Muscle, Bone, Joint Problems are health problems in the human body. Problems of muscles, bones, joints felt by almost everyone, both parents, adolescents, and children. Symptoms of muscle, bone, joint problems can be pain in the knee, pain in the shoulder, pain in the neck, pain in the hands, pain in the legs or pain in the back. To categorize the problems of muscles, bones, joints, there are many problems in management reporting to find out the symptoms that often occur in one semester. Based on this it is necessary studies that lead to the creation of a system that can categorize the spread of symptoms in muscles, bones, joints to determine the results of diagnosis based on the pattern of symptoms experienced by patients. So that helps management to find out and get information based on the pattern of symptoms that occur in patients. One alternative to the problem, this study we make a search pattern or association rule association (associative rules) of large-scale data and is very closely related to data mining that can be used to find certain rules that associate data with one other data with a priori algorithm method. The purpose of the method is to search historical data to identify data patterns based on previous characteristics to determine the disease diagnosis. So that the information generated can be used by management to provide appropriate diagnostic information according to the natural pattern of symptoms by the patient.
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