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This research focuses on the design and evaluation of a novel parallel graph optimization algorithm incorporating dynamic load balancing (DLB) to address inefficiencies in heterogeneous computing environments. Large-scale graph optimization problems, such as those in social networks, bioinformatics, and transportation systems, often suffer from computational imbalances when using traditional static load balancing approaches, leading to underutilized resources and prolonged execution times. The primary objective of this research is to develop an algorithm that can dynamically adjust workload distribution across processors, enhancing computational efficiency and scalability. The proposed method combines heuristic techniques, including region expansion and multilevel partitioning, with diffusive load balancing strategies to minimize inter-processor communication overhead. Experimental results demonstrate that the proposed algorithm reduces execution time by up to 40% compared to static methods, with optimized resource utilization and more balanced workload distribution. The scalability of the algorithm is also evident, as it adapts effectively to increasing problem sizes and processor counts. These findings suggest that dynamic load balancing is crucial for improving parallel graph optimization in real-world applications. Future work will focus on further enhancing the algorithm’s responsiveness to rapidly changing workloads and expanding its applicability to additional domains.

This study aims to analyze the operational condition of the distribution transformer at substation PY094, PLN ULP Pringgabaya, with a primary focus on identifying and calculating the level of load imbalance on the consumer side. Data were collected through direct measurements of electrical parameters, including voltage and current in each phase, followed by a detailed analysis of energy losses. The measurement results indicated a significant load imbalance. In Feeder B, the average phase currents were recorded at 103.8 A for phase R, 130.2 A for phase S, and 90.4 A for phase T. Meanwhile, in Feeder D, the average phase currents were 47.4 A for phase R, 18 A for phase S, and 20.4 A for phase T. This imbalance caused notable power losses in the distribution system, with an estimated daily energy loss of 28.94 kWh, assuming the system operates 12 hours per day. To address this issue, load balancing simulations were carried out using ETAP software. The simulation involved redistributing load values across each phase in the two main feeders. Feeder B was simulated at 46.82% of the transformer’s full capacity, while Feeder D was simulated at 12.38% of the total 160 kVA capacity. The simulation results demonstrated that redistributing the load significantly reduced the current imbalance, thereby minimizing power losses and improving the operational efficiency of the distribution substation. Therefore, load balancing strategies are essential for enhancing energy efficiency and ensuring the reliability of electricity supply in distribution networks.

Fatigue is a critical issue in labour-intensive small industries, especially in traditional food production such as tofu manufacturing. This study aims to develop a fatigue classification model using a decision tree algorithm by integrating subjective assessments of the work system through the Macroergonomic Organizational Questionnaire Survey (MOQS) and objective physiological indicators, specifically Cardiovascular Load (CVL). The research was conducted in a tofu home industry located in Kalisari Village, Banyumas, Indonesia. Primary data were collected from 10 workers through MOQS questionnaires and heart rate measurements taken at rest and during work. CVL values were calculated and used as labels for classification into three categories: low, moderate, and high fatigue. Meanwhile, MOQS dimension scores (organization, job, personal, environment, and technology) were transformed into interval data and used as classification features. A decision tree model was built using the CART algorithm and visualized for interpretability. The results show that all workers experienced at least moderate fatigue, with 20% categorized as high fatigue. The decision tree revealed that the dimensions of organizational and personal factors were the most influential in predicting fatigue levels. The model provides a practical and interpretable tool to support decision-making in scheduling, workload balancing, and ergonomic interventions. This study demonstrates a novel approach to combining macroergonomic assessments and physiological data with machine learning for practical fatigue risk management in small-scale food production environments.

The optimization of thread management in operating systems is essential to improve the performance of multithreading-based applications. This study analyzes various techniques to enhance thread management efficiency, including thread pooling, dynamic scheduling, load balancing, and synchronization contention reduction. Experimental results indicate that thread pooling reduces overhead by reusing threads, while dynamic scheduling improves multitasking responsiveness by prioritizing urgent tasks. Load balancing ensures equitable workload distribution across processor cores, minimizing execution time. Furthermore, reducing synchronization contention using mechanisms like semaphores decreases thread waiting time, thereby boosting application performance. These optimizations enable modern operating systems to efficiently utilize multi-core architectures, improving speed, responsiveness, and user experience. This research highlights the importance of thread management optimization as a foundational step towards developing adaptive and scalable operating systems for future complex and data-intensive applications.

As cloud computing advances, organizations' IT infrastructure and application deployment processes are moving to the cloud because cloud computing provides everything as a service over the Internet. The performance of a cloud-based application is based on proper datacenter selection and workload distribution within the selected datacenter. Service broker policies are used for suitable datacenter selection, and load balancing algorithms(LBA) are applied to distribute workloads. This paper is to evaluate the effect of a proposed service broker policy (PSBR) on the performance of cloud-based applications with LBA. To achieve the objective, the behavior of the TikTok application was modeled using the worldwide users’ statistics on the cloud simulation framework, namely CloudAnalyst. As a result, the average response time and data center processing time are measured. Next, the PSBR provides better results than the existing service proximity-based policy. This paper supports cloud service providers' benefits, from coordination between data center configuration, data center selection, and workload distribution to cloud users' identification of the appropriate procedures for their organization or application. PSBR with Active Monitoring had the best average response time of 75.1 ms, while SPR consistently exhibited higher average times across all algorithms, with the highest being 84.5 ms for Round Robin. Under the PSBR policy, Throttled had the lowest average processing time (4.67), while Round Robin had the highest (5.72). Similarly, under the SPR policy, Throttled maintained its efficiency with the lowest average (4.8), while Round Robin showed the highest (5.79).

This research aims to develop a network security system with AdGuard DNS on Debian Linux and control time-based internet access using the Microtik Routerboard. The main challenges are rising network security threats and the need for efficient internet access management in a variety of environments, including families,, education, and offices. The aim of this study is to improve network security and efficiency by blocking harmful content and advertisements, ining user privacy, and regulating internet access at a specific time. Technologies used include DNS AdGuard on Debian Linux to strengthen protection against network security threats and RouterOS Microtik devices to manage internet access based on time. These technologies include content filtering features, network traffic distribution (load balancing), and the ability to block unwanted sites to enhance network performance. Research results show that the combination of AdGuard DNS and   Microtik Routerboard is an effective solution to enhance network security and efficiency. The system is capable of blocking harmful content and advertising, improving user privacy, and adjusting internet access as needed, thus creating a more secure, controlled, and optimal network.

This research explores increasing the efficiency of network resource use through load balancing techniques. Load balancing distributes workload evenly among servers to optimize resource usage, maximize throughput, and minimize response time. We compare various load balancing algorithms, such as round-robin, least connections, and least response time, in various network scenarios. Experimental results show that proper load balancing techniques can reduce response time by up to 30% and increase resource usage efficiency by up to 40%. This study highlights the importance of selecting appropriate algorithms based on network traffic and workload characteristics. Implementing effective load balancing strategies can improve the quality of network services and ensure even distribution of workloads, providing practical guidance for network administrators to optimize network performance and efficiency.

Computer networks and the Internet are currently developing very rapidly, especially the role of the internet as a source of information, demanding excellent connection quality. Hotel Puri Indah Mataram, for example, has used two internet service providers (ISP) to handle the surge in demand from customers/guests. When there is an increase in requests, network devices become burdened because they have to process more requests. One solution is to implement load balancing, namely distributing the traffic load to network devices so that it is not centralized on just one ISP. This aims to ensure traffic runs optimally, increase throughput, speed up response time, and prevent overload on one connection line. This technique will optimize network performance by utilizing a two-path connection distribution method known as the NTH method. In addition, a failover technique will be implemented, where if one gateway connection is lost, another gateway will automatically take over all network traffic. This aims to ensure continuous service availability. Finally, there will be bandwidth management for all clients, so that bandwidth distribution becomes more even and efficient.

Reliable and high-performance Internet access is essential to support practical activities in the IBN Lampung Computer Laboratory. Dependence on a single ISP often leads to connection disruptions, reduced service quality, and interruptions in the learning process. This study aims to design and implement a Mikrotik-based load balancing system to improve Internet performance by utilizing two ISP links and providing an automatic failover mechanism when one link becomes unavailable. The research employs the Network Development Life Cycle (NDLC) approach, which includes network requirement analysis, multi-WAN topology design, implementation of load balancing and failover configurations on Mikrotik, and performance testing. The results show that the load balancing system successfully distributes traffic more evenly, enhances connection stability, and provides more consistent Internet speed. Additionally, the failover mechanism works effectively and ensures service continuity when an ISP experiences downtime. In conclusion, the implementation of a Mikrotik-based load balancing system effectively improves Internet access quality and supports smoother laboratory activities.

Implementation of Distance Learning (PJJ) is effective in the teaching and learning process during the pandemic. This is supported by Unisbank students in mastering information technology. PJJ technology, also known as e-learning, is a bridge between lecturers and students in the process of meeting in class into a meeting process in cyberspace. E-learning becomes ineffective when the demand for e-learning usage is high, causing server overload or crashes. When the e-learning server is overloaded, all parts that are usually connected and interrelated, such as lecturers, students, administration and others, become disconnected. The importance of monitoring the e-learning server to keep the e-learning load under control, and the server that has a lot of load will be divided so that e-learning will run smoothly and not be overloaded. Monitoring the Elearning server with the Least Connection method is applied to the Unisbank e-learning server and makes e-learning not overloaded. The results of the load balancer workload test with 1000 connections, the resulting response time is 0.2 ms, the workload is 5000 connections, the response time is 0.2 ms and the workload is 10,000 connections, the resulting reply time is 0.2 ms.

In the process of distributing electricity from the generator to the consumer, it goes through many processes and passes through several parts. Starting from the electric power distribution system, one of which is the distribution system. Considering that the scope of this distribution network is directly related and is located in an inhabited area, in addition to meeting technical quality requirements, it must also meet the requirements for being safe for users and familiar with the environment. In this distribution system there is a very important equipment in distributing electric power, namely the distribution substation. Because of the important role of the distribution substation, it must be protected from disturbances that may occur. One of them is the load imbalance between phases. In practice and in reality, in various locations of electric power distribution, a completely balanced load condition is obtained, mainly because of the large number of single-phase load groups that are serviced by a low-voltage three-phase distribution system. This is because the characteristics and types of electrical power user equipment vary with different consumer conditions and activities. To obtain load balance, load balancing is carried out between phases for load distribution so that load adjustments occur at distribution substations.

Load imbalance in three-phase distribution transformers can increase neutral current and power losses, thereby reducing the efficiency and reliability of electric power distribution systems. This study aims to analyze the level of load imbalance, power losses caused by neutral current, and the effectiveness of manual load balancing using the two-time-point method, namely peak load time (PLT) and off-peak load time (OPLT). The research was conducted on the PNIAI007 distribution transformer at PT PLN (Persero) ULP Enarotali using a quantitative descriptive approach with a case study design. Data were obtained through measurements of phase currents and neutral current, which were then analyzed to compare conditions before and after load balancing.The results show that the load imbalance level was significantly reduced from more than 29% to 2.47% during daytime operation and 1.21% during nighttime operation. The neutral current decreased from 37.81 A to 14.58 A during the daytime and from 51.76 A to 19.83 A at night. In addition, power losses due to neutral current were reduced by more than 85%. These results indicate that the two-time-point load balancing method is effective in improving the efficiency and operational reliability of distribution transformers.