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This study was conducted at PT. Asmin Bara Bronang, Sepan Uring Village, Kapuas Tengah District, Kapuas Regency, Central Kalimantan Province, with the aim of analyzing the productivity and influencing factors of the PC 300 excavator in coal getting activities to support the achievement of production targets. The objective of this research is to analyze the actual productivity and the factors affecting it in Sector 7 coal getting operations. The research method used field observation with a quantitative descriptive analysis approach. The results show that the productivity of the PC 300 excavator ranges from 127.12 to 224.29 tons/hour, with an average of 173.98 tons/hour. In several conditions, the productivity is still below the company’s target of 180 tons/hour. The analysis indicates that productivity is influenced by material conditions, particularly the Hardgrove Grindability Index (HGI) value of 47, which reflects relatively harder material with coarser particle size, and a moisture content of 22.71%, causing the material to be sticky and cohesive, thereby affecting the bucket filling process. In addition, operational factors such as bottom loading patterns, limited number of tailgate dump trucks, and suboptimal selection of dump truck types also contribute to productivity performance.  Based on the findings, it can be concluded that the productivity of the PC 300 excavator has not consistently met the company’s target. Therefore, improvement efforts are required, including the implementation of top loading methods, increasing the number of tailgate dump trucks, optimizing the selection of hauling equipment, and controlling material conditions that affect the digging process.    

The study analyzes the implementation of the 5S method (Seiri, Seiton, Seiso, Seiketsu, Shitsuke) in improving shoe production quality at the Assembly section of PT X through observation, interviews, and documentation. Involving supervisors, production leaders, and operators, the study aimed to assess the impact of 5S on production processes. The results showed that the implementation of 5S successfully created a more organized, cleaner, and standardized work environment. These improvements led to a reduction in potential work errors, increased process efficiency, and the establishment of an employee disciplinary culture. Employees became more aware of maintaining cleanliness and orderliness, which contributed to a smoother workflow and better quality control. The findings align with theories of quality management, organizational behavior, and operations management, demonstrating the benefits of 5S in enhancing operational effectiveness. This study confirms that integrating the 5S method into industrial practices, particularly during internships, is an effective strategy to encourage continuous improvement and enhance production quality in the industry.

The shoe manufacturing industry demands a planned, integrated, and consistent production system in maintaining product quality. One of the crucial stages is the gluing process between the outsole (rubber) and the midsole (phylon), which determines the adhesive strength, comfort, and durability of the shoe. This study aims to analyze the implementation of internship activities in a series of gluing processes in the Stockfit Department of PT X. The research method uses a qualitative descriptive approach with data collection techniques through direct observation, involvement in production activities, and systematic field recording during the internship period. The analysis was carried out by linking the field findings with the operations management theory of Heizer and Render, the Crosby concept of quality management, and the principles of continuous improvement from Deming and Imai. The results of the study show that the gluing process has been systematically arranged, starting from material adjustment, primary application, the use of two types of glue, the rubber cutting process, to the final pasting. However, problems were found such as dependency between processes, inconsistency in glue thickness, as well as the influence of machine conditions and operator skills. These problems have the potential to reduce production efficiency and the quality of the final product. Therefore, it is necessary to strengthen process control and apply the principle of continuous improvement to improve overall production performance.

Operational risk management is an essential aspect in maintaining the stability and sustainability of micro-enterprises operating in the culinary sector, particularly in the fast food industry, which relies heavily on production processes, raw material quality, and human resource skills. This study aims to analyze the types of operational risks that arise in the daily operations of the Kebab Capadocia MSME in Boyolali Regency using a qualitative approach through in-depth interviews and field observations. The COSO Enterprise Risk Management (ERM) Framework was used as the primary theoretical foundation to map risks based on five components: risk identification, risk assessment, control activities, information and communication, and monitoring. The results indicate that the business faces four main risk categories: production process risks, human resource risks, food hygiene and safety risks, and raw material distribution risks. Implemented controls are still informal and not supported by standard operating procedures (SOPs), resulting in recurring risks that impact product quality. These findings contribute to the MSME risk management literature and offer practical recommendations for strengthening operational structures based on systematic risk management.

This study aims to analyze the transformative impact of digitalization and technology in the manufacturing sector on improving operational efficiency, particularly in budgeting and resource utilization, as well as to identify the main barriers to technology adoption. Using a Literature Review and Case Study Analysis of secondary data (journals, company reports, and industry publications), it was found that digitalization and Automation supported by Artificial Intelligence (AI) fundamentally transform budgeting functions. This transformation has been shown to improve budget accuracy by up to 50% (reducing human errors) and process efficiency by up to 25%, turning budgets from static documents into adaptive and predictive control tools. Positive impacts are also observed in operations through increased production capacity (revenue surge) and the implementation of Predictive Maintenance, which reduces expenditure and asset downtime, in line with the principles Cost Efficiency and Lean Manufacturing. Nevertheless, the adoption of advanced technology faces significant obstacles, namely high initial capital investment and skill gaps among the workforce. It is concluded that the success of digitalization heavily depends on strategic budget planning to overcome capital barriers and adequate allocation of funds for Human Resource (HR) training to support effective collaboration between humans and machines.

Production planning and inventory control are critical aspects of operations management, as they directly influence cost efficiency, resource utilization, and the continuity of the production process. Ineffective planning and inventory decisions may lead to excessive costs, production delays, or imbalances between supply and demand. The complexity of these problems, which often involve multi-period horizons and multi-stage decision-making processes, has encouraged the application of quantitative optimization methods, one of which is dynamic programming. This study aims to analyze and synthesize the application of dynamic programming in production planning and inventory control through a Systematic Literature Review (SLR) approach. The SLR process was conducted by systematically identifying, selecting, and analyzing 15 relevant national journal articles published between 2015 and 2024 and obtained from various recognized scientific databases. The reviewed literature indicates that dynamic programming is effective in supporting optimal decision-making by determining appropriate production quantities and inventory levels, minimizing total production and holding costs, and managing fluctuating demand conditions. In addition, this method helps reduce the risks associated with overstock and stockouts by considering sequential decision structures. However, the findings also reveal several limitations of dynamic programming, including high computational complexity, strong dependence on deterministic data assumptions, and limited flexibility in handling high levels of uncertainty. These constraints suggest the need for further methodological development or integration with other approaches to enhance practical applicability.

The Field Work Practice (PKN) carried out at PT MK Prima Indonesia focused on the implementation of periodic maintenance practices for the premoulding hydraulic press machine as an effort to maintain machine performance and operational lifespan. The main activities included identifying critical components such as the hydraulic system, valves, pressure hoses, and oil filters; conducting direct observation of common disruptions; and performing daily maintenance checklists that covered pressure monitoring, operating temperature, leakage detection, machine cleanliness, and lubrication conditions. Comprehensive cleaning procedures, condition-based filter replacement, and functional testing were also conducted to ensure reliability and safety in the production process. The implementation methods involved participatory observation, interviews with technicians regarding common failure patterns, visual and functional inspections, as well as the use of structured checklists supported by inspection documentation. The results indicate a significant decrease in the frequency of disturbances caused by leaks and oil contamination, improved compliance with routine inspection procedures, and enhanced machine readiness during operations. The introduction of structured documentation and simple technical training further improved technicians’ ability to detect early signs of abnormalities in the hydraulic system. As a recommendation, the company is advised to strengthen the use of digital recording systems, adjust filter replacement intervals based on actual machine conditions, and implement regular training programs focusing on contamination control and predictive maintenance.

The Field Work Practice (PKN) carried out at PT MK Prima Indonesia focused on the implementation of periodic maintenance practices for the premoulding hydraulic press machine as an effort to maintain machine performance and operational lifespan. The main activities included identifying critical components such as the hydraulic system, valves, pressure hoses, and oil filters; conducting direct observation of common disruptions; and performing daily maintenance checklists that covered pressure monitoring, operating temperature, leakage detection, machine cleanliness, and lubrication conditions. Comprehensive cleaning procedures, condition-based filter replacement, and functional testing were also conducted to ensure reliability and safety in the production process. The implementation methods involved participatory observation, interviews with technicians regarding common failure patterns, visual and functional inspections, as well as the use of structured checklists supported by inspection documentation. The results indicate a significant decrease in the frequency of disturbances caused by leaks and oil contamination, improved compliance with routine inspection procedures, and enhanced machine readiness during operations. The introduction of structured documentation and simple technical training further improved technicians’ ability to detect early signs of abnormalities in the hydraulic system. As a recommendation, the company is advised to strengthen the use of digital recording systems, adjust filter replacement intervals based on actual machine conditions, and implement regular training programs focusing on contamination control and predictive maintenance.

Overburden removal is a critical phase in coal mining operations, as it directly affects production continuity and operational efficiency. However, production realization often deviates from the mine plan due to various operational constraints. This study, conducted at Pit K1 Mahakam of PT. Insani Baraperkasa, evaluates the causes of underachievement in overburden stripping targets using the Six Big Losses framework, which classifies inefficiencies into Breakdown Losses, Setup and Adjustment Losses, Idling and Minor Stops, Reduced Speed Losses, Process Defect Losses, and Reduced Yield Losses. The analysis revealed that the dominant losses were Reduced Speed Losses (26%) and Setup and Adjustment Losses (10%), primarily caused by disposal congestion, shift changes, and repairs at the loading and disposal areas. Minor contributions were found from idling (3%), production losses (5%), while breakdown losses showed negligible impact. These factors led to increased standby time and reduced equipment cycle effectiveness. Improvement strategies are recommended through optimized disposal allocation, reduction of waiting time, and stricter control of external operational disruptions to enhance stripping efficiency and achieve production targets.

This study aims to analyze production performance and the factors influencing the productivity of mining operations at PT. XYZ during August 2025. The evaluation covers production achievement against the corporate work plan (RKAP) and the owner’s operational plan, equipment availability (Physical Availability), the productivity of loading and hauling units, and various types of loss time that reduce effective working hours. The results indicate that production realization reached only 65% of the RKAP target, while achieving 102% of the owner’s plan for total material. Low equipment availability, high loss time such as no hauler, wait operator, and front preparation, as well as the underperformance of 80-ton and 100-ton units, were identified as the main contributors to production deviation. Additional influencing factors include unit reassignment, suboptimal haul road conditions, and insufficient operational fleet numbers. The study recommends optimizing fleet management, enhancing preventive and predictive maintenance programs, reorganizing hauling workflows, and controlling dominant loss time sources to improve operational efficiency and production target achievement in future periods.

The purpose of this research is to use the six sigma approach to assess the quality of cracker manufacturing at UD. Palapa in Nganjuk Regency. This technology was chosen because it allows for quantitative measurement and analysis of product defect levels, as well as the identification of defect-causing variables. The study was carried out using the DMAIC (Define, Measure, Analyze, Improve, Control) steps and statistical methods such as Pareto diagrams, fishbone diagrams, and C-chart control charts. According to the research, the cracker manufacturing process at UD. Palapa has an average sigma value of 2.74, which is still below the six sigma (6σ) threshold.  This figure implies that the product fault rate remains fairly high.  The most common forms of faults are irregular shape and uneven thickness, which are mostly produced by machine, human, process, and raw material problems. C-chart analysis reveals that most processes are still under control, while there are a few spots beyond the control boundaries that indicate unique variances. Based on these data, it is possible to infer that UD. Palapa's quality control system is still reactive and has to be improved in order to be more proactive. Routine equipment maintenance, operator training, the introduction of standard operating procedures (SOP), and more stringent raw material selection are all possible efforts. Six Sigma deployment has been shown to provide a full view of production quality conditions, as well as a foundation for future continuous improvement programs.

This study aims to gain an in-depth understanding of the implementation of bread product quality control in the Pastry Section of Harris Hotel & Conventions Bundaran Satelit Surabaya, covering four main aspects: raw materials, production process, storage, and presentation. Furthermore, this study focuses on understanding the Standard Operating Procedures (SOPs) for bread production operations and the level of implementation of these SOPs in daily work practices. The research method used is descriptive qualitative, with data collection techniques through direct field observation, interviews with pastry section staff, and documentation related to bread production activities. The results show that bread product quality control is carried out comprehensively. In the initial stage, raw material selection is carried out strictly to ensure quality, freshness, and food safety. The production process is carried out according to standard procedures, paying attention to equipment cleanliness, processing techniques, and timeliness, resulting in products that are consistent in taste and texture. The storage stage is also carried out hygienically with a system for arranging ingredients and finished products that pay attention to temperature, humidity, and cleanliness of the storage room. In the final stage, bread is served with good aesthetic standards while maintaining food safety aspects, thus adding value to the hotel guest experience. The bread production operational SOP has been systematically developed and serves as an important reference for all pastry section employees in carrying out their daily tasks. Employee compliance with the SOP is high, although challenges remain, such as limited trainee skills and delays in raw material supplies from suppliers. These challenges can usually be overcome through direct supervision, internal training, and good communication with material suppliers. Overall, the implementation of quality control and bread production SOPs at Harris Hotel & Conventions Bundaran Satelit Surabaya has been running smoothly and consistently.

The study aims to evaluate the flow of material in the handling process and the quality control measures implemented throughout the production stages. The research employs a qualitative descriptive method, utilizing primary data collected through direct observation, interviews, and secondary data from relevant literature. The findings indicate that the IQF method significantly preserves the quality and freshness of the shrimp, ensuring compliance with international export standards. The study also identifies strengths, weaknesses, opportunities, and threats (SWOT analysis) related to the company's operations, highlighting the importance of maintaining high-quality raw materials and efficient production processes. Recommendations for improving quality control practices and enhancing operational efficiency are provided, emphasizing the need for continuous training and investment in modern technology.

Aquaculture is a vital sector in global food production, providing essential protein sources. However, the industry faces significant challenges, including high energy consumption and environmental impact. The integration of renewable energy, particularly solar power, with automation and IoT systems offers a promising solution to enhance energy efficiency, sustainability, and productivity in aquaculture operations. This study aims to evaluate the effectiveness of solar powered autonomous systems in reducing energy usage, improving operational efficiency, and promoting environmental sustainability in aquaculture. Literature Review: Recent research has explored various technologies, such as Digital Twins (DTs) and Precision Fish Farming (PFF), which integrate IoT sensors for real time monitoring and optimization of fish farming operations. The combination of Artificial Intelligence (AI) and the Internet of Things (IoT), known as AIoT, has further advanced the industry by enabling automated decision making and predictive analytics. Solar power integration with IoT systems has been shown to significantly reduce operational costs, minimize carbon emissions, and enhance the sustainability of aquaculture practices. These advancements have the potential to address the challenges of energy consumption and environmental degradation in the industry. Materials and Method: This research utilizes a hybrid solar powered IoT system for aquaculture, integrating solar panels, IoT sensors, and automated control systems. The system monitors key water quality parameters, such as pH, dissolved oxygen, turbidity, and temperature, to maintain optimal conditions for aquatic life. Data is collected through IoT sensors and analyzed through a cloud-based platform. A pilot study is conducted on a small scale aquaculture farm to evaluate the system's performance, including energy consumption, water quality management, and fish health. Energy savings, operational efficiency, and environmental impact are assessed. Results and Discussion: The integration of solar powered IoT systems significantly reduced energy consumption compared to traditional systems, with a notable decrease in grid electricity reliance. The system successfully maintained optimal water quality conditions, enhancing fish health and growth. Solar powered systems proved reliable, even in regions with variable sunlight, and demonstrated improvements in operational efficiency through automation. The environmental benefits were evident, with a reduction in carbon emissions and lower operational costs. The study highlights the feasibility of solar powered IoT systems as a sustainable solution for modern aquaculture operations.

Occupational Health and Safety (OHS) is a crucial aspect of the textile industry to ensure worker protection and maintain smooth production processes. This study aims to identify and analyze potential occupational accident risks in the sizing machine process. The methods used in this research are Job Safety Analysis (JSA) and Risk Assessment to evaluate workplace hazards that may disrupt operations. The results indicate several major risks in the sizing process, including mechanical hazards due to direct contact with machines, ergonomic hazards caused by improper working postures, and chemical hazards from exposure to cotton dust and sizing solution vapors. The main risk factors include human aspects, the work environment, and machinery. The recommended improvements in this study include enhancing work supervision and control, providing safety training for workers, optimizing workplace ergonomics, and conducting regular machine maintenance to reduce accident risks. The proper implementation of safety strategies is expected to improve production efficiency and create a safer and more conducive work environment.

This study aims to analyze the implementation of the accounting system at Mie Baso Akung, which is part of the Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. The main focus of this report is to explain the accounting system in the cash sales, purchasing, inventory, and payroll and wages sections. In its work, the author uses qualitative methods through interview techniques and also observation. Based on the results of the study, it was found that most of the processes are still carried out manually by the owner who does not comply with the proper procedures. This indicates the need for the implementation of a more structured system to improve operational efficiency. In addition, this study also identified obstacles in inventory management, which is very important to maintain the availability of raw materials and production efficiency. Therefore, Mie Baso Akung needs to implement a more detailed accounting information system and better internal control in order to improve operational efficiency that can help Mie Baso Akung in managing its finances and operations more effectively.

This study evaluates the impact of an AI-driven nutritional monitoring system in hospital settings, focusing on its effectiveness in reducing food waste and improving the accuracy of dietary assessments. Traditional food waste management and nutritional tracking methods in hospitals often suffer from inefficiencies, inaccuracies, and time constraints. In contrast, the AI-based system utilizes advanced technologies, including 3D scanners, digital scales, and image recognition, to optimize food production, minimize waste, and provide more accurate and timely nutritional assessments. The results of this study show a 31% reduction in food waste and a 40% improvement in the accuracy of nutritional assessments after implementing the AI system. This system enhances meal planning, portion control, and real-time tracking of food intake, offering personalized recommendations based on patient needs. The AI system also streamlines the nutritional assessment process, reducing labor-intensive procedures and providing real-time feedback to clinicians, which helps improve patient care and reduce errors associated with traditional methods. Furthermore, the environmental and financial implications of adopting AI technologies in healthcare are significant. The reduction in food waste not only helps lower hospital costs but also contributes to sustainability goals by reducing resource consumption, including water, land, and energy. This study underscores the potential of AI-driven systems to improve healthcare operations, support sustainability, and enhance patient outcomes. Future research should focus on expanding the application of AI in other healthcare sectors and further exploring its integration with other technologies for comprehensive healthcare solutions.

Batik Banten Mukarnas is a company that produces stamped batik designs with various patterns and varieties of batik. Problems frequently arise in the company due to increased stamped batik production capacity to meet the demand for stamped batik design products, which continues to rise from stamped batik suppliers. Another impact of growing demand capacity is the high number of defects in stamped batik cloth products, because overall, the company's management, including human resources, tools, and methods, is not prepared for the increase in production capacity to meet the surge in consumer demand, resulting in an impact on the quality of the products produced—consequently, the organization endeavors to regulate the quality of stamped batik cloth at PT. Batik Banten Mukarnas establishes objectives that employ Six Sigma with the DMAIC method (Define, Measure, Analyze, Improve, and Control) in the production of batik stamp designs to meet production objectives. The results of the data processing that has been done obtained a sigma value before improvement for 3 CTQ of 3.54. After improvement, the sigma value increased to 3.86. While for the sigma value before improvement for 1 CTQ of 3.04, the sigma value increased to 3.42 after improvement. The factors contributing to defective products, as illustrated by the fishbone diagram, include methods, personnel, materials, machinery, and environmental conditions. The division leader consistently oversees and regulates operations, enhances the number of brushes, and trains operators to ensure proficient adherence to standard operating procedures (SOP).

Operations management is a series of activities related to planning, organizing, controlling and supervising all resources used in the process of producing goods or services. The main function of operations management is to create quality products or services, at efficient costs, at the right time, and in accordance with market demand. This research is quantitative research that works with numbers and the data is in the form of numbers which are then analyzed using statistics to test hypotheses or to answer specific research questions and to make predictions. This research approach is explanatory research where data collection is carried out simultaneously in one stage (one shot study} or in a cross-section through a questionnaire. One of the main impacts of operations management what is good is increasing the efficiency of the production process by designing and managing efficient production processes, companies can optimize the use of available resources, reduce waste, and increase output without increasing significant costs. Effective operations management has a significant impact on various aspects of company performance, including operational efficiency, cost control, product quality and service, and customer satisfaction. By implementing good operations management principles, companies can increase their competitiveness, reduce waste, and improve the customer experience.

PT. Pebana Adi Sarana targets monthly production operations of 20,000 tons/month while actual production is only around 15,000 tons/month, which means that the production target has not been achieved. The factors that cause the failure to achieve the production operation target can be due to ineffective equipment performance, Low equipment performance is one of the things that cause production not to be achieved, so it needs to be studied. The purpose of the study to be achieved is to analyze the actual productivity of loading and unloading equipment and transportation equipment after repairs and conduct improvement analysis using the Quality Control Circle (QCC) method. The data taken for the research is in the form of Excavator and dump truck cycle time data, effective working time, tool specifications. The actual productivity of loading and unloading equipment and transportation equipment at PT. Pebana Adi Sarana for dump trucks of 19,146 tons/month. trucks are 16,351 tons/month while for the Quality Control Circle (QCC) method. The company only needs to carry out the number of tools needed for 3 units of Scania p380 dump trucks and 1 unit of komatsu PC 300 excavator with a production of 21,295 tons/month has exceeded the production target set by the company.