Maulana R Ibrahim, Muhammad F Ihsan, Rizky Maharani, Warsito P Taruno
International Symposium on Biomedical Engineering (ISBE), Jakarta, 2016
 CTECH Labs Edwar Technology
Corresponding Author Email: firstname.lastname@example.org
This research implemented nearest neighbor algorithm to classifies the position of phantom after scanned using Brain Electrical Capacitance
Volume Tomography (ECVT). With k-Nearest Neighbors algorithms, we evaluated 496 values of capacitance measurement to find its nearest
neighbors (highest similarity) and classifies its exact position in the sensor. The performance of this technique reached 93.33% of accuracy.
k-nearest neighbor; brain ECVT; supervised learning; phantom prediction