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This study aims to estimate the population in Minahasa Regency at t=7 or t=8 in 2026-2027 using a logistic population model. Based on data obtained from the Minahasa Regency Central Statistics Agency (BPS) from 2019 to 2022, it can be assumed that the capacity limit (K) = 400,000. The results of this research show that the accurate model to use in determining the estimated population of Minahasa Regency is the model with k = 0.0588644467, and the relative growth rate is 5.88% per year. Then, using the logistic method, the general form of the solution is obtained, namely P(t )=400,000/(e^(-0.0588644467t) (0.16921458)+1). Furthermore, the results obtained show that the predicted population of Minahasa Regency in 2026-2027 is 359,690 and 361,774 people.

This research aims to: (1) Describe the development of independence for foster children at the Chairun Nissa Orphanage. This research was conducted at the Chairun Nissa Orphanage on JL. Pisangan Baru Timur, No.12, Jatinegara, RT.6/RW.15, Pisangan Baru, Kec.Matraman, East Jakarta City, Special Capital Region of Jakarta 13110. The research method used was descriptive with a qualitative approach. Data collection techniques through observation, interviews, documentation and literature study. The subjects in this research were 8 respondents. The results of this research show that: (1) The process of fostering caregivers in forming the independence of foster children at the Chairun Nissa Orphanage in the coaching that is carried out includes several steps such as modeling, providing attention and love, providing good lessons (advice), and providing rewards and punishments. Coaching consists of several forms such as physical coaching, cultural coaching, religious coaching, and intellectual coaching. Chairun Nissa Orphanage Caretakers have a role in forming the independence of foster children in 3 aspects, namely emotional independence (emotional autonomy), independence in behavior (behavioral autonomy), and independence in values ​​(value autonomy).    

Universities' development hinges significantly on student admissions, necessitating accurate predictions for effective planning. This study applies the Monte Carlo simulation method to forecast new student arrivals at the Faculty of Mathematics and Natural Sciences (FMIPA) at Universitas Negeri Medan (UNIMED). Utilizing data from 2021 to 2023 sourced from the PDDikti website, the research employs PHP programming for implementation. The Monte Carlo algorithm's numerical prowess ensures precise statistical data simulation, comprising data collection, probabilistic distribution computations, cumulative distribution determinations, random number generation, and simulation analyses. Simulation results for 2022, 2023, and 2024 exhibit consistent trends, projecting an average of 860 to 930 new students per program. This methodology surpasses manual estimations, offering robust insights for university resource allocation and strategic management. Despite its effectiveness, study limitations, such as model assumptions, warrant continuous validation with actual data. This research advances predictive modeling in higher education, providing a foundation for future enhancements and comprehensive prediction integrations.

This study aims to reveal, describe, and analyze the development of Sumbun Dance in East Tanjung Jabung Regency, Jambi Province. This type of research is qualitative research using a descriptive method. The research instrument is the researcher himself assisted by supporting instruments in the form of stationery and cameras. Data were collected through literature studies, observations, interviews and documentation. The steps of analyzing data are data collection, data reduction, data modeling, and drawing conclusions. The results of this study show that the development of Sumbun Dance can be seen in terms of quality and quantity. In terms of the quality of the development of Sumbun dance, it is seen from the movement, floor patterns, dancers, music, makeup and clothing, time and place of performance. Meanwhile, in terms of quantity, it can be seen from the addition of actors, increasing performances, expanding the performance area. The development in terms of movement of the Sumbun dance which before it was developed there were 8 types of movements and in the creation of Sumbun dance there were 11 types of movements. The musical instruments used in the Sumbun dance that were previously developed were kulintang, gong, drum, and accordion and in the Sumbun dance that had been developed kulintang, gong, drum, accordion, violin, gambus, drums, keyboard, bass, and guitar. The floor pattern is carried out by variating what was initially 8 types of floor patterns now to 10 types of floor patterns and in the form of variations.  The costumes that used to be danced using Malay traditional clothes from Tanjung Jabung Timur were equipped with batik-patterned cloth songkets as well as golden iron head accessories and necklaces and men's accessories only used headbands. Now the costumes used in the creation mung dance have been packaged and created in a new form like costumes for performance events. Meanwhile, in terms of quantity, the number of Sumbun dancers who have been dancing for a long time amounted to 6.

This research aims to describe and determine the influence of work ethic on employee performance with work discipline as a mediating variable at the Jambi Province Regional Civil Service Agency. The analytical method used is quantitative analysis. The research population and sample were all employees at the Jambi Province Regional Civil Service Agency, totaling 81 respondents. Data collection was carried out by distributing questionnaires using a Likert scale. The statistical analysis used is the Structural Equation Modeling (SEM) technique with Partial Least Square (PLS) as an analysis tool, using the SmartPLS 4 program. The results of the statistical analysis show that work ethic has a positive and significant effect on employee performance, work ethic has a positive and significant effect on work discipline, work discipline has a positive and significant effect on employee performance, and work discipline is able to mediate the influence between work ethic and employee performance. So it can be concluded that work discipline functions as a link between work ethic and employee performance. Employees who have a good work ethic will work with discipline following company regulations so that their performance will increase and have a positive impact. This helps the company achieve its targeted goals.

Background: The rapid advancement of Industry 4.0 has accelerated the integration of digital technologies such as the Industrial Internet of Things (IIoT), edge computing, and Digital Twin systems in smart manufacturing environments. However, many existing implementations remain fragmented and heavily dependent on centralized cloud infrastructures, resulting in latency constraints, limited scalability, and suboptimal real-time decision making. Objective: This study aims to develop and validate an integrated edge based Digital Twin optimization framework that combines IIoT sensing, hybrid edge cloud architecture, and reinforcement learning based adaptive control. Methods: The research adopts a multi phase design consisting of framework development, simulation based validation, and industrial pilot implementation. The proposed system integrates real time data acquisition, localized edge processing, Digital Twin synchronization, and intelligent optimization mechanisms to enhance operational efficiency. Results: The findings demonstrate significant performance improvements compared to conventional cloud based systems, including substantial latency reduction, increased production throughput, reduced downtime, and improved energy efficiency. Scalability and robustness testing further confirm that distributed edge intelligence enhances system resilience under increased workloads and network disruptions. These results indicate that integrating edge computing with Digital Twin modeling and reinforcement learning provides a scalable, responsive, and energy efficient solution for next-generation smart factories.

Lampung, a province located at the southern end of Sumatra Island, serves as a gateway for many migrants from different regions in Indonesia. However, some of the locals and tourists still face difficulties in finding the central location for souvenirs due to the  vast number of shops available. The purpose of this research is to assist tourists in finding the shortest distance to the nearest souvenir location using the Floyd Warshall algorithm. The software development method employed in this study is the Prototype, which consists of four stages, namely Communication, Quick Plan, Modeling Quick Design, Construction of Prototype, Deployment Delivery & Feedback. In the Rapid Modeling stage, the Floyd Warshall algorithm is used to determine the shortest distance for users to find the souvenir location. The result of this research is an android-based application that can provide the    nearest souvenir location with the shortest distance around the user.

The pursue of this research is to analyze correctional relationship between customer relationship management (CRM) as quality of service and marketing mix to customer loyalty of ADA Swalayan in Bogor. The primary data are collected through questionnaire of 52 respondents who have made transactions in ADA Swalayan and analyzed the data with Structural Equation Modeling (SEM) using software SPSS. The results of the research show that Customer Management Relationship has an influence on customer loyalty of the ADA Swalayan as well.

The overflow of the Citarum River is one of the main challenges in maintaining the stability of the Saguling Dam in Indonesia. This research aims to analyze the impact of the Citarum River overflow on the stability of the dam. The methods used include field surveys, hydrological data analysis, and numerical modeling. This research makes an important contribution to understanding the interaction between river overflows and dam stability, and provides a basis for developing disaster risk mitigation strategies in areas vulnerable to floods and river overflows.  

In everyday life, three-dimensional shapes are ubiquitous, manifesting in structures such as houses, bottles, and vehicles. These shapes, characterized by length, width, and height, represent the application of functions of two variables, particularly within spatial domains. This research employs Python programming to model functions of two variables, specifically focusing on spatial surfaces. Leveraging the Matplotlib module, graphical representations of these functions are generated, while the NumPy module facilitates mathematical analyses, including identifying extremal values, critical points, and tangent lines. Results demonstrate the efficacy of Python in efficiently modeling functions of two variables. Through this approach, readers gain insights into the inherent characteristics and behaviors of such functions within spatial contexts, thereby simplifying mathematical analyses and enhancing comprehension.

Poverty is a fundamental problem that is the center of attention of the government in any country. The aim of this research is to analyze the influence of education, unemployment, the Covid-19 pandemic and the human development index on poverty in North Sumatra. The data used in this research is secondary data based on time series available on the official website of the Central Statistics Agency in North Sumatra. This research data processing uses the help of SmartPLS 3 software. The research analysis used in this research is Structural Equation Modeling which shows that the variables education, unemployment, the Covid 19 pandemic and the human development index are exogenous variables and poverty is an endogenous variable. The research results obtained an R-Square value of 0.511 or 51.1%. The large value of the coefficient of determination shows that the independent variables consisting of education, unemployment, the Covid-19 pandemic and the human development index are able to explain the dependent variable, namely the poverty percentage of 51.1%. Meanwhile, the remaining 48.9% is explained by other variables not included in this research model. The human development index variable has a negative and significant effect on poverty of 0.678. For the Covid 19 Pandemic variable, it has a negative and significant effect on poverty of 0.267.

Sales of coffee drinks from opening stands at bazaars and through social media have fluctuated. In November the target was exceeded. However, from December to April the target was not met. Based on these obstacles, there is a need for sales innovation that will increase sales of Aroma Kahuripan coffee drinks. This research uses qualitative research. After processing the data using ISM Professional software, the results showed that the obstacles that occurred in Aroma Kahuripan sales were unfriendly customer service and unattractive marketing. Apart from that, there are main actors in the sales process, namely marketing staff and baristas.    

Coffee grounds waste, which is rich in carbon, can accelerate global warming if not managed properly, considering its contribution to the greenhouse effect (Hendra Arthaviana, 2019). Therefore, coffee grounds can have a negative impact on the environment if they are not processed or utilized. So, coffee grounds need to be processed into useful products so as not to pollute the environment. The method used in this research is interviews. Based on the results of the application of the ISM (Interpretative Structural Modeling) method which was carried out regarding the coffee grounds waste processing strategy, it was concluded that the application of the ISM method can be used to review the main constraint elements and objectives of processing coffee grounds waste at Aroma Kahuripan    

Penelitian ini bertujuan untuk mengeksplorasi sejauh mana citra merek dan kualitas produk dapat memengaruhi loyalitas konsumen generasi milenial terhadap Mie Instan Sedaap, dengan kepuasan konsumen sebagai variabel mediasi. Generasi milenial dipilih sebagai fokus karena mereka merupakan kelompok usia produktif yang memiliki karakteristik konsumsi yang unik, kritis terhadap merek, dan cenderung loyal terhadap produk yang sesuai dengan nilai dan preferensi mereka. Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei terhadap 100 responden yang dipilih melalui teknik purposive sampling. Data dianalisis menggunakan metode Partial Least Square-Structural Equation Modeling (PLS-SEM). Hasil penelitian menunjukkan bahwa citra merek memiliki pengaruh signifikan terhadap kepuasan konsumen, sedangkan kualitas produk tidak menunjukkan pengaruh yang signifikan terhadap kepuasan. Namun, secara langsung, baik citra merek maupun kualitas produk terbukti berpengaruh terhadap loyalitas konsumen. Sementara itu, kepuasan konsumen tidak memiliki pengaruh langsung terhadap loyalitas, dan tidak berperan sebagai mediator antara citra merek maupun kualitas produk terhadap loyalitas. Temuan ini memberikan wawasan bagi produsen Mie Sedaap dalam merancang strategi merek yang lebih relevan dengan nilai-nilai generasi milenial untuk meningkatkan loyalitas mereka.

This research examines the influence of sharia financial literacy on investment decisions in sharia financial products, by considering two moderating variables: perceived quality and religiosity. Quantitative methods were used by collecting data through bold questionnaires via Google Form to 190 respondents who understand sharia financial products. Data analysis was conducted using Structural Equation Modeling based on behavioral finance theory. The research results show that there is a positive influence of sharia financial literacy on investment decisions in sharia financial products. Perceived quality and religiosity do not moderate the influence of financial literacy on investment decisions, but have a direct effect. The implication is that sharia financial literacy influences positive investment decisions. Perceived quality and level of religiosity also influence investment decisions in sharia financial products. These findings are important for the Islamic finance industry in developing effective marketing and service strategies, as well as for educational institutions to increase sharia financial literacy.

Currently, the government is increasingly building PLTMG to fulfill the electricity needs of the society. Beside for fulfill the electricity needs of the Indonesian people, PLTMG also has a negative impact on the society, especially for the community around the PLTMG in the city of Batam. So companies need to conduct studies on environmental impacts, one of which is the impact of the air produced on the surrounding area. The PLTMG industry does not use air pollution control devices, but uses a leanox combustion control system on each gas engine with a chimney outlet that emits SO2 and particulate emissions. The model simulation was carried out using Aermod view software with meteorological data from the affected locations. The results of AERMOD modeling show that the PLTMG industry will have an impact on particulate emissions in the ambient air around the activity location which will spread to the northwest, north, south and east of the activity location. The Aermod Model also shows that current conditions have resulted in dispersion with concentrations below the maximum limit stated in the 2021 Government Regulation. The addition of an emission monitoring system such as CEMS can be used to help monitor the concentration of dispersed emissions. Apart from that, emission control devices such as incinerators or combustion can also be used to reduce the concentration of the emissions used.

The objective of this research is to devise a personalized recommendation system for a freelancing platform to optimize the freelancer project matching process. This enhancement is intended to improve user experience and increase the success rate of projects. The system will recommend projects to freelancers based on their skills and preferences by employing data analysis and machine learning methodologies. The research methodology adheres to the Cross Industry Standard Process for Data Mining (CRISP-DM), incorporating six stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The proposed project employs a hybrid recommendation strategy, integrating Content-Based Filtering through KNearest Neighbors (K-NN) and Cosine Similarity, Collaborative Filtering via Singular Value Decomposition (SVD), and recommendations derived from Word2vec. Evaluation metrics such as precision, recall, F1 score, MAP, and MRR are utilized to assess model performance. The results, including precision scores of 0.80 for KNN and 0.728 for SVD, recall scores of 0.60 for KNN and 0.623 for SVD, and F1 scores of 0.69 for KNN and 0.671 for SVD, as well as a MAP of 0.75 and MRR of 0.80 for Word2vec, demonstrate the efficacy of the hybrid recommendation system in delivering accurate and varied project suggestions to freelancers, with a weighted average ensemble learning model emerging as the most effective solution.

This study aims to identify the influence of organizational culture, transformational leadership, and work motivation on the performance improvement of civil servants at the Main Secretariat of the National Civil Service Agency. Data analysis was conducted using Linear Structural Relationship (Lisrel) version 8.80 with Structural Equation Modeling (SEM) method. The choice of using SEM in this research lies in its ability to analyze the pattern of relationships between latent constructs and their indicators, latent constructs with each other, and measurement errors directly. The results of the analysis indicate that organizational culture, transformational leadership, and work motivation significantly contribute to the improvement of civil servants' performance. Managerial implications and recommendations for further research are also discussed.                                                                                                                                                      

Applying ergonomic principles in work tool design for manufacturing industries is a crucial factor in improving productivity while maintaining worker health. This research aims to analyze the effectiveness of adaptive work tool design models based on cognitive and physiological ergonomic principles, identify interaction patterns between workstation design and operational performance, and develop a conceptual framework for integrating ergonomic principles into production cycles. The research method adopts a cognitive-physiological approach with qualitative analysis of human-machine interactions, biomechanical simulations using digital human modeling, and muscle load measurements through electromyography. Implementation was conducted using a participatory ergonomics approach and IMU sensor-based real-time monitoring systems. Results show that using materials with controlled deformation capabilities (15-20%) in work tools reduces muscle work by up to 27%, while adaptive automation system integration improves assembly accuracy by 18%. Workstations with ergonomic adjustments increase assembly speed by an average of 12%, and low-cost ergonomic interventions effectively improve productivity by 11-15% in resource-limited environments. Longitudinal analysis reveals that evidence-based ergonomic investments yield a 230% ROI through increased productivity, reduced injury compensation costs, and decreased employee turnover. IMU-based posture monitoring systems integrated with adaptive feedback loops reduced musculoskeletal disorder incidents by up to 41%. In conclusion, ergonomic optimization based on cognitive-physiological principles creates synergy between production efficiency and worker well-being, making it an essential component in achieving sustainable productivity.

Healthcare waste (HCW) is a significant environmental and public health concern due to its hazardous nature, particularly the presence of emerging pollutants such as pharmaceuticals, heavy metals, and pathogens. The improper disposal and management of healthcare waste contribute to pollution and pose long-term risks to both human health and ecosystems. This study examines the toxicity risks associated with HCW in areas near healthcare facilities with inadequate waste management practices, showing an increase in toxicity risks by 22% to 30%. The research develops a cumulative risk assessment model that integrates human exposure with ecological risks, considering both direct and synergistic effects of pollutants. The model incorporates various components, including pollutant analysis, bioaccumulation mapping, and long-term exposure modeling, to assess the environmental and health risks of HCW. The findings highlight that inadequate waste management leads to significant pollutant accumulation in local ecosystems, with direct implications for biodiversity and human health. Additionally, the study emphasizes the benefits of applying the One-Health approach, which considers the interconnectedness of human, animal, and environmental health, offering a more integrated understanding of the risks posed by HCW pollutants. The research advocates for the incorporation of the One-Health model in healthcare waste management policies to mitigate risks and improve sustainability. Future studies should refine the cumulative risk assessment model and expand it to encompass other environmental waste sources, providing a more comprehensive understanding of pollutant impacts and advancing mitigation strategies.