Indonesian cloves have strong competitiveness in the main market due to their economic benefits, such as being raw materials for kretek cigarettes, spices, and the perfume industry. However, high global competition demands improvements in product quality and consistency. The manual and subjective sorting of cloves often leads to inaccuracies and inconsistencies in quality, which can be detrimental to farmers, especially in smallholdings. The objective of our research is to develop a web-based system for classifying the quality of dried clove flowers using the Tsukamoto fuzzy logic method. The stages of system development using the waterfall method include system requirements analysis, architecture and interface design, website implementation with the Tsukamoto fuzzy method, and testing. The Tsukamoto fuzzy logic implementation method was chosen due to its ability to process uncertain data and produce consistent output. Our findings successfully produced a web-based system called 'Clove Tester', with an average sensitivity of 45.99% from sensitivity testing based on modifications to the membership function of condition and quality variables. These results indicate that the system has a good adaptability to variations in input data, making it suitable for application to data with a high level of uncertainty or ambiguity in this research.