Utilizing Soft Computing for Determining Protein Deficiency
Abstract: In recent years, the
occurrence of protein shortage of children under 5 years old in many poor area
has dramatically increased. Since this situation can cause serious problem to
children like a delay in their growth, delay in their development and also
disfigurement, disability, dependency, the early diagnose of protein shortage
is vital. Many applications have been developed in performing disease detection
such as an expert system for diagnosing diabetics and artificial neural network
(ANN) applications for diagnosing breast cancer, acidosis diseases, and lung
cancer. This paper is mainly focusing on the development of protein shortage
disease diagnosing application using Backpropagation Neural Network (BPNN)
technique. It covers two classes of protein shortage that are Heavy Protein
Deficiency. On top of this, a BPNN model is constructed based on result
analysis of the training and testing from the developed application. The model
has been successfully tested using new data set. It shows that the BPNN is able
to early diagnose heavy protein deficiency accurately.
Author: Sri Hartati and Sri
Nurdiati
Journal Code: jptinformatikagg110005
