Publication Search

The management of essential drug inventory is a strategic component of hospital pharmaceutical services because it directly influences service continuity, cost efficiency, and the overall quality of healthcare delivery. Poor inventory control can result in excessive stock accumulation, increased risk of drug expiration, inefficient budget utilization, and potential drug shortages that may compromise patient care. This study aims to evaluate the effectiveness of essential drug inventory control at Pekerja General Hospital by applying the ABC-VEN, Economic Order Quantity (EOQ), and Reorder Point (ROP) methods. It also examines differences in inventory management efficiency between 2024 and 2025 based on inventory value, cost of goods sold (COGS), and Inventory Turnover Ratio (ITOR). A mixed-methods approach with a sequential explanatory design was used. Quantitative analysis involved a paired sample t-test comparing inventory data from 2024–2025, while qualitative data were collected through in-depth interviews and analyzed thematically using NVivo. The findings reveal a significant improvement in inventory management in 2025 (p < 0.05), reflected in reduced inventory value and COGS, along with an increased ITOR. However, the implementation of ABC-VEN, EOQ, and ROP methods has not been fully integrated, and challenges such as limited human resources and procurement bureaucracy persist.In conclusion, although inventory control became more efficient in 2025, further integration of inventory methods and strengthening of human resource capacity are necessary to ensure sustainable improvements.

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.

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.

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.  

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in supporting regional economic development. However, inefficient inventory management remains a significant challenge in operational effectiveness. This study aims to analyze raw material inventory control at Kebab & Burger Foursist MSME in Tarakan City using the Economic Order Quantity (EOQ) and Reorder Point (ROP) methods. A descriptive quantitative approach was employed, utilizing annual sales data, ordering costs, and storage costs of main raw materials. The results indicate that the implementation of EOQ and ROP effectively determines the optimal purchase quantity and reorder timing, thereby minimizing total inventory costs and reducing the risk of stockouts or overstocking. The use of POM-QM for Windows software enhances the accuracy of the analysis. The implications of this study offer practical solutions for MSME actors in managing raw material procurement more efficiently and systematically.

This study aims to analyze the optimization of seaweed seedling inventory management using the Economic Order Quantity (EOQ) method to enhance cost efficiency for farmers in Tarakan City. The research employs a quantitative descriptive approach, integrating EOQ with forecasting techniques (Moving Average and Exponential Smoothing) to predict raw material needs accurately. Data were processed using Microsoft Excel and POM-QM for Windows to ensure precision. The results indicate that EOQ yields an optimal order quantity of 878 ropes per order, with a frequency of 6 orders per year, a reorder point of 16 ropes, and a total inventory cost (TIC) of IDR 842,681. Compared to traditional methods (TIC IDR 2,132,083), EOQ reduces costs by 60.5%. Forecasting analysis reveals that Exponential Smoothing (MAPE 19.67%) outperforms Moving Average (MAPE 22.5%) in accuracy. These findings highlight EOQ’s effectiveness in minimizing waste, preventing stockouts, and improving productivity. The study provides practical insights for coastal small-scale farmers and policymakers in the marine sector.

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.

Community Health Centers (Puskesmas) are facilities established to implement promotive, preventive, curative, and rehabilitative health services by the government, local authorities, and the community. The system of drug planning and procurement plays a pivotal role in determining drug availability and the budget allocation required. This study aims to evaluate the process of drug planning and procurement using a combination of the ABC-VEN and Reorder Point (ROP) methods at the Belik Community Health Center, Pemalang Regency. This research is a descriptive analysis employing a retrospective case study design with data collection from January to December 2023 and supported by interviews. The results show that the ABC-VEN combination analysis identified: AV group (1 item; 0.29%; cost IDR 4,662,000), AE (45 items; 12.86%; IDR 271,578,813), AN (7 items; 2.00%; IDR 65,272,502), BV (7 items; 2.00%; IDR 7,825,526), BE (53 items; 15.14%; IDR 70,352,382), BN (11 items; 3.14%; IDR 15,283,936), CV (19 items; 5.43%; IDR 3,687,488), CE (194 items; 55.43%; IDR 42,690,036), and CN (13 items; 3.71%; IDR 2,779,589). Drugs in groups AN, BN, and CN (Additional group) should be prioritized for reduction; AE, BE, and CE (Main group) are second priority; while AV, BV, and CV (Priority group) must always be available. The highest Reorder Point (ROP) was for Dexamethasone at 64,067 tablets, while the lowest was Betason skin ointment with 0 tubes.

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 or stock is stored material or goods that will be used to fulfil a specific purpose. An inventory management system is a set of control policies to determine the level of inventory that must be maintained. XYZ Company is a food company that produces Cireng. In the production process, the amount of demand received by the company varies from period to period.  Based on the existing data, there is too much raw material stock that causes high storage costs for the company. Therefore, the EOQ method is needed to manage the company's inventory. From the data processing carried out in the POM-QM software, the output is obtained for tapioca flour raw materials where the total cost is Rp. 404,034,000 and the reorder point is 8 units, the output of the garlic raw material data where the total cost is Rp. 397,513,200 and the reorder point is 5 units, while the output of the flavouring raw material data where the total cost is Rp. 392,749,500 and the reorder point is 6 units. So as to obtain the optimal amount of inventory in each order, the total cost incurred and the reorder point value for each raw material of the XYZ company.      

The need for soybeans in Indonesia increases along with population growth, with demand reaching 2.7 million tons in 2023. Soybeans are an important raw material in the food industry, especially for processed products such as tempeh. This research aims to analyze the control of soybean supplies in the Bogor Regency Tofu and Tempe Cooperative (KOPTI) using the Economic Order Quantity (EOQ) method. The Economic Order Quantity (EOQ) method was chosen because it is able to optimize the costs of ordering and storing raw materials. Primary data was obtained through interviews with KOPTI owners and employees. The analysis results show that the optimal order quantity is 333,371 kg with an order frequency of 4 times per year. In addition, the safety stock required is 82,252 kg, and the reorder point is 85,865 kg. Using the EOQ method can save total inventory costs from IDR 14,332,491.57 to IDR 910,102.39. This research suggests KOPTI to apply the Economic Order Quantity (EOQ) method to increase cost efficiency and maintain stable raw material supplies.

PT XYZ is an industrial company that produces tools. In this research, the problem that must be resolved, namely the issue of raw material inventory control that occurs at PT XYZ, will be resolved using the Economic Order Quantity (EOQ) method using POM-QM software. By using the Economic Order Quantity (EOQ) method, it is hoped that it can solve the raw material inventory control problems that occur at PT XYZ so that the costs incurred by the company are optimal. So, PT XYZ can solve the problem of controlling raw material inventory with the help of the POM-QM application to facilitate the calculation process. Based on the analysis and data processing that has been carried out, it is known that the optimal quantity of raw material A output per order is 150 units with a total cost of IDR 270,596,000 and a reorder point value of 7 units. For raw material B, the optimal quantity per order is 241 units with a total cost of IDR 2,439,490,000 and a reorder point value of 53 units. For raw material C, the optimal quantity per order is 94 units with a total cost of IDR 425,200,400 and a reorder point value of 7 units. For raw material D, the optimal quantity per order is 82 units with a total cost of IDR 217,229,600 and a reorder point value of 5 units. So the raw material that has the most influence in the tool making process at PT XYZ is B because it has the largest reorder point value.    

Inventory is an important factor in carrying out a production. Many companies experience problems in terms of inventory control, one example is inventory scarcity. The purpose of this study is to optimize the need for goods so that the company will not experience problems with inventory shortages or inventory buildup. This study uses  the Min-Max method  by collecting data in the form of inventory of goods needs, ordering costs, and storage costs. The result of this study  is that the safety stock value  of 80,887-tons is useful for protecting and anticipating inventory shortages, so companies must be on guard when they are at that value. Then, the Reorder Point value was obtained at 108,165 tons. Furthermore, the value of the Minimum Inventory  is 269,879-tons and the Maximum Inventory is  378,044-tons so that companies are not recommended to have more inventory than that value.    

Every sale of goods, sales report the number of goods sold to the warehouse admin. Because of the many types of goods being sold, sometimes the warehouse admin forgets about which items are almost out of stock and should be ordered. The aim of this research is to produce a goods ordering system with the EOQ and ROP control methods to overcome the occurrence of stockouts. The author uses the research object of employees who work at PT Kimia Farma Plant, namely sales, warehouse department, admin and HRD. With this system, the warehouse admin can see the number of items in real time. The EOQ method generates a report on the number of economic purchases (EOQ), the total costs that must be incurred by the company to reorder an item, the duration of the EOQ, up to the reorder point (ROP).

PKS Pagar Merbau is a plantation company engaged in palm oil processing. Due to the unpredictable level of demand, determining the timing and number of orders becomes difficult, resulting in increased inventory costs. By using the Period Order Quantity Method, it aims to be able to control Crude Palm Oil raw material inventory which will minimize inventory costs. The Period Order Quantity (POQ) method is a development of the Economic Order Quantity (EOQ) method where the number of orders can minimize the total cost of inventory. The results of applying this method, obtained the optimal number of orders of 1,208,798.12 kg for one order with a frequency of 101 times a year with a safety stock of 3,000,200.61 kg and a reorder point of 3,961,816.26 kg. The total inventory cost according to company policy is  Rp. 3,159,298,770.65 while the total inventory cost according to the Period Order Quantity method is 2,879,961,532.42. Then the total inventory cost savings of Rp. 279,337,238.23 or 8.86%

In all section of inventory management, including inventory management in a hospital, minimize cost and ideal inventory accommodation against demand has always been a primary goal (Varghese, 2012). Nearly a third of the operational success of a hospital is in the field of medical supplies. In its usual way, inventory  management in hospitals using the approach to the demand usage, the characteristics of the item and the estimate of the demand. The model presented in this study accommodates that common approach which use a combination of inventory safety stock limit, Economic Order Quantity, and reorder point in a information system dashboard that capable to provide quick and easy information about the condition of inventory management. The result of the system are used for the hospital pharmaceutical inventory management in integration with the INACBGs  to optimize the inventory performance.