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This paper presents a computational approach to addressing complex challenges in fluid dynamics and thermodynamics. The study begins by exploring the fundamental principles and challenges in these fields, emphasizing the importance of efficient computational methods for analyzing fluid flow and thermal behavior in various engineering applications. The primary objective is to develop a robust computational framework that integrates advanced numerical techniques and simulation tools to enhance accuracy and efficiency. The methodology involves implementing high-fidelity simulations using finite volume and finite element methods, validated against benchmark problems and experimental data. The findings demonstrate significant improvements in predictive capabilities, offering insights into fluid-thermal interactions under various conditions. These advancements hold practical implications for optimizing engineering systems, such as energy conversion, heat exchangers, and aerodynamics. This research contributes to the ongoing efforts to bridge theoretical knowledge and practical applications in fluid dynamics and thermodynamics.

Quantum computing has emerged as a transformative technology with the potential to revolutionize numerical methods in scientific research. This study explores the integration of quantum algorithms to enhance the efficiency and accuracy of computational techniques used in solving complex scientific problems. The objective of this research is to investigate how quantum computing can address limitations in classical numerical methods, particularly in areas such as optimization, simulation, and data analysis. By employing quantum-enhanced algorithms, such as quantum Monte Carlo and quantum machine learning, the study demonstrates significant improvements in processing speed and solution quality. The findings highlight the capability of quantum computing to tackle challenges in high-dimensional computations and provide novel insights into scientific phenomena. These advancements have profound implications for disciplines ranging from physics and chemistry to material science and beyond, paving the way for a new era of computational-driven discoveries.

Participation from all parties is important in post-disaster rehabilitation and reconstruction because it is the most complex activity in disaster management from the planning process, funding, and implementation. A Tsunami that struck Sunda strait in December 2018 caused a great loss and immediate response is necessary. The delay of rehabilitation and reconstructions affected the stability of national security. Therefore, all parties need to take part in post-tsunami recovery so that the disaster recovery process implemented effectively and efficiently. The purpose of this study was to analyze the participation of society in the post-tsunami rehabilitation and reconstruction management in Pandeglang district, coordination networking, and contributions to national security. The qualitative method is used in this research from the primary and secondary databases. For the purposes of this study, the primary data were gathered through face-to-face interviews from the subjects of research who were chosen based on purposive sampling and snowball methods. The data analyzed qualitatively and simulation by UCINET 6 is used for coordination networking. The result shows that all parties had taken part in the Pandeglang post-tsunami recovery management from the planning process, implementation, monitoring, and evaluations. The level and form of community participation are diverse.

Quantum computing offers promising alternatives to classical approaches for solving complex linear algebra problems. This paper presents a comparative study of the performance of quantum algorithms versus classical algorithms in solving systems of linear equations and matrix operations. Through simulation and analysis, we demonstrate that while quantum computing holds advantages in specific problem sets, classical computing remains efficient for general applications. These findings highlight the current limitations and potential of quantum computing.

This study aims to identify the problems faced by students in implementing learning. This study used a quantitative approach with a survey method, involving 30 students from two high schools in Yogyakarta. Data were collected through questionnaires about students' learning difficulties, interests, and needs for learning media. The results showed that 96% of the students considered chemistry as a difficult subject to understand because of the abstract nature of the material. As many as 64% of the students felt bored due to the uninteresting presentation of the material, while 72% of the students indicated the need for varied learning methods and interactive learning media to facilitate understanding. The results of the study showed that an innovation was needed to support chemistry learning activities to make learning more active and enjoyable so that it does not lead to student boredom. The developed virtual laboratory media provides flexible, safe and economical simulation of chemical experiments. This application is designed to be accessible without an internet connection using an Android device, allowing students to learn anytime and anywhere. The use of this virtual lab is expected to increase students' motivation, understanding of concepts, and learning experience.

The spread of infectious diseases has become a critical issue in public health, requiring effective mathematical models to understand and control their dynamics. This study aims to develop a mathematical model based on differential equations to analyze the transmission patterns of infectious diseases. By dividing the population into distinct compartments—susceptible, infected, and recovered—this model provides a framework to study disease progression. The methodology involves formulating a system of ordinary differential equations to represent interactions among these compartments, followed by numerical simulations to explore key parameters influencing disease spread. The findings reveal significant insights into the role of infection rate, recovery rate, and basic reproduction number in determining the outbreak's intensity and duration. These results highlight potential strategies for intervention, including vaccination and quarantine measures, to mitigate the impact of infectious diseases. The proposed model serves as a valuable tool for researchers and policymakers to predict and manage disease outbreaks, offering practical implications for public health planning.

In order to achieve production targets for fuel and petrochemical products to support national energy security, reliable equipment is needed to support the operation of petroleum processing refineries. Main equipment such as injection pumps must be able to adapt to the expected operational conditions. Check valve is one of the supporting components of injection pump reliability. Research was conducted to determine the velocity characteristics of two ball type check valve designs using Computational Fluid Dynamics (CFD) numerical simulations. In this research, three variations of pump stroke length were simulated, namely 25%, 50% and 100% with three variations of solid particle size, namely 200, 250 and 300 microns. The fluid that passes through the check valve is a solid-liquid mixture of catalyst and particles. The analysis carried out is by comparing the velocity values as well as the flow patterns produced for each variations used. The simulation results show that of all the variations tested, the model with a stroke length of 100% produces the maximum velocity. In addition, the size of solid particles is inversely proportional to fluid velocity and flow. From the results of this research, it was also found that model 2 has more potential for backflow towards suction, and also model 2 has more potential for clogging because particles that should flow stop inside the check valve.

Battery storage systems are essential for stabilizing renewable energy grids, especially for sources like solar and wind power that are inherently variable. This study evaluates various battery technologies and their effectiveness in storing and redistributing energy within renewable energy grids. Through simulations and analysis of performance metrics, the study offers insights into optimal operating conditions for different battery types, highlighting their role in enabling sustainable and stable energy distribution.

Data transmission efficiency is crucial in wireless sensor networks (WSNs), where limited battery life and signal reliability are significant concerns. This research explores various machine learning algorithms aimed at optimizing data transmission in WSNs, focusing on reducing energy consumption and enhancing network stability. Simulation results indicate marked improvements in efficiency, making WSNs more viable for long-term deployment across diverse environments.

Dasawisma groups have strategic potential in supporting family independence, but have not been optimally empowered. This Community Service activity aims to strengthen Dasawisma's capacity as agents of social change in enhancing family independence through the internalization of independence spirit values. The method used was a participatory and educational community organizing approach, implemented at Dasawisma Asoka RT.007, Bukit Timah Sub-district, Dumai City, on August 10, 2024. Activities included interactive material delivery, group discussions, work program preparation simulations, and reflective evaluations. The results showed increased understanding among Dasawisma members regarding their strategic roles, emergence of initiative and self-confidence, ability to formulate solutions based on local potential, and formation of more structured cooperation patterns and emergence of local mobilizer figures. The participatory approach based on independence values proved effective in driving Dasawisma's transformation from administrative implementers to subjects of independent and sustainable family and community development.

This article describes the complex implementation of Community Service (PKM) carried out in Kelambir Lima Kebun Village, where PKM activities are carried out to overcome the problems experienced by housewives in managing their finances. This PKM presents a solution to the problem by providing accounting training. The training was conducted using two methods, namely lectures and simulations. This is done to maintain the effectiveness of PKM so that the objectives can be achieved. The results of this community service are considered quite effective in overcoming the problems experienced by housewives, although there are still some PKM participants who do not apply the knowledge gained during PKM so that they do not experience significant changes in managing their finances. It is suggested that the next PKM should not only focus on the quality of increasing the knowledge or skills of the participants but also be able to instill motivation to realise the knowledge or skills in daily life.

The development of food commodities in Banten province, with geographical conditions where the area is mostly agricultural and with a fairly large population, has an important role, one of which is as a food buffer on the island of Java. Many harvests are distributed directly outside the region, after which they enter the market through distributors and agents, so this is a point of weakness and deficiency for policy makers in regulating and distributing rice commodities. This research was conducted with the aim of knowing the rice distribution model using the Powersim application. The method used to create a food policy model/design for Banten province is the Dynamic System. The results of this research are that the output obtained from the rice food distribution model simulation is that each rice stock in the Gapoktan warehouse sends according to the amount requested in each district/city, with a total capacity that can be obtained at the food distribution center of 109,682 tonnes/yr, or 2,742 tons/harvest. Then, after carrying out a simulation model using Powersim software, it can be concluded that the rice food commodity in Banten Province can still meet demand. With the Banten Province Food Distribution Center, it can control the availability of rice.

Predicting sales is an important aspect in sales development. Sales prediction simulation is an estimated calculation of the level of product sales in a certain period. Sales of pempers tend to fluctuate due to the choice of many brands available, resulting in sales having a little difficulty in estimating sales of MAKUKU diaper products at Greens Mart stores. This research aims to predict sales Pempers products. This research uses several stages of identifying problems, determining research objectives, collecting data, data collected or obtained from interviews with salespeople, managing data using Monte Carlo stages, implementing/testing data and testing results to see the accuracy of the method used. The analysis results show that Comfit M and Comfit L have almost the same level of accuracy, namely Comfit M is around 90.63% and sales of Comfit L are 90.48%. These values ​​provide an indication of the level of accuracy of the sales predictions made.      

Community Health Centers (Puskesmas) are the main place for the public to get basic health services. In certain conditions, the Health Center will receive visits from patients who arrive with the same number of origins at the same time. This has an impact on health services experiencing a decline and not maximizing the health of health workers in checking patients' health. So, comprehensive services are not obtained, and there are even patients who queue for too long. In order to minimize this occurrence, simulations are carried out to predict the number of possible visits that will occur in the future. The method used in this study is Monte Carlo. This research is intended so that the information provided by the Health Center related to the prediction of the number of patient visits that are likely to occur in the next year or in the future can be done validly and accurately. The data used is data on the number of patient visits in 2021, 2022, and 2023. As a result of this study, a prediction of the number of patient visits was obtained so that the Health Center could implement the next action that was useful for improving the quality of services needed    

West Nusa Tenggara (NTB) Province is a leading tourism destination in Indonesia, which requires predictions of the number of hotel guests for effective planning and resource management. This research aims to predict the number of hotel guests in NTB in 2025 using the Monte Carlo method, which is able to handle data variability and uncertainty. The data used is the number of guests from 1 to 5 star hotels during 2022. The simulation results show fluctuations in the number of guests throughout 2025 with the highest peak in December, especially in 3 star and 4 star hotels. The Monte Carlo method has proven to be effective in providing accurate predictions. accurate and reliable. The implication of this research is that stakeholders in the NTB hotel and tourism sector can use the results of these predictions for better strategic planning and decision making. This research is limited to data for 2022, so it is recommended that further research use data with a longer time span and consider external factors that influence the number of hotel guests. Combinations of other prediction methods can also be explored to improve the accuracy and reliability of predictions.    

Nara Kitchen is a daily catering service provider with a varied menu every day. Since the Covid-19 pandemic, catering demand has increased to 130 portions per delivery. This surge in demand necessitates improvements to the layout of production facilities, as higher production volume results in increased activity between workstations. Consequently, Nara Kitchen aims to enhance the layout of its facilities to optimize production efficiency. Facility layout improvements are implemented using the Blocplan method and are simulated through a discrete systems approach. The Blocplan method designs the layout based on the proximity between departments, aiming to minimize overall travel distance. The results of the layout improvements are then simulated using Flexsim software before being implemented. The simulation outcomes demonstrate reduced weekly travel distances. The movement distance for workers traveling from the kitchen workstation to the compounding workstation has decreased by 5.33m, while workers moving from the kitchen workstation to the packing workstation experience a reduction in movement distance of 142.38m

The operation of electromedical equipment in health care centers is very dependent on the quality of electrical power. Disturbances such as voltage sags, also known as dip voltage, can disrupt the performance of sensitive electronic devices and potentially threaten the stability of a power distribution system. This study suggests the use of a Dynamic Voltage Restorer (DVR) equipped with feedforward control to reduce voltage sags. With long flashes and significant voltage drops, simulations using MATLAB/Simulink show that the feedforward control on the DVR is able to compensate for voltage sags correctly and on time while still maintaining a stable load voltage.

The use of computers in the development of Electronic Chart Display and Information System (ECDIS) teaching materials can be used to assist lecturers in learning activities on vocational campuses as well as other materials in the Computer Base Training (CBT) laboratory at the Indonesian Maritime Polytechnic. The CBT laboratory provides learning materials on ship machinery systems and multiple choice questions for learning evaluation. The purpose of this study was to determine the level of effectiveness of the use of ECDIS material learning media software when used computer-based. The method used in this study is a qualitative method by looking at the final grades of students. This software consists of 42 slides of ECDIS material theory, 1 slide of ECDIS material video tutorial, 1 slide of ECDIS material practice, 20 slides of multiple choice evaluation questions, and 1 slide of final grades made using Visual Basic software. The results of the test showed that all cadets who attended the lecture were successful in using the software until the final grade was obtained.

The definition of Social Sciences (IPS) in Indonesia refers to the integrative study of human life in various dimensions of space and time and its activities. In the education sector, social studies refers to knowledge about the relationship between humans and their social environment. Character education, on the other hand, refers to a system of instilling character values ​​that includes the components of knowledge, awareness, and action to apply these values ​​in various contexts. The importance of character education in developing responsible, caring and empathetic individuals is emphasized in the culture and social environment concerned. The importance of integrated social studies includes several in-depth aspects, including a holistic understanding of the relationship between social science disciplines, development of critical and analytical thinking skills, development of social and emotional skills, and a broader understanding of human values, justice and democracy. Through various learning methods such as introduction to material, project-based learning, group discussions, case studies, simulations, and field visits, students can get to know integrated social studies well. After studying integrated social studies, students can show improvements in characteristics such as courtesy and responsibility. Through integrated social studies learning, students learn to respect cultural differences and be tolerant towards other people.

Computational thinking is the ability to solve problems and design systems using concepts and techniques generally associated with computers and computer programming. The aim of this research is to conduct a literature review, namely to determine the application of computational thinking in mathematics learning. The technique used is the Systematic Literature Review (SLR) strategy. SLR is a research method that aims to identify, study and interpret data in journals systematically with specified stages. The conclusion obtained from the research results is that the application of computational thinking in mathematics learning can be done using four foundations of computational thinking, namely: (1) Decomposition, namely the problem is divided into small parts, (2) Pattern recognition, namely the process of identifying patterns or sequences of problems, (3) Abstraction, namely consideration of the important parts of a problem, and (4) Algorithm, namely a series of instructions for solving the problem. Examples of its application include the use of interactive mathematics software, mathematical simulations, problem-based learning with technology, adaptive learning and the use of educational games.