ANALISIS HASIL LABORATORIUM PENGIDAP PENYAKITDIABETES DENGAN ALGORITMA KLASIFIKASI PADAPUSKESMAS KECAMATAN CIRACAS JAKARTA TIMUR - Daffy Fayyadhya Ramzy (2024)
Diabetes is a chronic disease in the form of metabolic disorders that are indicated by the increase of glucose in a patient's blood to an abnormal level. The amount of diabetes patients continues to increase all around the world. The diagnoses of diabetes on a patient can be predicted with the Random Forest classification algorithm. After training and testing data with the Random Forest classification model with different split ratios, the model with the highest accuracy is the model that uses the split ratio of 70:30 with 72,89% accuracy. The time taken to learn and test with this model is also relatively short with 21,23 seconds of training time and 0,76 seconds of testing time. The result may not be as accurate as possible due to the fact that the amount of data with the label 0 (undiagnosed) is far higher than the amount of data with the label 1 (diagnosed).