Penerapan Algoritma Naive Bayes Untuk Memprediksi Penyakit Malaria Pada Puskesmas Tana Teke - Roswita Tanggu; Elfira Umar; Lidia Lali Momo (CV. ITTC INDONESIA, 2023)
In health care medical records can be used as comparisons and gauges to determine the development of disease in an area.But it's good that the data is being treated as useful data including being able to predict a disease..Malaria cases are infectious and are very dominant in the tropics / subtropics.The puskemas tana teke has the most positive sufferer malaria.The puskemas party doesn't have a system yet to predict malaria., Therefore, to harness information system technology and to prevent malaria earlier, research has been done to predict malaria by means of na ve bayes on tana teke pusemas..The patient's dataset contains 16 attributes and 6 are symptoms of malaria with a total of 118 patients' data.The calculations with na ve bayes show that appropriate symptoms of disease will result in positive predictions..Such predictions can be used for cement conjectures.