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Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in supporting local and national economic development, particularly through employment generation and income distribution. Seasonal religious events such as Ramadan significantly influence consumption patterns and market dynamics, creating both opportunities and challenges for MSMEs. This study aims to analyze the implementation of the “Seri Ramadhan” phenomenon within the strategic management practices of MSMEs in Martapura, focusing on the periods before and after Ramadan. The research employed a qualitative descriptive approach with field study methods. Data were collected through in-depth interviews, direct observation, and documentation involving selected MSME actors in the culinary, fashion, and retail sectors. The findings indicate that prior to Ramadan, MSMEs emphasize strategic planning through product innovation, stock preparation, promotional intensification, and operational adjustments. After Ramadan, they conduct performance evaluations, inventory control, and strategic realignment to maintain business sustainability. The study highlights that Ramadan is not merely a short-term sales opportunity but also a strategic momentum integrated into broader business planning cycles. The implications suggest that adaptive and cyclical strategic management enhances MSME resilience and competitive advantage in seasonal markets.

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.

In the era of digital transformation, the utilization of information technology in business activities has become an important factor in improving operational efficiency and effectiveness. Dzikri Baby Shop, a business engaged in the sale of baby equipment, still faces challenges in managing sales transactions and inventory manually, which may lead to recording errors, process delays, and less optimal customer service. This study aims to design and develop a sales information system for Dzikri Baby Shop to support digital transformation in its business processes. The system development method used in this research is Rapid Application Development (RAD), as it enables software to be developed in a relatively short time through an iterative approach and active user involvement. The system developed includes product data management, sales transaction processing, inventory control, and report generation. The testing results using the Black Box Testing method show that all system features function in accordance with user requirements. Therefore, the implementation of this sales information system is expected to improve operational efficiency, accelerate transaction processes, minimize errors in data management, and enhance the quality of customer service.

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.

Production planning and inventory control are critical aspects of operations management, as they directly influence cost efficiency, resource utilization, and the continuity of the production process. Ineffective planning and inventory decisions may lead to excessive costs, production delays, or imbalances between supply and demand. The complexity of these problems, which often involve multi-period horizons and multi-stage decision-making processes, has encouraged the application of quantitative optimization methods, one of which is dynamic programming. This study aims to analyze and synthesize the application of dynamic programming in production planning and inventory control through a Systematic Literature Review (SLR) approach. The SLR process was conducted by systematically identifying, selecting, and analyzing 15 relevant national journal articles published between 2015 and 2024 and obtained from various recognized scientific databases. The reviewed literature indicates that dynamic programming is effective in supporting optimal decision-making by determining appropriate production quantities and inventory levels, minimizing total production and holding costs, and managing fluctuating demand conditions. In addition, this method helps reduce the risks associated with overstock and stockouts by considering sequential decision structures. However, the findings also reveal several limitations of dynamic programming, including high computational complexity, strong dependence on deterministic data assumptions, and limited flexibility in handling high levels of uncertainty. These constraints suggest the need for further methodological development or integration with other approaches to enhance practical applicability.