Perbandingan Metode Decision Tree dan Naive Bayes untuk Memprediksi Thyroid Cancer Recurrence

Fidya Hafizd (Universitas Pancasila)
Dian Rizky Julyani (Universitas Pancasila)
Hasna Yuliza (Universitas Pancasila)
Emely Nemy Agustine (Universitas Pancasila)
Kessya Immanuella Surbakti (Universitas Pancasila)
Iman Paryudi (Universitas Pancasila)

Journal of Informatics and Advanced Computing
Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)

Abstract – This study aims to predict thyroid cancer recurrence by comparing two data mining methods, namely Decision Tree and Naive Bayes. The data used is classification data that has gone through preprocessing and modeling processes, then tested using test and score tests on analysis software called Orange. By using Orange as an analysis tool, experiments were conducted to determine which method gave the best accuracy. The results show that the two methods have different accuracy comparisons in predicting thyroid cancer recurrence. This research is expected to help in identifying symptoms that are at high risk of causing thyroid cancer recurrence and provide valuable insights in data analysis.