This research employs a literature study approach, relying on books and journal articles as primary sources. The findings indicate that the application of MIS provides significant benefits in terms of planning, management, and evaluation. By providing real-time data, MIS enables educational institutions to make better decisions, monitor student progress, and allocate resources more effectively. Additionally, MIS enhances the transparency of educational services, ensuring that all stakeholders—students, parents, and educators—have access to important information related to educational processes and outcomes. However, challenges in the implementation of MIS remain, such as technical barriers related to inadequate infrastructure and limited access to technology, as well as human resource issues like insufficient training. To address these challenges, the research recommends providing comprehensive training programs for educators and administrators, investing in technological infrastructure, and promoting data integration across educational institutions. Overall, while MIS offers many advantages in promoting equal educational access, addressing technical and human resource challenges is crucial to fully realizing its potential in Islamic educational institutions in Indonesia.

The integration of Internet of Things (IoT) with cloud computing has revolutionized healthcare systems, offering scalable and real-time patient monitoring. However, optimizing response times and energy consumption remains crucial for efficient healthcare delivery. This research evaluates various algorithmic approaches for workload migration and resource management within IoT cloud-based healthcare systems. The performance of the implemented algorithm in this research, Hybrid Dynamic Programming and Long Short-Term Memory (Hybrid DP+LSTM), was analyzed against other six key algorithms, namely Gradient Optimization with Back Propagation to Input (GOBI), Deep Reinforcement Learning (DRL), improved GOBI (GOBI2), Predictive Offloading for Network Devices (POND), Mixed Integer Linear Programming (MILP), and Genetic Algorithm (GA) based on their average response time and energy consumption. Hybrid DP+LSTM achieves the lowest response time (82.91ms) with an energy consumption of 2,835,048 joules per container. The outcome of the analysis showed that Hybrid DP+LSTM have significant response times improvement, with percentage increases of 89.3%, 79.0%, 83.8%, 97.0%, 99.8%, and 99.94% against GOBI, GOBI2, DRL, POND, MILP, and GA, respectively. In terms of energy consumption, Hybrid DP+LSTM outperforms other approaches, with GOBI2 (3,664,337 joules) consuming 29.3% more energy, DRL (2,973,238 joules) consuming 4.9% more, GOBI (4,463,010 joules) consuming 57.4% more, POND (3,310,966 joules) consuming 16.8% more, MILP (3,005,498 joules) consuming 6.0% more, and the GA (3,959,935 joules) consuming 39.7% more. The result of ablation of the Hybrid DP+LSTM model achieves a 47.05% improvement over DP-only (156.57ms) and a 70.64% improvement over LSTM-only (282.41ms) in response time. On the energy efficiency side, Hybrid DP+LSTM shows 22.80% improvement over LSTM-only (3,671,51 joules), but 7.34% underperformance compared to DP-only (2,640,93). These research findings indicate that the Hybrid DP+LSTM technique provides the best trade-off between response time and energy efficiency. Future research should further explore hybrid approaches to optimize these metrics in IoT cloud-based healthcare systems.

The DH Building of the Electrical Engineering Study Program at Udayana University faces significant challenges in energy efficiency, as it still relies on conventional electrical systems. User negligence, such as forgetting to switch off lights and air conditioners (AC) after use, often results in unnecessary energy waste and increased operational costs. This issue highlights the urgent need for smart solutions capable of automating energy management, reducing waste caused by human error, and supporting the creation of a more efficient and sustainable campus environment. To address this problem, this study designs and implements a smart building system based on the Internet of Things (IoT). The system employs a NodeMCU ESP32 microcontroller as the main processing unit, integrated with a series of sensors including a DHT22 sensor for monitoring temperature and humidity, an MQ2 sensor for smoke detection, a PIR sensor for motion detection, and a PZEM-004T sensor for monitoring energy consumption. Control of electronic devices such as lights and AC units is carried out both automatically and manually through relay modules connected to the system. All sensor data and control functions are accessed via a web interface developed using the Laravel framework and a MySQL database. The testing results indicate that the designed system was successfully implemented and functions as expected. Sensor testing demonstrated high accuracy compared to standard measuring instruments, while the electronic device control system achieved an average response time of approximately 3.6 seconds, proving its reliability. Overall, the system provides a comprehensive solution for energy consumption monitoring and control, while also enhancing comfort and safety in the DH Building, in line with the goals of energy efficiency and facility modernization.

Traditional herbal medicine MSMEs face challenges in increasing the appeal of their products among the younger generation who prefer fresh and modern drinks. To overcome this, innovation in the presentation of herbal medicine is needed to make it more practical, hygienic and attractive. One solution is the manufacture of a microcontroller-based portable box cooler that can maintain the freshness of herbal medicine at an optimal temperature. This box cooler is equipped with an automatic cooling system controlled by a microcontroller, ensuring the jamu stays fresh and high quality for a longer period of time. A temperature sensor monitors and adjusts the cooling conditions as needed, so that the herbs remain at their best when served. In addition, the automatic dispenser system helps regulate the volume of herbs dispensed precisely, reducing wastage and maintaining flavour consistency. With its portable and efficient design, this box cooler is perfect for use in various locations such as bazaars, cafes, offices, or community events. This innovation not only improves the efficiency and competitiveness of MSMEs, but also reinforces the image of jamu as a modern and contemporary healthy drink, making it more attractive to young consumers.

This study provides an in-depth analysis of the benefits of implementing a SAP-based Enterprise Resource Planning (ERP) system for end-users at PT XY, an Indonesian airport management company. A qualitative case study approach was applied through comprehensive in-depth interviews and direct observations of accounting division staff who actively utilize the SAP Financial Accounting (FI), Controlling (CO), and Materials Management (MM) modules as part of their daily operations. The findings demonstrate that SAP implementation significantly enhances work efficiency, data accuracy, and overall operational productivity across multiple business processes. The system facilitates seamless cross-departmental integration, reduces manual errors, accelerates financial reporting, and supports real-time, data-driven decision-making. Furthermore, SAP strengthens internal coordination by providing consistent, centralized, and easily accessible information to all relevant stakeholders. Key challenges identified include limited network access, server congestion during peak hours, and difficulties with remote connections when accessing the system outside the office environment. The company addressed these issues through regular user training, provision of secure Virtual Private Network (VPN) access, expansion of server capacity, and a strategic plan to migrate to cloud-based SAP S/4HANA to improve flexibility, scalability, and long-term system reliability. The findings not only enrich the literature on ERP adoption, with practical guidance for other organizations seeking to plan, implement, and evaluate ERP systems to meet their own business needs, including effective human resource planning and change management strategies.