Detection of Ovarian Cancer Risk Level Using the Web-Based Dempster Shafer Method
Kraugusteeliana Kraugusteeliana, Nursaka Putra, Miandhani Denniz Yuniar, Dasril Aldo, Anik Rahmawati, Viro Dharma Saputra · 2022 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS) · 2022
Ovarian cancer is cancer that grows in the ovaries or ovaries. This disease occupies the seventh position among the types of cancer that most attack women. Every year, there are about 250,000 cases of ovarian cancer worldwide, which causes 140,000 deaths per year. The purpose of this study is to improve the prediction of ovarian cancer symptoms using the Dempster Shafer method where patients can get to know more about the symptoms that may occur if a patient is diagnosed with ovarian cancer. Dempster Shafer is a mathematical theory for proof based on a belief function and reasonable thought, which is used to combine separate pieces of information (proof) to calculate the probability of an event. The results of this study, it is known that the risk density value for ovarian cancer is 0.32131497 or 32.131497%. With a density value of 32.131497%, then the patient has evidence that he is not at risk of developing ovarian cancer because it is more than 50%.