<![CDATA[Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.]]>
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