Open AccessKlasifikasi Golongan Darah Menggunakan Artificial Neural Networks Berdasarkan Histogram Citra
Author(s) -
Lailis Syafaah,
Novendra Setyawan,
Yudawan Hidayat
Publication year - 2021
Publication title -
ijeis (indonesian journal of electronics and instrumentation system)/ijeis (indonesian journal of electronics and instrumentation systems)
Language(s) - English
Resource type - Journals
eISSN - 2460-7681
pISSN - 2088-3714
DOI - 10.22146/ijeis.64049
Subject(s) - histogram , artificial intelligence , computer science , pattern recognition (psychology) , rgb color model , pixel , artificial neural network , computer vision , image processing , image (mathematics)
Blood type in the medical world can be divided into 4 groups, namely A, B, AB and O. To be able to find out the blood type, a blood type test must be done. So far, human blood type detection is still done manually to observe the agglutination process. This research applies a blood type identification process using image processing. This system works by reading the blood type card image that has been filled with blood samples, then it will be processed through a histogram process to get the minimum and maximum RGB values and pixel locations which are then classified by Artificial Neural Networks (ANN) to determine the blood type from the training results and data matching. From the test results using 12 samples, it was found that the average error in blood type identification was 16.67%.