The study evaluates cassava chip crispness using a fuzzy logic system based on temperature and vacuum pressure variables. Fuzzy logic system is applied to objectively assess crispness, modeling the relationship between frying variables and chip texture. The application of fuzzy systems as a quality control tool can help optimize the production process so that chips meet standards. This study employs a literature review combined with an expert-based approach to design a fuzzy logic system for evaluating the crispiness of cassava chips based on temperature and pressure variables. For input and output variables, we use temperature and vacuum pressure. The temperature range used is 140-200°C and for pressure variable, we use -65, -68, -72 CmHg. Sensory values for the three crispness categories show that the undercooked category received an average score of 3.76 ± 0.52, the crisp (optimal) category received 3.72 ± 0.88, and the overcooked category received 3.85 ± 0.11. Combination of temperature 170°C and vacuum pressure -68.5 CmHg yields the best crispness result, showing that the chips reach the desired texture, not too hard and not too soft. This demonstrates that the centroid method provides a representative defuzzified value that closely reflects actual frying conditions, ensuring consistent product quality.
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