<![CDATA[Micro, Small, and Medium Enterprises (MSMEs) in the angkringan-based coffee shop sector have significant economic potential; however, many of them still face challenges in production decision-making due to limited resources and the lack of data-driven planning. This study aims to optimize the beverage production mix at Coffee Suganda, an MSME coffee shop located in Majalengka Regency, which produces 25 product variants, with three main products: palm sugar milk coffee, creamy milk coffee, and chocolate. The research applies Linear Programming (LP) to maximize profit under constraints related to raw materials, production time and is further strengthened by sensitivity analysis to examine the robustness of the optimal solution under parameter changes. Research data were collected through field observations, interviews with the business owner, and records of production and sales activities. The results indicate that the Linear Programming approach provides a more optimal production combination compared to the existing conditions and improves resource utilization efficiency. The sensitivity analysis reveals that changes in raw material availability and selling prices significantly affect the optimal solution, highlighting the importance of adaptive production planning. This study contributes practical insights for angkringan-based coffee shop MSMEs in developing data-driven and adaptive production strategies, as well as academic contributions to the literature on MSME production optimization]]>
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