Pendekatan Algoritma Klasifikasi Machine Learning untuk Deteksi Penyakit Demensia

Early detection of dementia through the use machine learning classification algorithms is important for providing appropriate interventions to patients. In this context, study aims compare performance several in detecting using attribute selection method. early stages, patient data including medical history, cognitive test results, and other attributes were collected as input, an algorithm was used select most informative subset dementia. The input training models, such Extra Trees (ET), Linear Discriminant Analysis (LDA), Random Forest (RF) Ridge. study, accuracy main metric performance. evaluation results show that produces best with 91.56%. (ET) has almost comparable 91.44%, while Ridge (LDA) have 90.44% respectively. context detection, method proved be These indicate developed model capable recognizing complex patterns relationships between features are relevant status. also contributes increasing efficiency algorithm.