PROTOTYPE SISTEM KLASIFIKASI KELAS PASIEN PENYAKIT PERNAPASAN BERBASIS RASPBERRY PI DENGAN METODE DECISION TREE

Abstract

Everyone must have experienced something called illness. A disease in the human body can be caused by external factors such as pathogens or internal dysfunction. In a broader sense, a disease also includes injuries, disorders, disabilities, infections and syndromes. Among the various infections that exist in the human body, acute respiratory infections (ARI) are the most common diseases that affect all individuals regardless of age or gender, especially this virus that attacks the respiratory tract or respiratory diseases that virus spreads very quickly. . With this, the world health agency or known as the WHO (World Health Organization) has set several standards that can help deal with problems in the world. Therefore, we need equipment that helps check patients regularly and performs an early diagnosis so that when entering the patient's room, medical personnel have prepared themselves with some equipment that is by the patient's classification. This study will focus on the classification process in real-time on sensors installed in patients using machine learning decision trees as the classification method. Then, the classification results can be shown directly that the respiratory disease patients fall into a predetermined class.