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This study aims to analyze inventory control of catfish seeds at ABC Company by comparing the conventional inventory method represented by the Economic Order Quantity (EOQ) approach and the Just In Time (JIT) system in order to improve cost efficiency. This research employed a descriptive quantitative approach using a case study design. Data were collected through direct observation, semi-structured interviews with company management, and documentation of inventory and cost records for the 2024 operational period. The analysis method involved calculating optimal order quantities, ordering frequency, delivery frequency, and total inventory costs using EOQ and JIT formulas, followed by a comparative cost efficiency analysis. The results show that the conventional method resulted in a total inventory cost of Rp 75,050,000 per year with high ordering frequency. In contrast, the implementation of the JIT system reduced inventory costs to Rp 18,762,500 per year, achieving a cost efficiency of 72%. These findings indicate that the JIT system is more cost-efficient than the conventional method; however, its implementation requires careful consideration of supplier capacity, logistics readiness, and biological risks associated with live inventory. This study contributes empirical evidence on the applicability of JIT in the aquaculture sector, which has different characteristics from manufacturing industries.

This study aims to analyze and determine the optimal production capacity at Sekar Arum MSMEs to achieve maximum profit using the Linear Programming (LP) graphical approach. The research employed a quantitative method with a descriptive approach. The data used included primary data from interviews and observations, and secondary data from production and raw material records. The analysis was conducted by formulating a mathematical LP model consisting of an objective function and constraint functions based on the limited resources available to the enterprise. Data processing was carried out using POM-QM for Windows version 5 with the graphical method to identify the optimal solution point. The results indicate that the optimal production combination is 2 kilograms of red ginger and 3 kilograms of tamarind turmeric, yielding a maximum profit of Rp4,600,000 per production cycle. The implementation of Linear Programming proved effective in assisting MSME owners in making efficient production decisions, thereby enhancing profitability and the sustainable use of resources.

This study aims to analyze the effect of Total Asset Turnover (TATO) on stock prices at PT Baramulti Suksessarana Tbk during the 2014–2023 period. TATO is an activity ratio that measures how efficiently a company utilizes its total assets to generate sales. This research employs a quantitative associative approach using secondary data obtained from the company’s annual financial statements published by the Indonesia Stock Exchange. Data were analyzed using simple linear regression to determine the relationship between the independent variable (TATO) and the dependent variable (stock price). The results show that TATO has a positive and significant effect on stock prices, with a correlation coefficient of 0.859 and a significance value of 0.001 (p < 0.05). This indicates that the more efficiently a company uses its assets to generate sales, the higher its stock price will be. The findings support the signaling theory and efficient market hypothesis, suggesting that asset efficiency serves as a positive signal for investors in evaluating firm performance.

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 business position of BMT Dana Mentari Muhammadiyah Purwokerto using the McKinsey Matrix as a strategic analysis tool. The method used is a qualitative approach with data collection through literature studies, observations, and interviews with BMT managers. The data obtained were analyzed using the McKinsey Matrix to assess market attractiveness and business strength in each business unit. The study results indicate that most of the BMT Dana Mentari Muhammadiyah Purwokerto business units are in the blue and yellow zones in the McKinsey Matrix, indicating the need for selective development and maintenance strategies. This analysis also recommends effective and efficient resource allocation to improve the competitiveness and performance of BMT in the Islamic microfinance market. Thus, the use of the McKinsey Matrix has been proven to help BMT in determining the priority of business strategies that are adaptive to market dynamics and competition.

Artificial Intelligence (AI) has become an essential tool in the world of management for decision-making. This article examines the ways in which AI can be used to improve the quality and speed of decision-making, and how AI can improve the operational efficiency of companies. In addition, this article also examines the challenges and opportunities that companies face in adopting AI.In the rapidly evolving digital era, AI has become an essential component of modern business strategies. Today's managers are often faced with the challenge of analyzing very large and complex volumes of data. To make good and timely decisions, AI offers a potential solution with fast and precise data analysis capabilities.The use of AI in decision-making involves machine learning algorithms and models to efficiently process and analyze large amounts of data. This helps managers gain deeper and more accurate insights, enabling more effective decision-making.

This study aims to optimize sales profit at the MSME Batagor Bandung Tarakan by applying the Simplex method in linear programming, supported by the POM-QM for Windows software. Profit optimization plays a crucial role in strategic decision-making, particularly in determining the optimal daily production quantities to enhance operational efficiency, maximize the use of raw materials, and meet market demand effectively. The Simplex method was chosen for its ability to solve linear optimization problems involving multiple constraints and variables, providing accurate mathematical solutions to achieve maximum profit. This research utilizes daily production data as the basis for analysis, which is then processed using the Simplex method in POM-QM. The results show that implementing the Simplex method can increase daily profits from IDR 634,000 to IDR 831,408 through a more efficient production combination. The study concludes that the Simplex method, when applied via the POM-QM software, is an effective tool for daily production decision-making and can support MSMEs like Batagor Bandung Tarakan in improving their competitiveness and business sustainability.