<![CDATA[Accurate calculation of the cost of goods manufactured (COGM) is essential for micro, small, and medium enterprises (MSMEs), yet small multi-product beverage businesses rarely trace shared conversion costs to individual menu items. Caffe Raza Coffee and Tea, an MSME in Sambas Regency, West Kalimantan, calculates the cost of its best-selling product, Coffee Raza, by adding up material purchases and a flat 25% share of payroll, while omitting depreciation and electricity costs. This study aims to (1) determine the COGM of Coffee Raza for January 2026 using the full costing method, (2) reconcile the result with the café's existing calculation by cost component, and (3) assess how sensitive the result is to the allocation and classification assumptions required in a multi-product setting. A descriptive quantitative case study design was used. Data were collected through observation, interviews, and documentation and were verified by cross-checking interview statements against purchase receipts, payroll records, the electricity bill, and sales records. Materials were traced directly to Coffee Raza, whereas shared conversion costs were allocated using the production-volume ratio of 300 out of 900 cups. The total production cost under full costing amounted to Rp3,898,131, consisting of direct materials of Rp925,000, direct labor of Rp1,300,000, and manufacturing overhead of Rp1,673,131, resulting in a COGM of approximately Rp12,994 per cup. The café's calculation (Rp2,974,000, or Rp9,913 per cup) understated the production cost by Rp924,131, which is fully explained by omitted electricity (Rp333,333), under-allocated labor (Rp325,000), and omitted depreciation (Rp265,798). The sensitivity analysis shows that the COGM ranges from Rp9,911 to Rp14,260 per cup under alternative assumptions, indicating that the choice of allocation base and labor classification matters as much as the inclusion of overhead itself. The results provide a reference cost floor for pricing decisions, while their effect on profit margins requires further analysis using selling price data.]]>
