Hybrid-dimension association rules for diseases track record analysis at Dr. Soetomo General Hospital

Dr. Soetomo General Hospital already has a Hospital Information System which has been computerized for data storage of each recapitulated patient´s disease. Since data recapitulated the patient´s disease is increasing, Dr. Soetomo Hospital needed an application which can provide information for decision makers. One application that can help in decision making is data mining. Data mining with hybrid-dimension association rules method where the method to analyze the relationship between disease with patient identity. This method is made using apriori algorithm. Hybrid dimension association rules is a multidimensional association rule that allow the repetition of the predicate on each rules. This method is very suitable to describe the rules of the relationship with the patient´s disease and patient´s identity. Data that has been prepared is processed by the algorithm to generate frequent itemset so that will produce hybrid dimension association rules and the rules displayed by form of tables and graphs. The implementation of the algorithm is using Java Netbeans 6.5 software and Oracle 10g. By using the output of this application is in the form of association rules and charts, decision makers can know the relationship between the patient´s disease with the patient´s identity such as gender, status, domicile, education and occupation with other diseases.