Sistem Fuzzy Pendukung Keputusan untuk Diagnosa Kanker Payudara - I Made Agus Wirawan (Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia, 2014)
In recent years, Artificial Intelligence methods havelargely been apllied in various fields including medicalapplications. Breast cancer is the cause of death worldwide,especially among women. To make a diagnosis of breast cancer, adoctor had difficulty in determining the risk status of breast cancer.This study aims to develop a decision support system (DSS) basedfuzzy to help doctors classify the risk of breast cancer. The systemhas six input variables (Her2, hormone receptors, age, tumor grade,tumor size, lymph node and) and one output variable (risk status).This system uses a model inference Mamdani (max), where eachvalue of each rule generated from several tNorm implicationsmethod such as tNorm Zadeh, tNorm Dombi, tNorm DuboisPrade,tNorm Yager, tNorm Product, and tNorm EinsteinProduct.Defuzzyfication method are used is centroid method. Based on thetests performed, Risk Status value obtained is 2.7089 for tZadeh,tDombi, tYager and tProduct. Risk Status for tDubois Prade is 2.86,while for tEinstain Product, Risk status is 3.35. In further research,this system can be applied to other types of cancer or using otherinference methods for the preferences of the previous case.