Analisis Pola Penyakit Hipertensi Menggunakan Algoritma C4.5 - Nurul Azwanti; Erlin Elisa (Universitas Islam Sumatera Utara, 2019)
There are approximately 95% of cases of unknown cause of hypertension, while the rest caused by other diseases such as coronary heart disease, impaired kidney function, and impaired cognitive function or stroke. RSUD Embung Fatimah is an Indonesian hospital located in Batam Island Riau Province. In 2015, the total number of inpatients for hospitalization reaches 10,317 inhabitants. With the large number of patients per year it causes patient data is increasing. To overcome the problem in tackling people with hypertension disease, it is necessary to analyze the existing disease data, to predict the patient's illness which must be handled based on the pattern of the disease. In data mining there is a model that can be used to predict a pattern in a condition that is predictive or prediction model. One of the algorithms that can be used to create a decision tree (decission tree) is the C4.5 algorithm. The C4.5 algorithm is a method used for predictive classification. Using C4.5 algorithm method, the researcher can classify the pattern of hypertension as a comorbid illness of heart failure, kidney failure, diabetes, stroke and hypoglycemia. In this study, researchers used WEKA (Waikato Environment for Knowledge Analysis) software as tools or tools used to perform testing in order to obtain the pattern of disease from hypertension. From the research findings in the find that in the prediction of hypertension disease as a disease, the attributes that are very influential to hypertension are heart failure.