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Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in Indonesia’s economy, including in the garment industry. The subject of this study is MSME X, located in Cimahi City, which specializes in the production of knitted clothing. This research aims to identify production problems, analyze the causes of defects, and design improvement strategies using the Six Sigma method with the DMAIC (Define, Measure, Analyze, Improve, Control) approach. In the Define stage, the main problems are identified through the Critical to Quality (CTQ) approach, which reveals three major types of defects: button defects (39%), stitching defects (32%), and fabric or pattern defects (29%). Next, the Measure stage is conducted to assess process performance using quality indicators. The calculation results show a Defects per Million Opportunities (DPMO) value of 10,968.95 and a Sigma Level of 3.79, indicating room for improvement. The Analyze stage utilizes Pareto and Fishbone diagrams to identify root causes. The Improve stage applies Failure Mode and Effect Analysis (FMEA) to determine improvement priorities. The Control stage involves the use of Statistical Process Control (SPC), regular inspections, and an incentive system. This approach is expected to reduce defect rates and sustainably improve production efficiency.

The low proportion of Grade A harvest quality in Hokkaido corn farming remains a challenge for horticultural agribusiness practitioners. This study aims to develop an operational strategy based on a managerial evaluation of key production factors to improve technical efficiency and harvest quality. The research was conducted at PT Agricole Indonesia Makmur, Cianjur, using data from 24 planting periods in 2024. Six production input variables were analyzed to identify the most influential factors on yield quantity and quality. The results show that only three variables watering frequency, organic fertilizer, and plant age at harvest consistently contributed significantly to the production of Grade A output. Although these variables are inelastic, they play a critical role in maintaining quality. The proposed strategy includes a 10% increase in harvest quantity and a 30% conversion from Grade B to Grade A. Simulation results indicate an additional 7.67 kg of Grade A yield per planting period, generating a value increase of IDR 239,490. The strategy is considered feasible with a positive Return on Investment (ROI) of 14.04% assuming a Grade A selling price of IDR 35,000/kg.

In response to increasing competition in the manufacturing sector, PT X—a copper busbar manufacturing company—implemented Lean Manufacturing supported by Value Stream Mapping (VSM) to improve production efficiency and reduce supply chain costs. This study utilizes VSM, Value Stream Analysis Tools (VALSAT), and Root Cause Analysis (5 Whys) to identify sources of waste and formulate improvement strategies. The analysis identified three dominant wastes: waiting time, product defects, and excess inventory. These were mainly caused by the lack of standardized material procedures, inadequate supporting equipment, and poor integration between the incoming inspection process and the Enterprise Resource Planning (ERP) system. To address these issues, the study proposes installing silica rolls, providing air wipers and flatness tools, developing standardized work instructions, and integrating Internet of Things (IoT) technology with the ERP system for real-time monitoring. As a result of implementing these solutions, PT X successfully reduced its defect rate from 6.23% to 1.32%, decreased lead time, and achieved notable savings in supply chain costs. The findings demonstrate that integrating Lean Manufacturing principles with VSM can effectively eliminate non-value-added activities, streamline production processes, and enhance overall competitiveness. This study reinforces the strategic value of Lean tools in continuous improvement initiatives within the manufacturing industry.

This study aims to analyze the implementation of Total Quality Management (TQM) and its influence on employee performance at the Kepiting Soka Micro, Small, and Medium Enterprise (MSME) in Pangkalan Batu, Langkat Regency. This MSME operates in the soft-shell crab processing sector and faces challenges in maintaining product quality and production efficiency. The research uses a qualitative descriptive method, with data collection techniques including observation, interviews, and documentation. The results show that TQM implementation remains informal and unstructured. Although work practices such as precision and compliance with instructions reflect basic TQM principles, employee understanding of the concept is limited. Employee involvement in quality evaluation is also minimal, and there is no documented quality management system in place. The main obstacles In applying TQM in this MSME include a lack of training, limited resources, and the absence of clear Standard Operating Procedures (SOPs). Therefore, a gradual implementation of TQM is necessary, starting with the development of SOPs, regular training, and strengthening commitment to quality. These steps are expected to improve employee performance and enhance the competitiveness of The product in the market.    

In global competition, companies must be able to set competitive selling prices. Production cost components such as raw material costs, direct labor costs, and factory overhead costs are all included in the cost of goods manufactured. This study analyzes the COGS with Job Order Costing at PT. XYZ, a make-to-order company. The study was conducted by comparing COGS with Job Order Costing between Box Roller Conveyor and Bag Stop & Go Belt Conveyor as well as material usage and outsourcing. The results of the study indicate that Job Order Costing at PT.XYZ accurately traces the contribution of material costs and outsourcing to total production costs, and evaluates efficiency and cost control on each project with different characteristics. The use of Job Order Costing shows that Bag Stop & Go Belt Conveyor has a higher COGS of Rp299,655,813 than the COGS of Box Roller Conveyor of only Rp209,740,142. The cost structure shows that outsourcing is the most dominant component, reaching more than 98% of HPP on Bag Stop & Go Belt Conveyor, while raw material costs contribute less than 3%, so it can be concluded that the outsourcing vendor management strategy greatly affects the efficiency of production costs at PT. XYZ.

UMKM Bakso 43 located in Jatiwangi Village is one of the micro businesses in the culinary field that sells meatball products at home. This business experiences obstacles in production consistency and limited marketing strategies. This study aims to analyze the production and marketing strategies of UMKM Bakso 43 and provide solutions and directions for future development. The research method used is descriptive qualitative through observation, interviews, and direct assistance. The marketing strategy focused on in this study is through the Facebook social media platform. The results show that production efficiency can be increased through production rescheduling and recording raw materials, while digital marketing through Facebook can significantly increase consumer reach. This study concludes that collaboration between strengthening production management and simple digital marketing can be the main driver of UMKM development

The purpose of this research is to examine how production costs factor into producer choices, particularly those pertaining to output volume, selling price estimation, and company growth strategies.  The research examined micro and small business players in Kediri Regency, East Java, employing a descriptive quantitative technique.  The findings demonstrate that the production cost structure, particularly the preponderance of variable costs, considerably affects the quantity of output and the margin for price adjustment.  It has additionally been demonstrated that saving money encourages manufacturers to take risks and grow their companies.  Moreover, management accounting-based cost tracking, waste reduction, and sourcing local raw materials are all cost management tactics that impact a company's strength and ability to compete.  Producers' long-term strategic decision-making is therefore influenced by effective production cost management, which in turn affects operational sustainability.

The automotive industry is a strategic sector that plays a crucial role in national economic growth. Facing rapid digital transformation, automotive companies are increasingly adopting Business Intelligence (BI) systems to facilitate a data-oriented decision-making process. This study aims to explore the implementation of BI in XYZ, one of Indonesia’s largest car manufacturers. Using a descriptive qualitative approach through literature review, the research highlights how BI dashboards enable real-time analysis of vehicle sales trends, regional performance, and product models. The findings indicate that BI significantly enhances strategic planning, marketing accuracy, and operational efficiency. Visual tools such as Tableau provide centralized dashboards that facilitate faster insights, enabling companies to adjust production and distribution strategies based on data patterns. The study concludes that BI is not merely a visualization tool but a vital element of the digital transformation strategy in the automotive sector.

This research was conducted at PTPN IV Regional II Adolina Palm Oil Plantation and Mill Unit with the aim of evaluating the effect of Ripple Mill machine efficiency on palm kernel impurity levels through a multiple linear regression analysis approach. Ripple Mill is a vital piece of equipment in the palm kernel cracking process, which plays a role in determining the quality of the palm kernel. This machine works by breaking the kernels to produce kernels that are separated from the shells. However, when machine efficiency decreases due to technical and operational factors, palm kernel impurity levels tend to increase, characterized by an increase in shell fragments, fibers, and other foreign materials. This condition can have an impact on decreasing product quality and increasing further processing costs. Data collection was carried out over five days of observations covering the variables of machine efficiency and kernel impurity levels obtained from production results. The study found a strong negative correlation between machine efficiency and impurity levels in palm kernels. This means that the higher the efficiency of the Ripple Mill, the lower the resulting palm kernel impurity levels. This finding also confirms that quality control in the production process is not only determined by raw material factors but also highly dependent on the performance of the processing machine. Furthermore, the research results demonstrate the importance of implementing preventive maintenance strategies, including regular inspections of the rotor bar, square bar, and drive motor, as well as regulating operating parameters such as rotational speed and machine load. Proper preventive maintenance and operational control are essential to sustain machine efficiency and product quality. Therefore, continuous improvement in technical and managerial aspects is essential to maintain palm kernel quality and support optimal palm oil mill productivity.

The Ripple Mill machine is one of the vital components in a Palm Oil Mill (PKS) that functions to separate the palm kernel from its shell. This process is very important because the quality and quantity of the palm kernel produced will directly affect the economic value and production efficiency in the palm oil industry. At PTPN IV Regional II Plantation Unit and Adolina PKS, various technical problems were found that caused a decrease in machine performance, including rotor bars and square bars that experienced wear due to age and improper machine settings. In addition, other damage that often occurs is a broken van belt due to age and excessive tension, feeder motor dysfunction caused by excessive load, and motor overheating that occurs due to age and high workload. To overcome these problems, this study uses the Failure Mode and Effect Analysis (FMEA) method. This method aims to identify various potential failures, assess the severity, frequency of occurrence, and detection capability, so that the Risk Priority Number (RPN) value can be calculated as a basis for repair priorities. The results showed that worn rotor bars and worn square bars had the highest RPN values, each at 280, equivalent to 40.23% of the total identified risks. This indicates that these two components are critical points requiring immediate repair and maintenance attention. Applying FMEA in this context provides tangible benefits, including helping the company formulate a more targeted maintenance strategy, reducing the risk of recurring damage, and minimizing downtime that impacts production. With more systematic maintenance, operational efficiency can be improved while extending the lifespan of the Ripple Mill machine.

A sustainable digital economy is an economic system that integrates digital technology, social sustainability, and resource efficiency within production processes and labor distribution. Advances in information technology, automation, and artificial intelligence have transformed the structure of the global labor market and created skill disparities among workers. The unpreparedness of human resources in facing digital transformation has led to gaps in access to training, technological literacy, and equal employment opportunities. Strengthening human capital is therefore a strategic solution to maintain balance between technological progress and social justice. This study employs a descriptive qualitative approach through Focus Group Discussions and literature reviews within the 2022–2025 period to analyze the interrelationships between competency development, automation implementation, and digital equity. The findings indicate that improving digital capabilities through upskilling, reskilling, and technology-based education enhances workforce resilience against disruption. Collaboration among government, industry, and educational institutions is proven to be effective in expanding training access, reducing the digital divide, and creating an inclusive and adaptive work ecosystem in the era of a sustainable digital economy.

The on-demand economy has transformed consumer expectations, demanding fast, transparent, and efficient services. However, the MSME printing sector in Indonesia is often still hampered by manual processes that cannot meet these demands. This research aims to design and validate an on-demand printing service platform interface that acts as a digital bridge between customer demand and MSME production capacity. Using a User-Centered Design (UCD) methodology, a high-fidelity interactive prototype was designed and validated through usability testing with 20 respondents. The test results demonstrated excellent usability, with an average task completion rate of 93%, an overall relative efficiency of 91.4%, and a user satisfaction score of 88%. These results validate that the platform design focusing on instant ordering flows, real-time price calculation, and a job management dashboard for service providers successfully creates an effective and satisfying user experience. The implication of this research is a validated platform model that can serve as a catalyst for printing MSMEs to adapt to the on-demand economy, increase their competitiveness, and participate in the broader digital ecosystem.

This study was conducted to analyze the effect of suction power effectiveness on cyclones in Light Tenera Dust Separator (LTDS) 1 and 2 units on the level of palm kernel losses at PTPN IV Regional II Plantation Unit and Adolina Palm Oil Mill (POM). Palm kernel loss is a significant factor that can reduce production efficiency, as palm kernel has high economic value and is the main product in the palm oil industry. Kernel losses not only reduce production efficiency but also create significant economic disadvantages for the palm oil mill. The research method used was a gravimetric method with a field experiment approach. The research process included sampling from LTDS waste, separating kernels from shells, and measuring suction speed using an anemometer to determine cyclone performance. The gravimetric method was applied to quantify the proportion of kernel mixed with shell waste, providing measurable data on suction efficiency. The results showed that low suction power effectiveness was directly proportional to the increasing number of kernels that were thrown away with the shells. In other words, poor suction performance directly correlates with higher kernel losses. The main contributing factors include leaks in the cyclone, suboptimal blower settings, and inadequate operator skills. Operational skills and equipment maintenance were identified as crucial determinants of system performance. Based on these findings, improvements to the suction system are recommended through routine maintenance, leak checks, and blower setting calibration. Furthermore, operator training is required to precisely adjust suction power. By maintaining suction effectiveness and optimizing blower settings, kernel losses can be reduced below the standard threshold of 2.0%. Thus, mills can improve operational efficiency while minimizing economic losses due to palm kernel loss.  

PT Perkebunan Nusantara I (PTPN I) is an Indonesian State-Owned Enterprise (BUMN) specializing in plantation operations, particularly the cultivation and processing of primary commodities, including rubber, coffee, and tea. Additionally, the company engages in secondary ventures such as tobacco production, plastic sack manufacturing, and asset optimization. As of December 1, 2023, PTPN I functions as a subholding entity with regional offices strategically located in Sumatra, Java, and Sulawesi to enhance operational efficiency. The company was originally established in Aceh in 1961 as PPN Kesatuan Aceh, marking the beginning of its long-standing presence in the industry.This study aims to analyze the impact of transformational leadership, internal communication, and work ability on both organizational commitment and organizational performance at PTPN I’s Surabaya region. Utilizing a quantitative causal-explanatory approach, primary data was collected through structured questionnaires. The target population comprised employees of PTPN I in Surabaya, with 100 respondents selected via purposive sampling. Data analysis techniques included descriptive statistics and SEM-PLS (Structural Equation Modeling-Partial Least Squares). Findings reveal that transformational leadership, internal communication, and work ability significantly and positively influence organizational commitment. Likewise, transformational leadership, work ability, and organizational commitment exhibit a significant positive relationship with organizational performance. However, although internal communication has a favorable effect, its impact on organizational performance is not statistically significant in this context.

This study uses a qualitative method to analyze the integration model of Supply Chain Management (SCM) in the manufacturing-service industry, focusing on a case study in the automotive sector. SCM integration in this context involves the coordination of production processes, distribution, and after-sales services to enhance efficiency and responsiveness to customer demands. Data were collected through in-depth interviews and direct observations at an automotive company implementing integration strategies between manufacturing and service operations. The findings show that cross-functional collaboration among suppliers, manufacturers, and service providers plays a vital role in creating an adaptive supply chain. Digital integration through connected information systems also significantly accelerates decision-making and improves overall supply chain visibility. This study highlights the importance of a holistic approach encompassing technical, organizational, and inter-partner relationship aspects. The results are relevant for automotive companies aiming to strengthen competitiveness through cross-sector SCM integration and serve as a reference for developing industrial policies that support collaboration between manufacturing and service actors in the Industry 4.0 era.  

Shrimp shell waste is a potential marine biomass resource rich in bioactive compounds such as astaxanthin and chitin, yet remains underutilized in the livestock sector. This study aimed to evaluate the effect of incorporating shrimp shell meal into duck (Anas sp.) feed rations on the yolk color intensity of duck eggs. The experimental design applied a completely randomized design (CRD) with a single factor and four treatments: D0 (100% rice bran, control), A1 (rice bran + 2% shrimp shell meal), A2 (rice bran + 6%), and A3 (rice bran + 10%), with a 21-day observation period. The primary parameter measured was yolk color intensity, assessed visually using a standardized color scale. The results indicated that the addition of shrimp shell meal significantly enhanced yolk color intensity, with the highest pigmentation observed in the A3 treatment. Astaxanthin, functioning as a natural carotenoid pigment, was biologically absorbed and distributed into the yolk via lipophilic pathways, while chitin supported gut health and nutrient absorption efficiency. This study aligns with the principles of the circular economy by valorizing marine processing waste as a functional feed ingredient. A 10% inclusion rate was found to be visually optimal; however, further studies are required to assess its physiological impacts and economic feasibility in broader production contexts.

Sensitivity analysis is an important method in linear programming used to evaluate the impact of parameter changes on optimal solutions in production optimization. This study aims to identify and analyze various sensitivity analysis methods applied in previous studies. Through a systematic literature review approach, the research finds that sensitivity analysis provides valuable insights into solution stability and the effects of parameter changes on optimal outcomes. The findings indicate that this method can support better strategic decision-making in industrial contexts. The results of this research are expected to offer practical recommendations for practitioners to enhance production efficiency and effectiveness.

The distribution of sugarcane from farmers to sugar mills in Indonesia continues to face various challenges, particularly in terms of logistical efficiency and farmers’ dependency on intermediaries. This study aims to analyze the role of intermediaries in determining the efficiency of sugarcane distribution, using a case study in Kedungmakam Village, Tuban Regency. A qualitative approach with a case study design was employed, enabling an in-depth understanding of distribution practices directly in the field. Data were collected through field observations, in-depth interviews with farmers, intermediaries, and retail traders, as well as supporting documentation. The results indicate that intermediaries play a crucial role in providing production capital, scheduling harvests, and managing transportation of sugarcane to the mills. However, their dominance, in the absence of formal contracts, creates relationship imbalances and weakens the bargaining position of farmers. Furthermore, geographical barriers, limited access to market information, and the lack of independent distribution infrastructure exacerbate inefficiencies and reduce fairness in the existing distribution system. Therefore, strengthening farmer institutions, improving contract transparency, and enhancing access to logistics and information are recommended as long-term solutions.

This study examines the role of environmental cost management in improving operational efficiency in manufacturing companies. Using a descriptive qualitative approach through a case study in Indonesia, the findings show that effective environmental cost management reduces waste and enhances production efficiency. Separate reporting of environmental costs also improves transparency and accountability.

The manufacturing industry faces major challenges in maintaining consistent product quality amidst the dynamics of technology and global competition. This study aims to develop an effective Business Intelligence (BI) implementation model to support data-based quality control. The method used is a conceptual design approach through integrated system simulation, including MySQL database, PHP backend, Power BI visualization, Google Cloud AutoML predictive analytics, and initial processing using Microsoft Excel. Historical production data for 12 months is used for model training and defect trend visualization. The simulation results show that the implementation of BI can reduce product defect rates, accelerate system response, and increase inspection process efficiency. Technical validation proves the model's prediction accuracy is above 90%, while field validation shows positive acceptance from users regarding the ease of use of the dashboard. This system not only supports early detection of quality deviations but also contributes to real-time strategic decision making. With an integrated technology approach, BI enables medium-sized manufacturing companies to adopt an adaptive and sustainable digital quality system, in line with the concept of Quality 4.0.