PENERAPAN ALGORITMA J48 UNTUK DETEKSI PENYAKIT TIROID - Sarifah Agustiani; Ali Mustopa; Andi Saryoko; Windu Gata; Siti Khotimatul Wildah (LPPM Universitas Bina Sarana Informatika, 2020)
Impaired thyroid function is often difficult to identify because the symptoms are not specific. The symptoms of thyroid disorder are very similar to various complaints due to modern lifestyles so it is often overlooked. As a result, patients often do not notice a problem and do not have to consult a doctor. Therefore, there is a study that implements methods to predict the disease which will facilitate the patient in diagnosing and early detection of thyroid levels. This research aims to predict against thyroid disease with the data used is the secondary data obtained from the UCI repository, this data is about the patient data affected by thyroid disease, while the method uses the J48 algorithm because in some studies, the J48 algorithm is proven to have good performance in detecting an illness, as well as producing high value of Accuasy and AUC. The stage of data analysis is based on the CRISP-DM method while algorithm testing is done with Weka tools. Results of the test obtained an accuracy value of 99.645%, and a AUC value of 0.992 thus the accuracy has Excellent Classification level.