Abstract
This study will investigate thalassemia. Thalassemia is a disease of blood disorders in red blood cells caused by genetic factors that cause red blood cells (hemoglobin) are not able to function properly. This disease causes a lot of death because it can not be cured, so to prevent the occurrence of thalassemia can do a prenatal test or early detection to determine people who have thalassemia. This study will separate a number of data using thalassemia classification technique to differentiate patients with thalassemia and normal patients by using the Fuzzy Kernel C-Means method. The results obtained show that FKCM has far better performance compared to FCM in classifying thalassemia data. FCM has an accuracy rate of 100% with an execution time of 0.80 seconds, while FKCM has an accuracy rate of 100% with an execution time of 0.19 seconds.
Original language | English |
---|---|
Pages (from-to) | 20-27 |
Number of pages | 8 |
Journal | International Journal of Advanced Science and Technology |
Volume | 28 |
Issue number | 8 Special Issue |
Publication status | Published - 8 Oct 2019 |
Keywords
- Accuracy
- Classification
- Fuzzy Kernel C-Means
- Thalassemia