KLASIFIKASI GOLONGAN DARAH PADA CITRA KERTAS DIAGNOSA GOLONGAN DARAH MENGGUNAKAN CENTRALIZED BINARY PATTERN DAN BACKPROPAGATION

NABILLAH, RIZKA and Fachrurrozi, M. and Arsalan, Osvari (2019) KLASIFIKASI GOLONGAN DARAH PADA CITRA KERTAS DIAGNOSA GOLONGAN DARAH MENGGUNAKAN CENTRALIZED BINARY PATTERN DAN BACKPROPAGATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Blood type is crucial for transfusion since the donor's and the recipient's blood type must be the same. Blood types can be classified based on image patterns of blood groups. Classification of blood groups is not a simple matter because the features of one blood type image have similarities with features of another blood type. In addition, blood that has been dripped with reagents also has a different clotting pattern. This study discusses the classification of blood type images by the Centralized Binary Pattern (CBP) and Backpropagation (BP) methods. First, the image of blood type is done by a pre-processing process which consists of grayscaling and segmentation. After that feature extraction is done using Centralized Binary Pattern (CBP) then the training and testing process is carried out with Backpropagation (BP). The software is built using the Rational Unified Process (RUP) approach. The test results with the developed software are able to classify the image of blood type with the greatest percentage of accuracy, which is 45% using a split validation 0.5 learning rate 1 and epoch 1000. Keywords : Classification of Blood Type Images, Backpropagation (BP), Centralized Binary Pattern (CBP) and blood type

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ilmu Komputer, Teknik Informatika
Subjects:	Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4650-4675 Pictures. Photographs
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 1789 not found.
Date Deposited:	10 Sep 2019 07:55
Last Modified:	10 Sep 2019 07:55
URI:	http://repository.unsri.ac.id/id/eprint/6930

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