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APPLICATION OF NEURAL NETWORKS ON BLOOD SERUM IMAGE FOR EARLY DETECTION OF TYPHUS

By Betty Purnamasari, Franky Arisgraha and Suryani Dyah Astuti

Abstract

Background: Typhus is a disease caused by Salmonella typhi, Salmonella paratyphi A Salmonella parathypi B, dan Salmonella paratyphi C bacteria that attacks digestive tract and caused infection in small intestine. The common test that performed in the laboratory is widal test. The result reading ofthe widal test still processed manually with looking the turbidity caused by the agglutination. Aim: The research was made to decrease human error by creating a program based on artificial neural network (ANN) with learning vector quantization (LVQ) method. Method: Input ofthis program is image ofblood serum that has reacted with widal reagen. Image procesing start with grayscaling, filtering, and thresholding. Result: Output of this program is divided into two classes, normal and typhus detected. Conclusion: From this experiment result that using 24 testing data, gives the accuracy ofthis program 95.833% with 1 error result from 24 testing data

Topics: Artificial Neural Network, Learning Vector Quantization, Salmonella, Typhus, Widal, Infectious and parasitic diseases, RC109-216
Publisher: Universitas Airlangga
Year: 2013
DOI identifier: 10.20473/ijtid.v4i4.234
OAI identifier: oai:doaj.org/article:c3b7a16c2eeb4e94a71cca3a6603459e
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