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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.  

Water heating systems on ships play a crucial role in supporting crew comfort and operations. However, conventional systems generally operate continuously without automatic control, resulting in energy waste and high operational costs. This situation drives the need for innovation in more efficient and environmentally friendly water heater designs. This research aims to design and implement an automated water heater temperature control system based on an ESP32 microcontroller with on/off control and the use of paraffin wax as a latent heat storage medium. This design is expected to improve energy efficiency while reducing the operational costs of water heaters on ships. The research methodology includes system design, hardware assembly, and performance testing, both static and dynamic. Testing was conducted to evaluate temperature stability and energy efficiency in system conditions with and without the use of paraffin wax. The results showed that paraffin wax improved water temperature stability while reducing the frequency of heater activation. In a 24-hour test, the system without paraffin wax recorded a heater operating time of 15 hours, consuming 8.85 kWh of electricity and costing Rp11,965.20. In contrast, the Paraffin Wax system only requires 10 hours of heater operation, consumes 5.90 kWh, and costs Rp7,976.80. This demonstrates energy savings of 2.95 kWh and a cost efficiency of up to 58%. Therefore, the ESP32-based water heater automation system and heat storage using Paraffin Wax are proven to be more energy-efficient, cost-effective, and have the potential to be an innovative and environmentally friendly solution for ship operational needs.

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.

This study is motivated by the downstream Teh Walini industry’s reliance on third-party logistics (3PL) services for product distribution, which restricts the company’s control over several key aspects, including logistics costs, delivery speed, routing efficiency, and product handling quality. The primary objective of this research is to analyze and compare distribution costs between outsourced logistics and self-managed delivery, and to evaluate the potential cost efficiency of an independently operated shipping system. A descriptive comparative quantitative method is employed, incorporating movement generation analysis, distribution spread mapping, and Vehicle Operating Cost (VOC) calculations to estimate the cost implications of self-shipping. Data were obtained through company documentation and analyzed using multiple linear regression involving six major distribution points. The results reveal that shipment volume significantly influences movement generation, with Waingapu, Makassar, and Padang identified as the dominant distribution destinations. The cost comparison analysis demonstrates that self-managed delivery is more cost-effective than third-party logistics services, making it a more viable long-term option. These findings suggest that transitioning to a self-delivery system could improve cost control and logistical efficiency for the company. However, this strategy should be implemented gradually, supported by regular updates on operational cost data and proactive management of external factors that could impact distribution performance. The study concludes by recommending broader coverage and the inclusion of additional relevant variables in future research to further validate and enhance decision-making related to distribution strategies. A well-informed shift toward internal logistics could ultimately contribute to greater competitiveness and sustainability in the company’s distribution operations

Increasing business competition requires companies to consistently improve quality and operational efficiency. This study aims to identify and reduce non-value added activities in the procurement process at Distributor X, a company engaged in the distribution of instant cooking spices. Common issues include expired goods (49.05%), damaged packaging (18.78%), and product mismatches (32.17%). The Lean Six Sigma approach with the DMAIC (Define, Measure, Analyze, Improve, Control) method is used to address these problems. Measurement results show an average DPMO value of 10,076.58 and a sigma level of 3.82, which are still far below the Six Sigma quality standard. Improvement proposals include the implementation of barcode/RFID systems, FIFO inventory management, higher-quality packaging materials, and the use of unique product codes. In the Control phase, monitoring is carried out through an ERP system and the establishment of structured SOPs to support distribution oversight. This approach demonstrates potential in reducing defect rates and improving the overall quality of the procurement process.

Distribution is an important aspect that affects the operational efficiency of a company, especially in terms of goods delivery. This study aims to develop an optimization model for LPG gas distribution routes using Excel Solver based on geographic coordinate conversion. In this study, the method used includes converting geographic coordinates from decimal to Degree-Minute-Second (DMS) format, followed by conversion to kilometers to form a more accurate distance matrix. The optimization model was built using the Capacitated Vehicle Routing Problem (CVRP) approach, which takes into account vehicle capacity constraints (a maximum of 560 cylinders per truck) and the limited number of available fleets, which is only one truck. The results show that coordinate conversion produces high accuracy in calculating distances between distribution locations. By using Excel Solver, the optimization solution successfully minimizes the total distance traveled compared to the conventional route, where distribution is carried out more evenly to 57 scattered LPG base locations. The addition of Solver Parameters Evolutionary and All Different constraints proved effective in avoiding duplication of visits and producing optimal distribution routes. This solution not only improves distribution time and cost efficiency, but also improves service to customers by reducing delivery delays. The success of this optimization model is expected to be implemented by other distribution companies to improve their operational performance. This study also highlights the importance of selecting the right software to aid the distribution optimization process. Excel Solver, despite its simplicity, proved highly effective in solving complex distribution routing problems, especially when combined with coordinate conversion techniques that yield more accurate distances. Furthermore, the application of the CVRP method enabled more efficient decision-making in determining distribution routes, taking into account vehicle capacity and fleet limitations.

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 the financial performance differences of Bank Syariah Indonesia before and after the merger based on three key ratios: Financing to Deposit Ratio (FDR), Operational Expenses to Operating Income (BOPO), and Return on Assets (ROA). A comparative quantitative approach was applied using financial statement data from the 2017–2024 period, analyzed with normality tests and paired sample t-tests. The normality test results indicate that all data are normally distributed. The paired sample t-test reveals no significant difference in the FDR ratio before and after the merger, while significant differences are found in BOPO and ROA. These findings indicate that the merger affected the efficiency and profitability of the bank, but not directly the effectiveness of fund distribution. The study implies that Bank Syariah Indonesia needs to strengthen operational efficiency and asset management post-merger. Future researchers are encouraged to include non-financial variables and apply qualitative approaches to gain more comprehensive insights.

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

This article discusses the importance of job analysis as a fundamental component of human resource management (HRM) within Islamic educational institutions in Indonesia. Using a qualitative approach based on a literature review, the study highlights the strategic role of job analysis in developing job descriptions, job specifications, and the professional development of human resources. Job analysis serves not only as an administrative tool but also contributes to institutional efficiency, the enhancement of educational quality, and the readiness of institutions to face global challenges and technological advancements. By systematically identifying and evaluating job roles and responsibilities, institutions can align their HR practices with organizational goals and the evolving demands of the educational sector. The application of analytical models such as the Position Analysis Questionnaire (PAQ), Functional Job Analysis (FJA), and the Job Characteristics Model ensures that job analysis is comprehensive and tailored to the specific needs of the institution. The article emphasizes that a results-oriented approach is more relevant for modern educational institutions, particularly those within Islamic settings. The findings indicate that the optimal implementation of job analysis can strengthen the governance of Islamic educational institutions, enhance their operational effectiveness, and improve the competitiveness of their human resources in the global education landscapes.

The operational department at PT. Baruna Mitra Segara Lines Bandar Lampung plays a crucial role in ensuring the timely departure of ships. This study examines how the department monitors ship departures to ensure they occur on time and follow established procedures. The research uses a qualitative case study approach, collecting data through observation and documentation. The findings show that active involvement from the operational department helps reduce technical and administrative issues that may delay departures. Improving human resources and operational systems is essential to guarantee smooth operations. The operational department is responsible for coordinating between departments, checking ship readiness, and monitoring schedules. The department's effectiveness significantly reduces delays and enhances customer satisfaction. The study also highlights that the accuracy of operational work impacts the efficiency, safety, and reliability of the shipping process. Strengthening the monitoring system and improving human resource quality are critical to optimizing the department’s role. However, challenges such as limited resources and outdated information systems need to be addressed to improve performance. This research aims to provide insights for PT. Baruna Mitra Segara Lines management to enhance the operational process of ship departures.

The use of BRIMEN (BRI Document Management System) in digital document processing operations during internship activities at the Medan Regional Office of PT Bank Rakyat Indonesia (Persero) Tbk. is the main focus of this article. The objective of this study is to understand how the BRIMEN system contributes to the storage, retrieval, and classification of documents, particularly in relation to credit document management. This system was introduced to address common issues found in manual archiving, such as limited storage space, difficulties in document retrieval, and the risk of errors in preserving clients’ physical records. The research employed a descriptive qualitative approach through direct observation and active participation in daily workflows. The findings indicate that BRIMEN significantly improves operational efficiency by providing a more systematic and secure digitalization procedure for banking documents. The system not only reduces the risk of loss or damage to physical archives but also accelerates the process of data retrieval when required by work units. Through its classification and tracking features, BRIMEN ensures better consistency between digital data and physical documents, although several technical challenges remain, such as restricted access to storage rooms and difficulties in scanning older or non-standard documents. Overall, the results highlight the importance of implementing a well-structured digital document management system to support the smooth operation of modern banking institutions. BRIMEN represents a tangible step in BRI’s digital transformation, strengthening data security while simultaneously improving the quality of credit services delivered to customers. With continuous improvement, this system has the potential to serve as a model for digital document management that can be more widely adopted across Indonesia’s banking sector.

Efficient operations of PT PLN, as a vital electricity provider, heavily rely on effective service management, including customer data collection and payment processing. Employee performance supervision is crucial to ensure optimal results and customer satisfaction, given that traditional manual systems often suffer from inefficiencies, inaccuracies, and delays. This research aims to develop and implement a web-based performance monitoring system for electricity bill delivery officers to enhance operational efficiency and accountability at PT PLN. The Waterfall method was adopted as a systematic development framework, encompassing stages of requirements analysis, design using Unified Modeling Language (UML) such as use case diagrams and activity diagrams, implementation with PHP and MySQL, and black box testing to validate system functionality. The results of the black box testing indicate that all main functions of the system, including user authentication, user data management, uploading of daily reports and supporting files by officers, and the administrator's ability to monitor and review reports, function as expected. The successful implementation of this system indicates its capability to overcome the limitations of manual methods and provide real-time visibility into the performance of field officers. Thus, this web-based monitoring system not only contributes to improving data accuracy and operational efficiency at PT PLN but also supports more informative and strategic managerial decision-making, aligning with digital transformation initiatives in the energy sector

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.

Currently, the use of data mining technology has become essential in enhancing business management efficiency, including in the trending coffee shop industry. Data mining allows business owners to analyze sales information in depth, enabling more accurate decision-making regarding inventory management, promotions, and sales strategies. This study aims to implement the Apriori algorithm to analyze sales data at Menrabic Coffee Shop. The Apriori algorithm is used to discover association patterns or relationships between products frequently purchased together by customers, which can assist management in providing inventory that aligns with customer preferences. The research method illustrates the detailed implementation process of the Apriori algorithm, starting from sales data collection, data cleaning, programming, and analysis of the results. The implementation uses web programming languages such as HTML, CSS, MySQL, and JavaScript, while back-end logic is programmed with PHP. The results of applying this algorithm reveal the most popular sales patterns among customers, providing valuable insights for management to improve operational performance and customer satisfaction. Therefore, this study demonstrates that applying data mining with the Apriori algorithm can be an effective tool for understanding consumer behavior and supporting data-driven decision-making at Menrabic Coffee Shop. By utilizing these insights, management can optimize inventory, enhance sales strategies, and ultimately increase overall business efficiency.

This study aims to analyze the influence of company characteristics, including Current Ratio, Debt to Asset Ratio, and Company Size, on Financial Performance. The population studied consists of companies in the F& B sector listed on the IDX during the period 2020-2024. The sample in this study was selected using the purposive sampling method. Out of the 24 companies listed in the sector, 3 companies were eliminated because they did not meet the established criteria, resulting in a final sample size of 21 companies. To test the influence of independent variables on the dependent variable, the multiple linear regression analysis technique was applied. The research results show that Company Size has a positive and significant effect on financial performance, while the Debt to Asset Ratio has a negative and significant effect on financial performance. On the other hand, the Current Ratio does not show a significant effect on financial performance. However, the Current Ratio does not appear to significantly affect financial performance. While it is a measure of liquidity, the results of this study suggest that liquidity alone does not guarantee profitability or financial success. It is possible that other factors, such as market conditions or management practices, may play a more dominant role in influencing financial performance. Overall, this research emphasizes the need for companies in the F&B sector to carefully manage their debt levels and consider the benefits of growing their company size to improve financial performance. Future studies could explore the role of other factors, such as operational efficiency and market conditions, to gain a more comprehensive understanding of what drives financial success in the industry.

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.

Efficient management of patient queues is essential in healthcare systems to ensure timely care, optimize resource utilization, and enhance patient satisfaction. Mathematical programming, particularly when applied in conjunction with queuing theory and optimization models, provides a rigorous framework for analyzing and improving healthcare service delivery. This approach involves modeling arrivals and service processes, applying queuing models (such as single-server, multi-server, and priority queues), and formulating optimization objectives—often to minimize total costs, patient waiting times, or resource idling. Recent research demonstrates that combining queuing theory with mixed-integer programming and simulation techniques enables healthcare managers to allocate resources dynamically, set staffing levels, and assign priorities among different patient categories. For example, the use of mixed-integer programming can determine the optimal number of servers, beds, and service rates based on patient flow and priority needs, striking a balance between reducing waiting times for critical cases and controlling operational costs. These mathematical models also account for practical constraints and stochastic variability inherent in clinical settings. Applications span emergency departments, outpatient clinics, and even pharmacy and blood service centers—showing significant improvements in system efficiency, reduced patient wait times, and enhanced overall care quality. Thus, mathematical programming is a powerful decision-support tool for queue management, offering evidence-based strategies to address congestion and resource allocation challenges in complex healthcare environments.

This study analyzes the effectiveness of implementing predictive maintenance (PdM) on the final drive components of the Komatsu PC200-8 unit at PT. Antareja Mahada Makmur, Site PT. Multi Harapan Utama, East Kalimantan, in an effort to reduce downtime and operational losses. Before the implementation of PdM in 2022, there were 12 repair cases for the final drive with a total downtime of 772.1 hours, repair costs amounting to IDR 310.6 million, rental income loss of IDR 208.03 million, and total losses of IDR 518.63 million. In 2023, during the PdM transition phase, the number of cases decreased to 4, with a total loss of IDR 252.05 million, although downtime remained high (714.6 hours) due to the limited scope of PdM implementation on certain units and components. In 2024, with full PdM implementation, the number of repair cases decreased to 5, with total downtime of only 96 hours and losses of IDR 45.75 million. The cost of PdM implementation for the year was only IDR 21.9 million. As of July 2025, no further damage to the final drive has been recorded, demonstrating a significant improvement in equipment reliability. The reduction in total losses from 2022 to 2024 amounted to IDR 472.88 million, indicating PdM’s effectiveness in avoiding significant costs through condition monitoring methods such as oil analysis, magnetic plug rating, thermal inspection, and oil leak testing (floating seal). The findings of this study confirm that PdM is effective in reducing downtime, repair costs, and enhancing asset management in the mining sector. It also improves equipment reliability and overall operational efficiency, proving PdM to be a successful strategy in reducing losses, increasing productivity, and supporting the sustainability of company operations.

A company's financial performance is one of the main indicators in assessing the health and sustainability of a business entity's operations. Evaluation of financial performance is crucial, especially for large companies operating in strategic sectors such as telecommunications. PT. XL, as a telecommunications company listed on the Indonesia Stock Exchange, requires regular performance assessments to provide a clear picture of the effectiveness of its business strategy and its ability to generate profits. This study aims to analyze PT. XL's financial performance using a profitability ratio approach. The research method used is descriptive quantitative, utilizing secondary data sourced from the company's financial statements, including the balance sheet, income statement, and other financial statements for the 2021–2023 period. The profitability ratios analyzed include Net Profit Margin (NPM), Return on Assets (ROA), Return on Equity (ROE), Gross Profit Margin (GPM), and Earnings Per Share (EPS). These five ratios were chosen because they are able to describe the company's ability to generate profits, both in terms of sales, total assets, and shareholder equity. The analysis results indicate that PT. XL's financial performance during the study period is still less than optimal. This is reflected in the profitability ratio, which is below the average standard for the Indonesian telecommunications industry. This condition indicates that the company has not been able to optimally manage its resources to generate competitive profits. This finding has important implications, namely the need to evaluate financial management strategies, operational cost efficiency, and improve service quality to increase company profitability in the future. Therefore, this study confirms that profitability ratio analysis is a crucial instrument for assessing a company's financial condition and serves as a basis for formulating performance improvement strategies.