<![CDATA[Product management in a vending machine business requires fast and data-driven decision-making to increase sales effectiveness and profitability. However, decision-making related to price adjustments, product bundling, product replacements, and product arrangement on vending racks is still mostly done manually based on the manager's experience, so it has the potential to produce less than optimal decisions. This research aims to develop an Intelligent Decision Support System that is able to produce business strategy recommendations through the integration of Quadrant Analysis, Time Series Trend Analysis, and Automatic Planogram Generation. The research data was obtained from the results of exporting the vending machine transaction database imported into the application in CSV or Excel format, so that the system does not depend on direct integration with the Application Programming Interface (API). Quadrant Analysis is used to group products based on sales performance and profit contribution, while Time Series Trend Analysis is used to evaluate historical sales trends as a support for decision validation, rather than as a sales prediction method. The results of the second analysis were processed using a rule-based decision engine mechanism to produce recommendations in the form of price adjustments, product bundling, maintaining or replacing products, and compiling an automatic planogram based on product performance priorities. The resulting planogram can still be adjusted manually by the user so that it still provides flexibility in operational decision-making. In addition, the system presents profit analysis based on product, machine, and location as the basis for business evaluation. The resulting artifacts are in the form of a decision support system application that not only presents data visualization, but also automatically generates strategic recommendations to help managers improve the effectiveness of product management in the vending machine business.]]>
