Analysis of Patient Disease Trends Based on Medical Record Data Using the C4.5 Algorithm

Abstract

Data mining is the process of finding patterns from large data sets using descriptive, estimation, prediction, classification, clustering and association techniques. The C4.5 algorithm is one of the most popular algorithms of the classification method in data mining which is the development of the Iterative Dichotomizer 3 (ID3) algorithm. By using the algorithm C4.5, the authors are interested in conducting research on medical record data that is in the Regional General Hospital dr. Fauziah Bireuen. A medical record is a file containing notes and documents regarding the patient's identity, examination results, medication, actions and other services that have been provided to patients. The purpose of this study was to find trends in patient disease using the C4.5 algorithm based on 4 data variables, namely age, gender, address and diagnosis. From the research results, it was found that disease trends in children, adults and the elderly in all Bireuen regions and all genders were F00-F99, namely mental and behavioral disorders. While the disease trend for infants is A00-B99, namely certain infections and parasitic diseases. Then for adolescents in North Bireuen and West Bireuen the emerging disease trend is F00-F99, namely mental and behavioral disorders, while for adolescents in South Bireuen who are male, the emerging disease trend is I00-I99, namely diseases of the car and mastid process, while adolescents in South Bireuen are female, the trend of disease that appears is M00-M99, namely diseases of the musculoskeletal system and connective issue.