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Formosa Journal of Computer and Information Science
Published by PT FORMOSA CENDEKIA GLOBAL
ISSN : -     EISSN : 28303040     DOI : https://doi.org/10.55927/fjcis.v1i2.1151
Core Subject : Science,
Computer Science & IT
Formosa Journal of Computer and Information Science (FJCIS) is an international platform for scientists, academics, practitioners and engineers involved in all aspects of computer science and information sciences to publish high quality, up todate, peer review papers. It is an international research journal sponsored by Formosa Publisher. The journal provide a platform for survey, research and review articles from experts in the field, promoting insight and understanding of the state of the art, and trends in computer and information sciences. The contents include original research and innovative theory and applications from all parts of the world. The journal publish articles twice in a year (March and August).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 61 Documents
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Blood Type Identification System in Humans Based on Digital Image Processing Muzaki Muaki; Aeri Rachmad; Indra Indra; Irfan AP
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16641

Abstract

Humans strive to imitate expertise through artificial intelligence approaches, including in medical diagnosis such as distinguishing human blood types A, B, AB, and O. Artificial Neural Networks (ANN) have been developed as a generalization of mathematical models of human learning. This paper discusses the development of ANN software to detect human blood types through recognition of clotting patterns. The clotting patterns of the four blood types can be distinguished well by experts. ANN with the backpropagation learning method is applied as expert learning to recognize blood types based on the clotting pattern formed after antigen reagents are administered. Several image pre-processing stages are used, including edge detection and feature extraction, to improve the recognition process and support accurate blood type identification through artificial intelligence techniques.

Page 7 of 7 | Total Record : 61

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