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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 Student Evaluation of Lecturers (EDOM) at the Faculty of Engineering, Universitas Dr. Soetomo has historically been conducted via Google Forms and processed manually, resulting in slow response times, repetitive recap procedures, and insufficiently documented reporting validity. This study aims to design, build, and evaluate a web-based EDOM system using the Prototype Model (MODEL PROTOTYPE) to improve data collection efficiency, recap accuracy, and the effectiveness of feedback for teaching quality assurance. The development method comprises requirements elicitation with the Quality Assurance Unit through a review of SPMI documents and brief interviews, architectural and interface design (Laravel, MVC pattern, and MySQL), staged prototyping, and rapid iterations based on stakeholder feedback until functional conformity is achieved. The resulting system provides authentication and role-based authorization (Admin, GPM, Lecturer, Student), odd/even period management, a question bank employing a Likert scale, anonymous questionnaire submission, score recap per lecturer and per category (pedagogical, professional, personal, social), dashboard visualizations, and report export to support governance needs. Functional evaluation was conducted through black-box testing on core scenarios (login, period scheduling, submission, recap, and export) and indicated conformance to specifications. User acceptance evaluation employed the Technology Acceptance Model (TAM) to examine perceived usefulness, perceived ease of use, attitude toward use, and behavioral intention; the results indicate positive acceptance and potential for operational adoption. Practically, the prototype approach accelerates requirement alignment, reduces the risk of mis-specification, and facilitates change control, while the Laravel-based implementation supports maintainability, role-based access security, and further feature development. The study is limited to a single faculty; future work may include SSO integration, audit trails, and longitudinal, cross-semester analytics for more comprehensive monitoring of lecturer performance.

Shadow puppet craft training is a strategic intervention in preserving cultural heritage and strengthening the creative economy sector in Indonesia. To ensure the effectiveness and efficiency of training, a planning approach is needed that is not only conventional, but also based on quantitative analysis and intelligent systems. This community service proposes a training planning strategy using an interdisciplinary approach involving Operation Research, Design of Experiment (DoE), Simulation, Metaheuristic Algorithms, and Data Mining. This study begins with the identification of key training variables, such as duration, number of participants, initial competency level, teaching materials, and instructor resources. Through the DoE approach, various combinations of variables are systematically tested to identify the optimal training design. Next, Simulation is used to model the dynamics of training implementation and evaluate implementation scenarios. To predict training needs and participant behavior, Data Mining techniques are applied to historical data of arts community training. In the final stage, Metaheuristic algorithms such as Genetic Algorithm and Simulated Annealing are used to solve complex and large-scale scheduling and resource allocation problems. The results of the integration of these approaches show an increase in training efficiency of up to 27% as well as increased participant satisfaction and the quality of work results. This activity demonstrates that applying a quantitative, data-driven approach to traditional crafts training planning can provide significant added value. This model can be replicated in other training programs based on local wisdom and other creative industry sectors.

Background: The scheduling of work of health workers, especially radiographers in type B hospitals, is a complex challenge due to the variety of radiology modalities, variations in the number of human resources, and the provisions of working hours regulations from the Ministry of Health of the Republic of Indonesia. Manual scheduling that is still in use tends to cause workload inequality, conflicts between employees, and operational inefficiencies. Objective: This study aims to design and develop an Artificial Intelligence (AI)-based radiographer shift scheduling system that is able to prepare work schedules automatically, fairly, flexibly, and integratedly, in accordance with hospital service regulations and needs. Research Method: This type of research is Research and Development (R&D). The development process is carried out through the stages of needs analysis, designing Python and Flask-based systems, simulating tests on data, and expert validation then the data collected and described from the initial mapping and also mapping potential problem-solving. Results: The system successfully manages morning, noon, night, and holiday shift schedules based on competence, fair rotation, and maximum working hours provisions. By showing a significant difference between user perceptions before and after using the system, which reflects improved efficiency, fairness, and ease of access to schedules. Respondents expressed satisfaction with the override feature and integrated notifications. Conclusion: The development of an AI-based radiographer shift scheduling system has proven to be feasible and effective in overcoming managerial problems of work scheduling in hospitals. This system is able to increase efficiency, transparency, and user satisfaction, and has the potential to be widely applied to various types of hospitals in Indonesia.

The maintenance of non-aviation defense equipment (main weapon system) is a critical aspect in maintaining operational readiness. However, the Maintenance, Repair, and Overhaul (MRO) system in Indonesia still faces limitations due to manual reporting, inefficiency in spare parts management, and the lack of integration of the Life Cycle Cost (LCC) approach. This study aims to design and develop the Integrated Cavalry Monitoring and Maintenance System (ICMMS) based on a web application that integrates sensors, real-time data analytics, and LCC calculation. The prototyping method was used, involving design, development, integration, and testing phases on the Maung Tactical Vehicle and Anoa Armoured Personnel Carrier at PT Pindad. The results of the prototype implementation showed a significant increase in maintenance efficiency: damage reporting time decreased from ±3 hours to ±1 minute, critical component identification became 95% faster, and maintenance scheduling shifted from reactive to predictive. Additionally, the integration of the LCC algorithm allows for more accurate maintenance cost estimation, supporting technical and strategic decision-making. This study demonstrates that ICMMS based on LCC can be an innovative digital solution to enhance MRO effectiveness and operational readiness of non-aviation defense vehicles in Indonesia. It is expected that this system will improve the resilience and cost-effectiveness of managing Indonesia’s military vehicle fleet.

This research was conducted with the aim of optimizing the assignment of working hours in the Procurement Division of PT. Pelindo Multi Terminal through the application of the Hungarian method. The fundamental problem faced is the imbalance between the number of permanent workers and the high workload that must be completed, thus creating a risk of inefficiency in the operational process. To address this problem, a quantitative approach was used with linear programming modeling techniques designed to produce a more systematic and measurable assignment allocation. Through the analysis conducted, an optimal solution was obtained regarding the distribution of working hours, where the total working time can be reduced to 10,120 minutes per month, lower than the previously set maximum limit of 10,560 minutes per month. These results indicate that the application of the Hungarian method is not only able to reduce excessive workloads on some employees, but also ensures a more proportional distribution of assignments among all available workers. In addition, this method can increase operational effectiveness because each worker receives a load according to their capacity, so that the risk of fatigue or decreased performance can be minimized. The findings of this study confirm that the Hungarian method is an alternative work scheduling strategy that is efficient to be applied in industrial environments with high task complexity. Proper implementation can also support the achievement of overall company productivity, improve the quality of human resource management, and strengthen the company's competitiveness in facing future operational challenges.

This study examines the effectiveness of education and training programs in improving employee performance and identifies the factors influencing training outcomes at the Personnel and Human Resources Development Agency (BKPSDM) of Southwest Papua Province. A qualitative descriptive approach was employed, utilizing interviews, observations, and documentation, with key informants including the Head of BKPSDM. Data were analyzed using the interactive model of Miles et al. (2014), encompassing data condensation, data display, and conclusion drawing. Findings reveal that education and training programs at BKPSDM significantly enhanced employee performance, as evidenced by improved timeliness in task completion, increased knowledge, skills, and expertise, and notable positive changes in employee behavior and attitudes. Training outcomes were also reflected in improved workplace discipline and greater responsibility among civil servants. Evaluation of program effectiveness employed five levels: participant reaction, learning achievement, behavioral change, organizational impact, and cost-effectiveness, all of which indicated favorable results. Factors influencing training effectiveness included the relevance of training materials to employee roles, appropriate scheduling that minimized work disruption, the use of clear and supportive training methods, and the competence of instructors in delivering material effectively. These findings demonstrate that well-planned and well-delivered training programs can strengthen the capacity and professionalism of civil servants, enabling them to better fulfill governmental and developmental responsibilities while supporting overall organizational performance improvement. In addition, the study highlights the importance of continuous monitoring and feedback throughout the training process to ensure sustained improvements in employee performance. It suggests that the involvement of employees in the design and planning stages of training programs can enhance the relevance and applicability of the content, fostering greater engagement and retention of knowledge.

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.

This study examines a comprehensive approach to addressing common issues in laundry services, such as ineffective scheduling, skills gaps, and operational inefficiencies. The research focuses on RPK Omah Laundry Prapen, aiming to improve work processes and optimize human resources in this laundry business. The proposed solutions include the implementation of an attendance system, financial application training, laundry and ironing skills training, and a single-shift work system. The attendance system is designed to improve workforce punctuality, while the financial application training aims to enhance employees' understanding of financial management. Additionally, providing specific training on laundry and ironing techniques helps to bridge the skills gap and ensure high-quality service. The introduction of a single-shift work system aims to increase efficiency by streamlining operations and reducing staff fatigue. The results of the study indicate that these proposed solutions lead to several positive outcomes. The attendance system contributes to better time management, fostering a sense of responsibility among employees. Financial application training helps staff manage the business's finances more effectively, leading to more informed decision-making. Furthermore, the skills training program has shown improvements in the quality of laundry and ironing services, which directly impacts customer satisfaction and retention. The adoption of a single-shift work system reduces operational costs and increases the overall efficiency of the laundry services. Ultimately, this approach enhances fairness, operational efficiency, and productivity, creating a more conducive work environment. Implementing these integrated solutions can help laundries, such as RPK Omah Laundry Prapen, achieve better, sustainable performance by addressing key operational challenges and maximizing their workforce's potential. This study provides valuable insights for other laundries looking to optimize their operations and improve long-term business success.

This study aims to analyze the effectiveness of preventive maintenance on the Simplex machine at PT. XYZ by applying the Overall Equipment Effectiveness (OEE) method and identifying the primary causes of production losses through the Six Big Losses framework. Preventive maintenance is an important strategy to ensure machine reliability, reduce downtime, and improve production efficiency. OEE is a widely recognized performance measurement tool consisting of three key indicators: Availability, Performance, and Quality. These indicators collectively reflect the overall effectiveness of equipment in supporting the production process. The results of this study indicate that the OEE value of the Simplex machine is 79%, which remains below the world-class benchmark of 85% as recommended by the Japan Institute of Plant Maintenance (JIPM). This finding suggests that the machine’s performance has not yet reached the optimal standard and requires improvement efforts. Further analysis using the Six Big Losses approach reveals that the most significant contributors to reduced machine effectiveness are equipment failure and idling or minor stoppages. These two categories account for the majority of productivity losses, thereby affecting both machine utilization and production output. To further explore the underlying issues, a root cause analysis was conducted using a fishbone diagram, which enabled the identification of several critical factors related to human resources, methods, machines, materials, environment, and measurement systems. Based on this analysis, improvement proposals were developed through the 5W+1H method, providing a systematic strategy to enhance preventive maintenance practices. The recommended actions include scheduling more frequent inspections, improving operator training, upgrading spare parts management, and implementing stricter monitoring of machine performance. In conclusion, this study highlights the importance of continuous preventive maintenance to optimize machine productivity and reduce unplanned downtime. By adopting the proposed improvement strategies, PT. XYZ can increase the effectiveness of its Simplex machine, moving

This study examines how project-based learning is used in Makassar State University's Educational Exhibition course for the Educational Technology Study Program. The purpose of this study is to outline the phases of project-based learning in the Educational Exhibition course, along with its benefits and drawbacks. The research method used a descriptive qualitative approach with a single case study type on the educational exhibition course. The findings demonstrated that there are multiple steps involved in implementing project-based learning in educational exhibition courses: determining the fundamental questions, project planning, scheduling, monitoring project progress, assessing results or project presentations, and the final stage of experience evaluation. Other research findings indicate that project-based learning in this course provides several benefits for students, such as active participation in the learning process, the ability to integrate theory and practice, team learning and collaboration, as well as the development and enhancement of students' skills.   However, a number of issues that need to be addressed, such as uneven student contributions, lack of open communication, and time management problems, can make the educational exhibition project less successful. The findings support designing effective project-based learning programs that meet workforce demands and enhance student's interpersonal skills through authentic experiences.

Employee shift scheduling in the hospitality industry remains a critical yet complex task due to fluctuating operational demands, fairness requirements, and labour regulations. Many hotels still rely on manual scheduling methods, which are time-consuming and prone to biases, particularly in ensuring fair workload distribution across employees. Despite numerous studies on workforce scheduling, limited attention has been given to integer linear programming (ILP) models that address gender-based restrictions and operational fairness simultaneously in real-world hotel contexts, especially in developing regions such as Central Java. This study proposes an Integer Linear Programming (ILP) model to generate optimal shift schedules for hotel staff over a 31-day planning horizon. The model incorporates operational constraints, including one shift per day, gender-based restrictions (which prevent female staff from working night shifts), availability, minimum staffing levels, and fairness in workload distribution. Key parameters and binary decision variables were defined to ensure compliance with the hotel's specific requirements. Empirical data were collected from a hotel in Central Java involving 20 employees, and the model was implemented using Python with a Gurobi solver. The ILP model successfully generated optimal schedules in under 10 seconds, significantly outperforming the manual method, which required over 4 hours. While the manual schedule resulted in an imbalance where some employees worked over 27 days and others only 22, the ILP approach enforced a strict maximum of 26 working days for all staff. Furthermore, the fairness index (FI) improved from 19.2% in the manual method to 0% in the ILP-generated schedule, indicating complete equity in workload allocation. The proposed ILP model demonstrates its effectiveness in improving scheduling fairness, operational efficiency, and compliance with labour policies. This work not only addresses a critical research gap in hospitality scheduling practices in Indonesia but also offers a replicable framework for other labour-intensive service sectors. Future research may explore multi-objective extensions incorporating employee preferences, satisfaction, and dynamic demand fluctuations.

In addition to improving interpersonal communication skills, this training also emphasized the importance of strategic communication in the context of advocacy and social mobilization. NGO administrators were trained to design campaign messages tailored to audience segments, including potential donors, corporate partners, and government stakeholders. An understanding of the importance of framing and emotional appeal was also emphasized, so that the messages delivered were not only informative but also able to inspire empathy and concrete action from the audience. During the training process, participants were also equipped with a basic understanding of digital communication, particularly in utilizing social media platforms as a tool to expand the reach of messages. Creative content strategies, effective posting scheduling, and the use of visual storytelling were introduced so that NGO administrators could build a positive image of their institutions in the digital space. These skills are crucial considering that the dynamics of public communication today are influenced by the speed and reach of social media.The positive impact of this activity was felt not only individually, but also institutionally.The NGO "Kakak Asuh" began to show an increase in public engagement through social media, an increase in the number of new volunteers, and the opening of opportunities for partnerships with external parties. This demonstrates that persuasive communication is not merely a means of conveying a message, but also a strategy for building strong, credible, and sustainable relationships with the wider community. Going forward, the sustainability of this training program is designed through a system of ongoing mentoring and support. This approach is expected to strengthen the implementation of the communication strategies learned and enable a comprehensive transformation of organizational communication. Thus, this PKM activity will not only have a short-term impact but also build a solid communication foundation to support the NGO's social mission in the future.

In addition to improving interpersonal communication skills, this training also emphasized the importance of strategic communication in the context of advocacy and social mobilization. NGO administrators were trained to design campaign messages tailored to audience segments, including potential donors, corporate partners, and government stakeholders. An understanding of the importance of framing and emotional appeal was also emphasized, so that the messages delivered were not only informative but also able to inspire empathy and concrete action from the audience. During the training process, participants were also equipped with a basic understanding of digital communication, particularly in utilizing social media platforms as a tool to expand the reach of messages. Creative content strategies, effective posting scheduling, and the use of visual storytelling were introduced so that NGO administrators could build a positive image of their institutions in the digital space. These skills are crucial considering that the dynamics of public communication today are influenced by the speed and reach of social media.The positive impact of this activity was felt not only individually, but also institutionally.The NGO "Kakak Asuh" began to show an increase in public engagement through social media, an increase in the number of new volunteers, and the opening of opportunities for partnerships with external parties. This demonstrates that persuasive communication is not merely a means of conveying a message, but also a strategy for building strong, credible, and sustainable relationships with the wider community. Going forward, the sustainability of this training program is designed through a system of ongoing mentoring and support. This approach is expected to strengthen the implementation of the communication strategies learned and enable a comprehensive transformation of organizational communication. Thus, this PKM activity will not only have a short-term impact but also build a solid communication foundation to support the NGO's social mission in the future.

This study aims to describe and provide recommendations regarding the proper management of extracurricular sports activities in senior high schools in Tarakan City. Extracurricular activities play an important role in helping students develop their potential. This study used a qualitative descriptive method. Subjects included principals, physical education teachers or extracurricular sports coordinators, and sports coaches from 14 randomly selected religious, public, and private senior high schools in Tarakan City. Data collection techniques included observation, interviews, and documentation. Data validity was ensured through source triangulation and technique triangulation. The data analysis process included data collection, data reduction, data presentation, and drawing conclusions. The research findings indicate that: (1) Planning for extracurricular sports activities is generally carried out through coordination meetings among the parties involved to organize activities during one school year. Scheduling is the responsibility of the extracurricular coordinator and is arranged in consultation with the sports supervisor or coach to avoid conflicts with other school events. Coaches also prepare training programs as part of the planning process. (2) Extracurricular sports activities are held in the afternoon, outside of regular school hours, based on a schedule prepared by the coordinator and vice principal for student affairs. (3) Evaluations are conducted at least once every three months and involve various school stakeholders. Aspects evaluated include student attendance, participation in learning, and training outcomes. (4) Supporting factors include adequate facilities and infrastructure, funding, student competency, and teacher involvement. Conversely, inhibiting factors include low student attendance, limited funding, inadequate or inadequate facilities, and unfavorable weather conditions. These findings provide an overview of how extracurricular sports activities are managed in high schools in Tarakan City and highlight the importance of effective planning, implementation, and evaluation. This study also identifies key factors that support and hinder the success of these programs, offering insights for future improvements.

This study investigates the correlation between mental health and turnover intention among working students at STIE IBMI Medan who fulfill dual roles as both students and employees. These individuals are particularly vulnerable to psychological stress arising from academic responsibilities and workplace demands. The objective of this research is to examine the influence of mental health on their tendency to resign from their jobs. An associative quantitative research method was adopted, with data collected through structured interviews involving 71 respondents. The analysis was conducted using simple linear regression via the SPSS application. The findings reveal that mental health has a significant negative effect on turnover intention, with a significance value of 0.001. This suggests that students who experience better mental health are less likely to consider leaving their jobs. The coefficient of determination (R Square) is 14.6%, indicating that mental health explains 14.6% of the variation in turnover intention. The remaining 85.4% may be attributed to other contributing factors, such as high work pressure from supervisors, poor work-life balance, financial stress, inflexible schedules, and lack of organizational support. The implication of these results is that efforts to support and maintain the psychological well-being of working students are essential for reducing employee turnover. Educational institutions and employers should collaborate to create supportive environments through counseling services, flexible scheduling, mental health awareness programs, and policies that accommodate the dual responsibilities of student workers. By addressing these mental health concerns, institutions can improve student performance and job retention simultaneously. This study highlights the importance of integrating mental health strategies in workforce and academic management, especially for populations that manage competing academic and professional obligations.

Distribution is the process of moving, managing, and storing goods from suppliers to customers in the supply chain. This process includes not only the delivery of raw materials from suppliers to manufacturers, but also the distribution of finished products to the end consumer. Distribution plays an important role in a company's profitability because it affects operational costs, delivery efficiency, and perceived value by customers. Successful well-managed distribution will increase customer satisfaction and strengthen the company's competitiveness in the market. PT. XYZ is one of the LPG distributors that provides 3 kg cylinders. This company serves a variety of consumers, ranging from households, small businesses, to retailers, with a coverage of distribution areas in Serang City. The distribution process is carried out based on sales orders and needs in 14 bases, where each base has a different level of demand according to consumer needs. However, PT. XYZ faces obstacles in achieving the optimal level of service, where the average service level only reaches 97.40%. An imbalance between inventory and demand at the base often leads to an oversupply or understock, resulting in backorders on some demands. This condition has a negative impact on customer satisfaction and overall distribution effectiveness. To overcome this problem, PT. XYZ developed a distribution dashboard by applying the Distribution Requirements Planning (DRP) method. Through this approach, distribution planning becomes more systematic, base needs can be met appropriately, and stocks can be managed more effectively. This dashboard also supports delivery scheduling and more coordinated marketing activities. The results of the implementation of the DRP dashboard in 2023 show a significant increase with a service level that has successfully reached 99%, minimizing backorders, and increasing customer trust and satisfaction.

This study aims to evaluate community satisfaction with the CSR Program of PT Pertamina Patra Niaga Fuel Terminal Samarinda focused on talent and interest development for children of the Butonese community in Sidodadi Urban Village. A quantitative approach was applied using the Community Satisfaction Index (IKM) survey instrument based on Ministerial Regulation PANRB No. 14 of 2017, supported by Importance Performance Analysis (IPA). Results indicate an IKM score of 84.18, which falls under the “very good” category. However, several priority attributes, such as scheduling accuracy and supporting infrastructure, require improvement. Recommendations include service quality enhancement, community engagement, and sustainability-based planning.

This research iss motivated by the problem of the lack of digital learning facilities that can be flexibly accessed by students and theachers at SMP Djama'atul Ichwan Surakarta, so that interaction in the theaching and learning proces is limited. The theories applied in this study include the concept of E-Learning as a distance learning method rooted in information technology, web-based system development, and an interactive technology integration approach to increase effectiveness and engagement in learning. The method used is the Waterfall model system development life cycle (SDLC), which includes the stages of needs analysis, system design, implementation with PHP and MySQL using the CodeIgniter framework, and function testing. The research findings show that the designed web-based E-Learning system successfully provides features for managing student and teacher data, distributing teaching materials, scheduling lessons, giving assignments, and interaction through discussion forums. This system is considered capable of supporting a more organized and interactive online education process.The implementation of this systemis expected to a long-term solution to overcome the limitations of traditional learning methods and become a foundation for the development of digital learning platforms in the futur.

Generator Set Service Management is the process of organizing maintenance, repair, and upkeep activities of generator sets, starting from planning, implementation, evaluation, control, and improvement of services to ensure the generator machine continues to operate effectively and efficiently. The research was conducted at PT. Sigma Quantum Insani, located in Balikpapan, East Kalimantan. The problem addressed in the research is the frequent delays in completing scheduled tasks within the generator set service management activities. The purpose of the study is to determine the critical path of activities and identify the duration of the critical path. From the analysis using the Critical Path Method (CPM) assisted by MS Project software, the identified critical path activities are: A1-B1-B2-B3-B4-B5-B6-B7-B8-B9-B10-B14-B16-B17-C1-C2-D1-D2-D3, which include DO approval, engineering scope, painting scope, and delivery scope. The total time obtained for the critical path is 38 days, resulting in a time efficiency of 8 days in the generator set service process.