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Electricity service quality depends not only on physical network expansion but also on the availability of accurate, traceable, and spatially integrated asset data. This study aims to formulate an infrastructure inventory plan for electricity distribution networks as a basis for optimizing electricity services in Musi Rawas Regency, Indonesia. A descriptive-technical approach was applied using administrative maps, spatial planning documents, distribution network maps, feeder single-line diagrams, January 2026 customer data, bill of quantity documents for electricity and public street lighting, and the planned network drawing for Mandi Aur Village. The results show that 14 target districts served approximately 101,932 customers, consisting of 78,564 postpaid and 23,368 prepaid customers. Tugumulyo, Megang Sakti, Muara Kelingi, and Muara Lakitan represented the largest customer concentrations and should be prioritized for detailed asset verification. The proposed inventory object includes medium-voltage lines, low-voltage lines, poles, distribution transformers, protection equipment, public street lighting, panels, and operation-worthiness documents. The inventory database should include unique asset codes, coordinates, feeder identity, specifications, physical condition, photographs, operational status, and follow-up actions. Spatial inventory is expected to improve maintenance planning, outage response, public lighting management, safety control, and evidence-based network development.

Drug logistics management is a critical component of pharmaceutical services that ensures the availability, quality, safety, and rational use of medicines. Inadequate logistics management may lead to stock shortages, overstocking, increased operational costs, and disruptions in healthcare services. This study aimed to analyze the drug logistics management system at Altara Simalingkar Clinic, encompassing planning, budgeting, procurement, receiving, storage, distribution, utilization, recording and reporting, as well as monitoring and evaluation. This study employed a descriptive qualitative approach. Data were collected through in-depth interviews, observations, and documentation involving a pharmacy assistant technician as the key informant directly responsible for the daily technical operations of drug logistics management. Data were analyzed thematically by comparing interview findings, observations, and supporting documents. The results showed that the drug logistics management system at Altara Simalingkar Clinic generally complied with pharmaceutical logistics management principles. Drug planning was based on previous utilization data, disease patterns, and evaluations of fast-moving and slow-moving medicines. Storage practices implemented the First Expired First Out  method, while recording and reporting activities were supported by a pharmacy management information system. However, three structural challenges were identified: delays in drug delivery from distributors, limited storage capacity that does not meet WHO Good Storage Practice standards, and discrepancies between physical stock and administrative records arising from the dual manual-digital recording system. To enhance the effectiveness and sustainability of pharmaceutical services, it is recommended to diversify distributors for critical medicines, fully digitize inventory recording through barcode implementation, and optimize storage infrastructure in accordance with applicable regulatory standards.

The coal mining industry requires accurate stockpile volume measurements for inventory and production reporting. Conventional methods have limitations in accuracy, efficiency, and safety. This study compares the accuracy and efficiency of coal stockpile volume measurements using a Terrestrial Laser Scanner (TLS) Leica MS60 and an Unmanned Aerial Vehicle (UAV) DJI Matrice 4E, validated by the ASTM D6172-98 standard. Conducted on five Run of Mine (ROM) coal stockpiles covering 13,500 m² at PT XYZ, Lahat, South Sumatra, the TLS method used 43 scan positions, while the UAV employed 430 aerial images with specific flight parameters. Data were processed using Leica Infinity, Surpac, and Agisoft Metashape. The results showed volumes of 94,076 m³ (TLS) and 94,965 m³ (UAV), with a difference of 889 m³ (0.95%). Volume deviations ranged from 0.48% to 1.89%, with an average of 1.42%, all within the ASTM tolerance (<2%). Time efficiency analysis revealed that the UAV method required 200 minutes (3.33 hours), saving 63.3% (approximately 6.17 hours) compared to the TLS method (570 minutes). The largest efficiency gain occurred during field data acquisition, with an 85% reduction in time. This study confirms UAV photogrammetry as a valid, accurate, and efficient alternative for coal stockpile volume measurement in mining.

The management of ethical drug inventory is a crucial aspect of supporting the smooth delivery of healthcare services in hospitals. Improper management of ethical drugs can lead to stockouts or overstock, which results increased operational costs and the risk of drug expiration. This study aims to analyze the inventory control of ethical drugs at RSUD Inche Abdoel Moeis Samarinda using the Economic Order Quantity (EOQ), Safety Stock, and Reorder Point methods. The data used in this study are the consumption of ethical drugs during 2024, obtained from the hospital’s Pharmacy Installation. The data analysis method involves calculating ordering and holding costs, determining the optimal order quantity using EOQ, and calculating Safety Stock and ROP to maintain drug availability during lead time. The results of this study indicate that the application of the EOQ method provides a more optimal and efficient order quantity compared to previous policies. Furthermore, Safety Stock and ROP calculations assist the hospital in preventing ethical drug shortages and creating a more structured ordering schedule. Thus, the implementation of EOQ, Safety Stock and ROP methods can improve the efficiency of ethical drug inventory management while supporting the continuity of healthcare services at RSUD Inche Abdoel Moeis Samarinda.

This research aims to control the planning of inventory control of palm raw materials to obtain the optimal quantity of raw material orders at PT. Gruti Lestari Pratama in 2020. The method used in this research is the model of Period Order Quantity (POQ) method which is the development of the Economic Order Quantity (EOQ) method. The result of this research obtained an optimal order quantity using the POQ method in 2020 which is 7.563,08 tons. The frequency of ordering based on company policy is 314 times in a year, while using the POQ method the order frequency 23 times in a year. Where safety stock with POQ method of 2.702,50 tons and reorder point of 3.256,35 tons. Total inventory cost of palm raw material by using POQ method of Rp. 8.907.361.822 in a year. Overall, this study shows that the application of the POQ method in controlling palm oil raw material inventory at PT. Gruti Lestari Pratama provides optimal results in reducing order frequency, saving costs, and ensuring timely raw material availability. The results of this study can serve as a basis for the company to implement a more efficient and effective inventory control system, supporting smooth production at a more affordable cost.

Ineffective spare part inventory planning may lead to supply delays and reduced compliance with lead time supply key performance indicators (KPIs). This study aims to implement the Collaborative Planning, Forecasting, and Replenishment (CPFR) method in spare part inventory planning at PT XYZ and to compare lead time supply performance before and after the implementation of the CPFR method. This research utilizes spare part usage data from January to June 2025, focusing on fast-moving spare parts. Demand forecasting is conducted using an error forecasting approach with the moving average method. Forecast accuracy is evaluated using the Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). Furthermore, inventory planning is carried out through the calculation of safety stock and reorder point (ROP) as the basis for determining replenishment decisions. The results indicate that the simulated implementation of the CPFR method provides a more structured and anticipative inventory planning process. The comparison of performance before and after the application of CPFR shows an improvement in lead time supply compliance with the established KPIs. Therefore, the CPFR method has the potential to support improved spare part inventory planning performance at PT XYZ.

Drug stockouts in hospitals pose significant risks to service quality, patient safety, and operational efficiency. This study aimed to analyze how drug demand planning and procurement processes at Johar Baru Regional General Hospital contribute to stockout occurrences and to develop data-driven recommendations based on supply chain management principles. A qualitative descriptive design was employed using data triangulation. Data were collected through in-depth interviews with the Head of the Pharmacy Installation, procurement staff, and warehouse pharmacists, complemented by direct observation and analysis of 2024 planning and procurement documents. Thematic analysis was conducted with the support of NVivo software to identify patterns and relationships among key variables, including drug demand planning, procurement, and inventory management.Findings reveal that stockouts stem from interconnected weaknesses in planning accuracy, procurement coordination, and inventory control systems. Effective stock management depends not only on increasing supply but also on improving data quality, integrating inventory information systems with operational workflows, and enhancing cross-functional collaboration. Recommended strategies include implementing a minimum stock alert system integrated with the Hospital Management Information System (HMIS), strengthening standard operating procedures for stockout response and procurement confirmation, improving integration between HMIS, the National Formulary, and budgeting systems, and applying consumption based planning methods combined with ABC VEN analysis to optimize inventory control.

The lack of a systematic calculation approach makes it difficult for APR Nine to monitor fabric raw material inventory, resulting in raw material purchases still being based on habit and intuition. With a total inventory of 2,001 rolls and raw material usage of 1,803 rolls of fabric, there were seven times of excess stock and five times of shortage during the period of October 2024 to September 2025. The difference between the two was 198 rolls. This study uses the Economic Order Quantity (EOQ) method to analyze fabric raw material inventory control. This study uses a quantitative approach with descriptive analysis using data from the period of October 2024 to September 2025. The results of the study indicate that 1694 orders with an ordering frequency of 10 times, a safety stock of 29 rolls, and a reorder point of 35 rolls are the ideal quantities when using the Economic Order Quantity (EOQ) approach. Compared to the previous APR Nine approach, the application of the Economic Order Quantity (EOQ) method is more effective in reducing overall inventory costs from Rp. 5,011,949.35 to Rp. 4,508,824.67.

This study aims to analyze the effectiveness of raw material inventory control at the Kediri Wet Noodle business by comparing the traditional method with the Economic Order Quantity (EOQ) method. A descriptive quantitative approach was applied, utilizing EOQ, Safety Stock (SS), Re-order Point (ROP), and total inventory cost analysis. The results indicate that the traditional method leads to 24 purchase cycles per year with an inventory cost of IDR 4,320,000, without considering safety stock or re-order points. In contrast, the EOQ method shows an optimal purchase quantity of 1,421 sacks (35,525 Kg) with five purchase cycles per year, an inventory cost of IDR 574,455, a Safety Stock of 67 sacks (1,675 Kg), and a Re-order Point of 107 sacks (2,675 Kg). Therefore, the EOQ method reduces inventory costs by up to 86% compared to the traditional method. Nevertheless, its limitation lies in the exclusion of raw material shelf life and storage condition factors.

Measuring Liquefied Petroleum Gas (LPG) levels and inventory in storage tanks is a critical aspect of terminal operations, directly influencing safety, operational efficiency, and accurate stock management. The Integrated Terminal Palembang – Pulau Layang LPG Site has implemented a servo-type Automatic Tank Gauging (ATG) system, namely the Proservo NMS81, to provide precise and real-time volume measurements. Despite its operational importance, there remains a limited in-depth understanding of how this ATG system functions, particularly regarding the complete process from sensing LPG levels to converting them into accurate inventory data. This study aims to analyze the working mechanism of the Proservo NMS81 in measuring LPG height and generating digital stock data for monitoring purposes. The research method combines a literature review of the Proservo NMS81 technical datasheet and related scientific references with direct field observation (KSM-LP) at the LPG Pulau Layang site. The analysis covers the operating principle of the servo sensor, which relies on displacement measurement via a mechanical float and wire system; the analog-to-digital conversion process utilizing a 12-bit ADC to transform continuous signals into discrete digital values; the communication protocols employed, including HART and Modbus RS-485, for transmitting processed data to the control system; and the algorithmic data processing that converts tank level measurements into standardized inventory figures based on tank calibration tables and product density. The results of this study are expected to improve technical knowledge regarding servo-type ATG systems, enhance the accuracy and reliability of inventory monitoring, and contribute to more informed operational decision-making. Furthermore, the research findings are intended to serve as a valuable academic reference for the application of advanced instrumentation technology in the energy industry, supporting both professional practice and further scholarly exploration in the field.

Economic Order Quantity (EOQ) is one of the methods in inventory management used to determine the optimal order quantity to minimize total inventory costs, which include ordering costs and storage costs. This study aims to analyze the application of the EOQ model in managing inventory in a company. By using data on raw material usage, ordering costs, and storage costs, the results show that the application of EOQ can optimize the amount of purchases and order frequency more efficiently. The results of the analysis show that the application of the EOQ model contributes to reducing operational costs and increasing the effectiveness of stock management. Therefore, EOQ can be used as an appropriate inventory management strategy to support the efficiency and productivity of the company. Economic Order Quantity (EOQ) in controlling coffee inventory at the Suteki Medan Coffee Shop to minimize total inventory costs. The EOQ method is used to determine the optimal order quantity with the most efficient cost, as well as considering safety stock, reorder point, and total inventory cost.    

Economic Order Quantity (EOQ) is one of the methods in inventory management used to determine the optimal order quantity to minimize total inventory costs, which include ordering costs and storage costs. This study aims to analyze the application of the EOQ model in managing inventory in a company. By using data on raw material usage, ordering costs, and storage costs, the results show that the application of EOQ can optimize the amount of purchases and order frequency more efficiently. The results of the analysis show that the application of the EOQ model contributes to reducing operational costs and increasing the effectiveness of stock management. Therefore, EOQ can be used as an appropriate inventory management strategy to support the efficiency and productivity of the company. Economic Order Quantity (EOQ) in controlling coffee inventory at the Suteki Medan Coffee Shop to minimize total inventory costs. The EOQ method is used to determine the optimal order quantity with the most efficient cost, as well as considering safety stock, reorder point, and total inventory cost.  

Currently, MD Drafika faces challenges due to a lack of proper inventory management, such as safety stock regulations and reorder schedules. This has led to inventory levels that often fail to meet customer demand. The objective of this research is to optimize inventory costs at MD Drafika to enhance cost efficiency. This study employs a descriptive quantitative method, utilizing data collected through observation and interviews to explain the relevant aspects of the research object. The results of the research reveal an optimal order quantity and a reduction in inventory costs. Inventory optimization was achieved by adjusting safety stock levels and reorder points. The calculations for 2023 showed an optimal order quantity of 3,349 pieces, with four purchasing cycles within the period. The safety stock was determined to be 945 pieces, and the reorder point was 992 pieces. The cost difference between the EOQ method and the company’s current approach amounted to IDR 1,179,928.

In facing fluctuations in the demand for spare parts at PT. SUN STAR MOTOR SURABAYA to avoid shortages that could disrupt its business operations, the company must ensure it can meet customer demands for specific items or orders. This means the company will lose an opportunity to earn profits. Before applying Safety Stock, Reorder Point, Economic Order Quantity, Maximum Inventory, and Total Inventory Cost, the company frequently faced spare parts stock shortages. To solve this issue, Safety Stock, Reorder Point, Economic Order Quantity, Maximum Inventory, and Total Inventory Cost are applied to determine order quantity, order time, and inventory levels for reordering. The results from inventory calculations can help determine the optimal spare parts needs for the company.

Companies often face various obstacles related to managing raw material inventory to meet demand, one of which is Peuyeum Ketan Istimewa. Working in the food processing industry, of course, raw material inventory management needs to be planned optimally to avoid various risks that can harm the company. The Quantity Discount model is used to take advantage of cost savings provided by suppliers when purchases are made in large quantities, while other efforts that can help manage raw materials in a company are by knowing the safety stock and reorder point of raw materials and also forecasting demand to predict future demand. This study will use the Quantity Discount model which optimizes inventory levels by considering storage costs, ordering costs, and quantity discounts. The calculations carried out are also to find the value of the company's Safety Stock and Reorder Point. The results of this study indicate that the use of the Quantity Discount method can reduce total costs by Rp26,319,267/year, while forecasting using the seasonality method increases the accuracy of demand predictions, thus enabling more efficient inventory management. The implementation of this model is expected to provide a significant contribution to operational efficiency and cost reduction at Peuyeum Ketan Istimewa

Inventory control is a crucial element in supporting the smooth production process in manufacturing companies. PT Bonecom Tricom, a producer of automotive spare parts, faces challenges in managing SPP-C05 Black plastic pellets due to inaccurate estimation methods, resulting in material accumulation in storage. This study aims to propose inventory planning using time series and min-max methods to optimize material requirements. The results show that the Holt-Winter's Multiplicative method provides the best forecasting accuracy with the lowest error rate (MAPE) of 2%. Furthermore, implementing the min-max method can reduce inventory costs by 14.245%. This study is expected to serve as a reference for companies to manage material inventory more effectively and efficiently.

PT.XYZ is an automotive company that has been operational since 1970, with over 400 suppliers for key components such as Stoper A and Stoper B. Annually, Stoper A sells 151,000 units (valued at IDR 4.077 billion), while Stoper B reaches 300,000 units (valued at IDR 8.100 billion). This research focuses on analyzing and optimizing the supply chain for these components, using sales data from January to December 2022. The goal is to create stock and flow diagrams, analyze the supply chain system modeling, and propose optimal scenarios for demand fulfillment. The modeling results indicate that a strategy of adding a 20% safety stock to the average sales is highly effective in preventing lost sales without burdening suppliers with overtime. However, the potential for overstock needs to be monitored. Based on the analysis, the second scenario proposing the addition of safety stock is recommended due to its effectiveness in meeting demand and efficiently managing inventory. This scenario is deemed most suitable for PT. XYZ in maintaining a balanced supply without unnecessary surplus.

Quality risk management is one of the important things in quality control in a pharmaceutical industry. One of the risky activities in the pharmaceutical industry is in storage and distribution. Every activity carried out in the inventory warehouse can potentially cause risks that affect quality including the flow of the storage and distribution process of goods. Based on this, a study was conducted in the form of a risk assessment on the flow of the storage and distribution process of release goods in the inventory warehouse of a pharmaceutical industry in Bandung which aims to determine the level of risk that has the potential for failure. The FMEA (Failure Modes and Effects Analysis) method is a method that can be used to assess the risks that can occur in the flow of the storage and delivery process of goods in the warehouse. This risk assessment is carried out with the stages of risk identification, risk analysis, and risk evaluation using categorization based on the Risk Priority Number (RPN). In this study, 15 risks were obtained with details of 1 low category risk, 7 medium category risks, 6 high category risks, and 1 very high category risk. Therefore, the pharmaceutical industry can immediately determine mitigation steps and take control measures against risks in the high and very high categories to reduce the risk of failure with the hope that the quality, safety and efficacy of the product can be maintained properly

PT Shoes Bata Tbk is a company engaged in the manufacture of leather shoes, canvas shoes, casual and sports shoes, injection/slop sandals and industrial footwear safety mats. Financial performance is a description of the financial condition of a company which is analyzed using financial analysis tools, usually the measure used is the ratio. Research conducted by the author to analyze the financial performance of PT Shoes Bata Tbk based on profitability ratios and activity ratios. The profitability ratio can be measured by Gross Profit Margin, Net Profit Margin, and Return on Investment. Where Gross Profit Margin and Net Profit Margin are ratios that measure the company's ability to earn profits on sales, Return on Investment is a ratio that measures the company's ability to use all assets owned to generate profits after tax. The activity ratio can be measured by Receivable Turnover, which is a ratio that measures the company's ability to quickly manage the level of accounts receivable turnover. Inventory Turnover is a ratio that shows how quickly inventory turns over in sales activities. And Total Asset Turnover is a ratio that measures a company's ability to create sales using all the assets it owns. The aim of this research is to find out and analyze the financial performance of PT SEPATU BATA Tbk during 2016-2021 based on the two ratios. This research uses a descriptive qualitative approach method. The data source used is secondary data in the form of profit/loss financial report data and balance sheet reports. The results of this research indicate that the financial performance of PT Shoes Bata Tbk for the 2016-2021 period based on GPM is considered very good because the company was able to reduce the cost of goods sold, resulting in high sales and high gross profit. NPM is considered not good because the net profit generated is less with quite high sales. ROI is considered very poor because the high total assets are not commensurate with the net profit generated. RT is considered very good because it increases every year. IT is considered very poor due to the decrease in cost of goods sold and increase in average inventory each year. TAT is considered quite good because the company is able to manage its assets well. Financial performance as measured by the profitability ratio and activity ratio can be said to be less efficient, because the components of the profitability ratio and activity ratio are still low and do not reach good company standards.

PG Madukismo is a sugar factory that was established in 1955 and is the only sugar factory in the province of the Special Region of Yogyakarta. This factory is located in Padokan Village, Tirtonirmolo Village, Kasihan District, Bantul Regency, Special Region of Yogyakarta. PT Madubaru, a company engaged in sugar cane processing, is a sugar and spirits factory located in the Yogyakarta area. Companies that produce cane sugar with SHS IA quality. Product defects are often found, resulting in a decrease in quality, therefore it is necessary to carry out quality control. This study uses the Failure Mode and Effect Analysis (FMEA) method to identify failure modes, Logic Tree Analysis (LTA) to determine the consequences of failure arising from failure modes and determine effective preventive maintenance policies for each machine. For the production quality control section, the Statistical Processing Control (SPC) method is used to analyze product defects to determine whether product defects are still within controllable limits or not. While the Failure Mode and Effect Analysis (FMEA) method is used to determine the failure mode in sugar production. For the quality control section on raw materials using the Economic Order Quantity (EOQ), Re-Order Point (ROP), Safety Stock (SS), and Total Inventory Cost (TIC) methods. The conclusion of this study is regarding the results of the analysis and calculations carried out with several settlement methods and there are several causes of production defects from 5 factors, such as: human factors, work methods, environment, raw materials and machines used. And provide solutions to companies in order to reduce defects by controlling product quality.