Abstract Catfish is one of the important strategic commodities in Indonesia which is widely cultivated. Catfish needs continue to increase along with the increasing demand for catfish as foodstuffs such as the need for many lamongan stalls. However, efforts to increase production and development of catfish farming have several obstacles that can reduce production by 50% due to certain diseases. This situation is certainly very detrimental to the catfish in particular and the wider community in general. However, farmers have very low knowledge about the technical maintenance of catfish plants. This situation resulted in farmers being highly dependent on the control of a limited number of plant pests. To overcome this problem, a website-based application was made. To optimize computational resources on mobile devices, we need a Cased Base reasoning method that consists of frame based and rule based representation with rules or rules that are used to determine whether catfish plants contract certain diseases, which types of diseases can be detected in the process this research includes bacterial pustular disease, interchnose disease, mosaic virus disease, collapsing disease, rust disease and blight disease. then analyzed which cased base reasoning is the most optimal. This can be done with a scenario comparing some of the cased base reasoning from the level of accuracy at 87.5%.