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UMKM Tahu XYZ, a small-scale tofu producer, is currently facing significant challenges in maintaining consistent product quality, primarily due to a high defect rate. Common issues identified include crumbled tofu shapes, overly soft textures, and inconsistent taste, which negatively impact customer satisfaction and business sustainability. This study aims to investigate the root causes of these quality issues and propose practical solutions using the Lean Six Sigma methodology. The research employs a descriptive quantitative approach through the DMAIC framework—Define, Measure, Analyze, Improve, and Control—to ensure systematic problem-solving. Data were collected over a six-month period through direct observation, structured interviews, and review of production records. The analysis identified four dominant types of waste within the production process: unnecessary transportation, product defects, excessive movement, and over-processing. The root causes of these inefficiencies are linked to poor handling of raw materials, variability in soybean quality, and an ineffective production layout that hampers workflow and consistency. To address these problems, the study proposes several targeted interventions, including the redesign of the production layout to optimize flow, the implementation of the 5S (Sort, Set in order, Shine, Standardize, Sustain) workplace organization method, the development of standardized operating procedures (SOPs), and the adoption of improved soybean boiling technology. The implementation of these improvements is projected to significantly reduce product defects, enhance process efficiency, and ultimately increase customer satisfaction. Furthermore, these actions are expected to improve the overall competitiveness of UMKM Tahu XYZ within the highly demanding food industry sector. This research provides actionable insights for other micro, small, and medium enterprises (MSMEs) seeking to apply structured quality control methods to strengthen operational performance and long-term business resilience.

This study aims to analyze and improve the quality control of packaging printing production at PT XYZ by applying the Lean Six Sigma methodology. Lean Six Sigma combines waste reduction principles with statistical quality control to achieve operational excellence. The research identifies major production challenges, including high defect rates, overproduction, and ineffective inventory management, all of which contribute to increased costs and reduced efficiency. The DMAIC framework—Define, Measure, Analyze, Improve, and Control—was employed to systematically address these issues. During the Define and Measure phases, types of waste were identified and defect rates were calculated using Defects Per Million Opportunities (DPMO). In the Analyze phase, root causes were examined using a Fishbone (Ishikawa) diagram, highlighting factors related to manpower, materials, machines, and methods. The analysis revealed a sigma level of 3.2, indicating a moderate level of process quality and substantial room for improvement. To address the identified issues, several improvement strategies were proposed. These include implementing a Just-In-Time (JIT) system to reduce inventory waste, adopting the First-In-First-Out (FIFO) inventory method for better material rotation, and conducting targeted technical training for operators to minimize human error. In the Control phase, the study suggests process standardization, routine inspections, and continuous monitoring as key practices to ensure that improvements are sustained over time. The findings and recommendations from this study are expected to contribute to better quality control, reduced operational waste, and enhanced productivity in the packaging printing process. Ultimately, this approach aims to strengthen PT XYZ’s competitiveness in the printing industry by fostering a culture of continuous improvement and quality excellence.

The spice industry faces significant challenges in maintaining product weight consistency as part of quality assurance and compliance with production standards. A case at PT X revealed that a newly installed filling machine produced deviations from the target weight of 50 grams, with hypothesis testing showing that out of 30 samples, 17 samples fell outside the  confidence interval. To mitigate this issue, this study proposes the development of a real-time data-driven Decision Support sistem (DSS) combined with statistical approaches. The methodology includes two-tailed hypothesis testing to detect weight deviations and Failure Mode and Effects Analysis (FMEA) to identify dominant failure causes based on high Risk Priority Numbers (RPN), such as delayed machine calibration, operator error, and worn-out machine components. These findings serve as the foundation for designing the DSS architecture, which consists of sensor input modules, statistical data processing, risk mapping, and an automated corrective recommendation engine. The sistem is designed to enable early detection of deviations, accelerate response time to quality issues, and support data-driven decision-making on the production floor. The study concludes that a structured implementation of DSS can be an effective strategy to improve product weight consistency and enhance operational efficiency in spice manufacturing.  

Coal is one of the main energy sources and the largest contributor to national revenue; however, its management faces challenges related to limited availability and accuracy in reserve estimation. An essential aspect of mining management is monitoring the Run of Mine (ROM) volume, which plays a critical role in crushing, washing, and blending processes. This study aims to compare the accuracy of ROM volume measurements using Terrestrial Laser Scanner (TLS) and Unmanned Aerial Vehicle (UAV) methods in the production area of PT FAD, Berau Regency, East Kalimantan. A quantitative descriptive approach was employed, involving field data acquisition, three-dimensional modeling, and volume analysis using specialized software. The results show that ROM volume measured with TLS was 1,407.669 lcm, while UAV produced 1,387.357 lcm, with a difference of 20.312 lcm or 1.45%. This deviation is within the ASTM D6172-98 tolerance limit (<2%), indicating that both methods are valid. Although TLS offers higher accuracy, UAV is more effective and efficient in terms of measurement time, making it a reliable alternative for modern mining monitoring. This study provides practical insights for the mining industry in selecting ROM volume measurement methods that are not only accurate but also efficient in supporting sustainable operations and data-driven decision-making.

It very important for business administration to e carried out in a structured and consistent manners in its execution. If it is not done well, it will become negative feedback in the course of the business and will reduce competitiveness. The activity of administraive tidiness is used for continuous improvement of the administrative system by adjusting the availale resouces, including human resources and technology. This community service aims to provide insights, knowledge, and skills in the implementation of administrative therapy activities through socialization, training and guidance on administrative writing, particularly in production and warehousing. The implementation leads to improved efficiency and effectiveness in working time, tidiness and ease of work. In addition, it makes coordination between employees and departements easier, while accountability is achieved.

Micro, Small, and Medium Enterprises (MSMEs) are strategic sectors in the Indonesian economy, but often face challenges in efficient and data-driven production management. This article highlights the urgency of the Real Work Lecture (KKN) program as a form of student service in assisting MSMEs, especially in optimizing the production of snacks typical of Tebing Syahbandar. This research aims to optimize the production output of the Untir-untir Titik Factory with an Integer Linear Programming (ILP) approach using the Branch and Bound algorithm. Primary data is obtained through interviews and production documentation, including product type, raw material needs, operational costs, selling prices, and profit margins. The initial analysis was carried out using the simplex method using POM QM software to obtain a linear solution, which was then refined with the Branch and Bound algorithm so that the results were in the form of integers. The results of the study showed that the optimal solution was achieved by producing 25 bales of kolong-kounder and not producing other types of snacks, resulting in a profit of Rp1,650,000 per day. These findings show that the ILP approach with Branch and Bound is able to significantly increase the efficiency and profitability of MSMEs. In addition, this method can be used as a basis for quantitative-based production decision-making. This research also emphasizes the strategic role of KKN in technology transfer and real solution-based assistance for MSME actors in the region, thereby supporting the sustainable strengthening of the local economy.

In manufacturing industries, machining processes play a critical role in ensuring product quality, precision, and production efficiency. However, in the production of swing arm parts, the machining process has been identified as a bottleneck due to its non-optimal cycle time. One of the main issues contributing to this inefficiency is the disorganized handling of circlip inner parts. These components are often scattered without a designated placement system, which creates significant difficulties for operators when retrieving and installing circlips onto the swing arm. Such abnormalities disrupt workflow continuity, extend production time, and reduce overall productivity. To address this challenge, a circlip feeder machine was designed as a supporting device to assist operators and streamline the machining process. The design emphasizes efficiency, integration, and systematic operation by utilizing readily available workshop materials. The developed feeder machine is equipped with a robust frame construction and has a storage dimension capable of accommodating up to 200 circlips. In addition, mechanical analysis demonstrates that the feeder structure can withstand a maximum applied force of 31,475 N, ensuring durability and reliability during operation. The introduction of this circlip feeder machine directly impacts the production process by reducing operator workload, minimizing delays caused by disorganized parts, and ensuring faster and more accurate installation of circlips. Consequently, the overall machining cycle time is shortened, thereby improving production flow and enhancing the efficiency of swing arm part manufacturing. Beyond immediate time savings, the use of the feeder machine contributes to better resource utilization, reduced ergonomic strain on operators, and improved consistency in product quality. This study highlights the significance of simple yet effective mechanical innovations in overcoming production bottlenecks and optimizing manufacturing processes in automotive component industries.

Reservoir heterogeneity has long been recognized as a critical factor influencing the efficiency of enhanced oil recovery (EOR) methods. Among the techniques applied, cyclic waterflooding is considered one of the promising approaches due to its relatively simple operational design and potential to improve sweep efficiency. This method involves alternating water injection in specific cycles to mobilize trapped oil and redistribute reservoir pressure. However, the variation in geological properties such as porosity, permeability, and fluid saturation creates challenges in achieving uniform displacement, especially in reservoirs with high heterogeneity. Understanding the role of heterogeneity is therefore crucial for optimizing cyclic waterflooding applications. This study applies a literature review approach by synthesizing findings from previous experimental and field studies that evaluated cyclic waterflooding under different reservoir conditions. The analysis compares the performance of cyclic water injection periods across reservoirs characterized by varying levels of heterogeneity. Parameters such as injection rate, water breakthrough time, and oil recovery factor were considered in evaluating the effectiveness of this method. The results highlight that reservoirs with high heterogeneity often experience uneven fluid distribution, leading to early water breakthrough and reduced oil recovery. In contrast, reservoirs with relatively low heterogeneity tend to respond better to cyclic waterflooding, resulting in improved sweep efficiency and higher incremental recovery. Moreover, the optimization of cycle timing and water injection intervals appears to significantly mitigate the negative effects of heterogeneity. In conclusion, the study emphasizes that reservoir heterogeneity plays a decisive role in determining the success of cyclic waterflooding. Tailoring injection strategies based on geological variability is essential to maximize recovery efficiency. Future research should focus on integrating advanced reservoir characterization techniques with adaptive cyclic flooding models to further enhance oil production outcomes.

This study aims to analyze the application of the full costing method in determining the cost of goods sold at a Sukoharjo Village-Owned Enterprise (BUMDes). The full costing method is an approach that assigns all production costs, both fixed and variable, to the product. It is expected to provide more accurate cost information than the traditional method currently used by BUMDes. This study used a qualitative descriptive approach, using a case study of a BUMDes Sukoharjo that produces traditional foods such as clorot, geblek, and lanting. Data collection techniques included interviews, observation, and documentation.The results indicate that the method currently used by BUMDes Sukoharjo does not capture all production costs, particularly equipment depreciation and other fixed overhead. Calculating the cost of goods sold using the full costing method yields a higher value than the previous method. This difference occurs because the full costing method comprehensively considers all cost elements, providing a more accurate basis for setting selling prices. By implementing the full costing method, BUMDes can improve cost management efficiency and obtain more accurate information for managerial decision-making. Furthermore, applying the full costing method enables BUMDes to better understand the impact of fixed costs on the overall profitability of their products. By factoring in all costs, including overheads and depreciation, BUMDes can make more informed decisions regarding pricing strategies and resource allocation. This method also allows for greater transparency in cost structures, which is essential for effective financial planning and budgeting. Ultimately, the full costing method will contribute to improved financial sustainability and long-term profitability for BUMDes Sukoharjo, helping them navigate challenges in the competitive market of traditional food production.

The Unnoni Weaving Center is a community-led, small and medium-sized enterprise (SME) development center for traditional weaving. Despite its significant potential, many entrepreneurs in this center face challenges in determining appropriate product prices. They typically rely solely on intuition or follow market prices without considering all production cost components, resulting in very small profit margins and even the risk of incurring losses. In response to these challenges, this community service program was designed to improve the ability of SMEs to determine more rational, measurable, and profitable selling prices through comprehensive and applicable training in production cost calculations. The methods employed included outreach, workshops, intensive mentoring, and hands-on simulations on pricing based on real costs and reasonable margins. The program was conducted in two sessions at the Unnoni Weaving Center Hall, involving 25 local weaving entrepreneurs. The results showed significant improvement, with participants' understanding of identifying production cost components increasing by 76%, while approximately 80% successfully conducted simulations for determining selling prices, taking into account raw materials, labor, overhead costs, and profit margins. The tangible impact of this activity is seen in increased business literacy, more systematic calculation skills, and the confidence of SMEs in determining prices and negotiating with consumers and business partners. Furthermore, this activity is expected to be a starting point for the implementation of a simple financial recording system, increased operational efficiency, and the development of a branding strategy for Unnoni woven products so they can compete more professionally, sustainably, and with high competitiveness in both local and global markets.

The production process of graphite glass at ABC faces challenges in the form of waste that has an impact on low operational efficiency. Waste in production activities can affect the quality, cost, and timeliness of product completion. This study aims to identify the most dominant types of waste and provide relevant improvement recommendations to improve production efficiency. The method used is Value Stream Mapping (VSM), a visual approach that maps the flow of the production process from raw materials to final products. The research stage is carried out through direct observation on the production floor, time study, interviews with employees, and documentation of production activities. The results of the analysis show that the most dominant form of waste is overprocessing, which is a repetitive activity that does not add value to the product. This causes longer production cycle times and reduces the effectiveness of resource use. To overcome this, this study provides several recommendations, including: combining production processes that have similar functions, redesigning workflows to make them more concise, and eliminating activities that do not provide added value. The implementation of this improvement has proven to be effective by increasing the Process Cycle Efficiency (PCE) value from 45% to 67%. The increase in PCE reflects that the production process has become more efficient, the workflow is smoother, and the rate of waste has decreased significantly. In addition, the results of this study also confirm that the application of the VSM method can be a strategic solution in identifying sources of inefficiency, designing continuous improvements, and increasing the competitiveness of companies. Thus, the company is expected to continue to evaluate, control, innovate, and improve technology so that efficiency achievements can be maintained, expanded, and improved consistently and sustainably in the future.

Indonesia has a rich cultural heritage, one of which is batik, which has become a national cultural heritage and is recognized by UNESCO as a world intangible cultural heritage. Along with the development of digital technology and the increasingly dynamic needs of society, innovations in the form of digital batik have emerged, opening new opportunities in the preservation and development of traditional batik motifs. Digital batik not only allows efficiency in the production process but also expands the reach of creative expression through the exploration of new, more modern forms, colors, and media. This creative research aims to explore the shape and color of the female beetle (Coccinellidae) as inspiration in creating digital batik motifs that are then applied to mugs using digital printing techniques. The method used is exploratory with an artistic practice approach, involving stages ranging from visual concept design, digital sketching, color exploration, to the printing process on ceramic media. The design process was carried out digitally using the Ibis Paint application on a mobile device, which demonstrates that batik works can be created flexibly with the help of simple technology. The results of this creation are 15 digital batik works with the visual character of the female beetle that have been artistically modified without losing their distinctive shape and striking color. Each design measures 20 x 8 cm and is printed on a cylindrical mug with a curved surface. This research demonstrates that natural elements such as insects can be a rich source of aesthetic inspiration for developing contemporary batik motifs. Furthermore, this work demonstrates that modern technology can play a crucial role in maintaining the relevance and appeal of traditional arts like batik in the era of globalization and digitalization.

Pesidi Village, located in Grabag Subdistrict, Magelang Regency, is a highland region with promising potential in agriculture and livestock, particularly sheep farming. However, one of the major challenges faced by local farmers is the limited availability of forage during the dry season, coupled with the low utilization of agricultural by-products such as rice straw. These constraints often hinder livestock productivity and pose risks to feed security. To address this issue, a community service program was conducted with the aim of introducing and demonstrating local-based feed processing technologies, including silage, ammoniation, and Urea Mineral Block (UMB) production. The activity was implemented in several stages: problem identification, socialization, education, training, and monitoring of farmer implementation. Through this participatory approach, farmers were given hands-on training and practical guidance on processing alternative feed sources to ensure the availability of nutritious and sustainable livestock feed. The results showed that farmers began adopting UMB as a feed supplement due to its practicality and visible benefits in maintaining livestock health and productivity. However, silage and ammoniation methods were not yet widely adopted, mainly due to limited experience, lack of supporting equipment, and the perception that the processes were relatively complex. Despite these challenges, the program succeeded in raising farmer awareness of the importance of feed diversification and the optimization of agricultural waste. The training provided valuable insights into how the integration of silage, ammoniation, and UMB can increase feed efficiency, reduce dependency on fresh forage, and support sustainable livestock management. The implementation of these three technologies holds significant potential to enhance sheep farming productivity in rural highland communities, while simultaneously strengthening food security and supporting environmentally friendly agricultural practices.

The agricultural sector plays a crucial role in fulfilling food needs, but it continues to face several challenges, including limited land, climate change, and the need for more cost-efficient production methods. To address these challenges, the application of Artificial Intelligence of Things (AIoT) technology emerges as a promising solution to enhance productivity and efficiency in farm management. AIoT technology integrates artificial intelligence (AI) and the Internet of Things (IoT), enabling smarter decision-making, automation, and real-time data analysis in agricultural practices. This community service activity aimed to provide AIoT technology training to the Satria Tani Hanggawana Farmers' Group in Kalisapu Village, Slawi Sub-district, Tegal Regency, focusing on premium melon cultivation. The methods used in the activity included presentations on relevant materials, an introduction to AI and IoT-based Smart Farming technology, hands-on practice in a greenhouse, and interactive discussions. These methods were designed to equip participants with practical knowledge about integrating AIoT technology into their agricultural operations, enabling them to apply it directly to melon cultivation. The results of the activity showed a significant increase in the participants' understanding of agribusiness management, basic bookkeeping practices, and the application of AIoT in melon cultivation. The participants exhibited high enthusiasm, actively engaging in discussions and successfully performing practical exercises. This training was effective in improving farmers' knowledge and motivating them to adopt AIoT technology in their farming operations. The program has been instrumental in encouraging the use of smart farming techniques, which can lead to more efficient and sustainable farming practices. It is recommended that ongoing support, including follow-up activities and further training, be provided to ensure the sustainability of the technology implementation and continue to improve local food security

UD. Indokarya Brass is a company engaged in the brass handicraft industry with its main products being door handles and bells. The main raw materials used in the production process include brass, copper, tin, and aluminum, which are obtained from suppliers both within and outside the city. On average, raw materials are received weekly with quantities of 50–100 kg of brass, 7–10 kg of copper, 10–15 kg of tin, and 3–5 kg of aluminum. In addition, the company also uses additional materials in the form of thinner and epoxy purchased from nearby hardware stores with less frequent purchases, namely 5–10 liters of thinner every month and around 5 kg of epoxy every two months. To date, the company has not had a structured policy for procurement and control of raw material inventory. This condition results in excess inventory of several types of raw materials which actually incurs high costs, both in terms of storage costs and warehouse maintenance costs. This excess inventory ultimately has an impact on reduced efficiency and decreased company profits. This study was conducted to analyze the existing inventory system and compare the company's current policy with a proposed method for more optimal inventory control. The calculation results show that the proposed method is able to provide significant inventory cost savings, namely 83.25% in brass raw materials, 15.28% in copper, 14.6% in tin, 43.37% in aluminum, 4.66% in epoxy, 4.2% in thinner, and 40.7% in other raw materials. Thus, the implementation of the right inventory control method can improve operational efficiency and help companies reduce cost burdens, so that profits can be more optimal.

This study aims to analyze the process of preparing operational budgets in micro, small, and medium enterprises (MSMEs) of Pempek Love Palembang, which are engaged in the culinary sector typical of South Sumatra. Pempek Love Palembang is one of the business actors that plays a role in maintaining culinary traditions while contributing to the local economy. The research approach used is quantitative descriptive, with data collection techniques through direct interviews with business owners. Interviews are focused on operational activities that cover all stages of production to sales. The scope of analysis includes the preparation of various budget components, including sales budgets, production and inventory costs, raw material budgets, direct labor budgets, overhead costs, operational costs, cost of goods sold (COGS), and profit and loss budgets. Based on the findings, it is known that Pempek Love Palembang has not prepared a budget systematically and well documented. This is due to the limited knowledge of owners and employees about the concept of budget planning, so that the financial management process runs less than optimally. The absence of a structured budget makes it difficult to evaluate performance in a measurable manner and limits the ability of businesses to project profits accurately. This study confirms that the implementation of a good operational budget is not only beneficial for setting clear targets, but also serves as a cost control tool and a basis for strategic decision-making. With proper budget planning, MSMEs such as Pempek Love Palembang can increase efficiency, maintain financial stability, and expand business development opportunities in the future. The recommendation of this study is simple financial management training for MSME actors to be able to prepare budgets independently, accurately, and sustainably for more sustainable and stable business growth.

The rapid development of the smart city concept encourages the need for energy management that is more efficient, sustainable and adaptive to the needs of modern urban communities. In this context, renewable energy is the main solution to reduce dependence on fossil energy sources that are limited and pollute the environment. This research aims to optimize the utilization of renewable energy in smart cities by integrating Big Data technology and Decision Support Systems (DSS). The approach used in this research is a case study and system modeling method, which involves collecting energy data from various sources such as IoT sensors, weather stations, and energy distribution systems in real-time. The data is then analyzed using Big Data Analytics techniques to identify energy consumption patterns, potential renewable energy production, and peak load predictions. Furthermore, a decision support system was designed to assist policy makers and city managers in determining optimal energy distribution and usage strategies based on the available data and simulations. The results show that the integration of Big Data and DSS is able to increase the efficiency of renewable energy utilization up to 25% compared to conventional systems. In addition, the system is also able to dynamically respond to changing conditions and provide more accurate and adaptive decision recommendations. These findings indicate that the synergy between data technology and decision support systems plays a strategic role in creating sustainable and environmentally sound smart cities.

The production of pharmaceutical sterile products requires strict procedures to minimize the risk of microbial, particulate and pyrogen contamination that can be harmful to the user's health. The selection of the right sterilization method is the key to achieving the desired stability of the final product. Filtration sterilization is one of the oldest methods used for pharmaceutical sterile products. There are two types of feed flow in the method, namely through flow filtration and tangential flow filtration. This review article is prepared through literature search and download of national or international journals with inclusion or exclusion criteria that have been set. Literature sources are accessed online from various sites such as Google Scholar and Pubmed in the range of 2014-2024. The keywords used for journal searches are sterilization, through flow filtration, and tangential flow filtration. This review article reviews and compares the two methods to understand the differences, mechanism of action, and research objectives based on the review article on membrane filtration sterilization. This review aims to provide a better insight into the advantages and disadvantages of each membrane filtration sterilization method, as well as guidance in choosing the appropriate method based on the characteristics of the product to be sterilized. The results showed that through flow filtration is more commonly used in small volume and batch processes because of its simple design, but has limitations in reducing membrane fouling. In contrast, tangential flow filtration allows for continuous processing of larger volumes, with the advantage of minimizing particle build-up on the membrane surface, thus extending membrane life. The choice of method is also influenced by factors such as particle size, viscosity of the solution, sensitivity to heat, as well as operating costs. An in-depth understanding of the Working Principle and application of each method is essential for the pharmaceutical industry to ensure the quality, safety and efficiency of the production process. Thus, this review is expected to be a reference for researchers and practitioners in determining the optimal filtration sterilization strategy according to product needs.

This study aims to evaluate the effectiveness of current asset management, specifically cash, receivables, and inventory, and its impact on a company's ability to generate profits. The study focused on companies in the automotive sector listed on the Indonesia Stock Exchange (IDX) from 2020 to 2023. The research approach used a quantitative method with secondary data sourced from annual financial reports. The study sample included 11 companies, resulting in a total of 44 observational data sets over four years. Data analysis was performed using SPSS version 25 software to examine the relationships and influences between the study variables. The test results showed that cash management did not significantly influence profitability. This indicates that the amount of available cash does not always correlate with profit, possibly because cash funds are not optimally utilized in productive activities. Conversely, receivables management showed a negative correlation with profitability. This finding suggests that high receivables can burden cash flow and reduce a company's ability to generate profits. Meanwhile, inventory management has a positive and significant impact on profitability, indicating that good inventory control can support smooth production and sales, thereby increasing profits. Together, these three variables explained 68.4% of the variation in company profitability, while the remaining 31.6% was influenced by factors outside the model, such as operational efficiency, cost structure, and marketing strategy. These findings provide insights for automotive company management to prioritize inventory management and review cash and receivables policies to optimize financial performance.

This study aims to analyze the effect of variations in screw conveyor speed and cutting blade on an automatic meatball molding machine in producing meatballs weighing between 15 and 20 grams. The research method used a design of experiments (DOE) approach with a factorial design, followed by a two-way ANOVA analysis to test the effect of each factor and their interactions. The screw conveyor speed variations used were 160 RPM, 140 RPM, and 124 RPM, while the cutting blade speed was varied at 224 RPM, 186 RPM, and 160 RPM. The speed variations were obtained by adjusting the pulley ratio on the machine. The testing process was carried out by molding meatballs using a combination of these speed variations, then boiling them until they float to ensure doneness. After that, the mass of each meatball was weighed with a precision scale. The weighing data were processed using Microsoft Excel and Minitab 21 software to obtain accurate statistical analysis. The results showed that increasing the screw conveyor speed tended to increase the meatball mass, while increasing the cutting blade speed actually decreased the mass of the meatballs produced. The interaction between screw conveyor speed and cutting knife speed was statistically significant with a p-value ≤ 0.05, indicating that the combination of the two plays an important role in determining the final meatball mass. Through Response Optimization analysis, the most optimal combination for producing meatballs with a mass in the range of 15–20 grams is a screw conveyor speed of 124 RPM and a cutting knife speed of 160 RPM. This setting can be achieved by using pulleys with diameters of 114.3 mm (4.5 inches) and 88.9 mm (3.5 inches). These findings are expected to be a reference for meatball industry players, especially MSMEs, in increasing production efficiency and maintaining product size consistency.