Penerapan Metode K-Means untuk Evaluasi Senyawa Anti Kanker Berdasarkan Kajian Proteomik Sel MCF7 - Mochammad Pratama Viadi; Marji Marji; Sri Widyarti (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Cancer is a disease that originates from several body cells that can divide without stopping and can spread to surrounding tissues. Then split cell will attack and damage the surrounding tissue. Especially in breast cancer or occupying the top level in cancer. This cancer originates from a glandular tract in the breast which declared a malignant tumor. In the detection this disease can use bioinformatics techniques, namely proteomic studies. Output produced is a grouping of the results of the anti-cancer process on the development of cancer in the form of clustering using the K-Means process which is divided into 2, active and inactive. The results of system testing were carried out using Silhoutte Coefficient and Precision Recall Accuracy. In the Silhoutte Coefficient test getting the optimal cluster is 5 with a value of 0.6827. Whereas in testing the Precision Recall Accuracy, the Precision value was 67.59%, the Recall value was 79.57%, and the accuracy rate was at 57.71%. Using 10-fold cross validation get an average accuracy of 62.26%.