Issue |
MATEC Web of Conferences
Volume 58, 2016
The 3rd Bali International Seminar on Science & Technology (BISSTECH 2015)
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Article Number | 03005 | |
Number of page(s) | 5 | |
Section | Information Technology and Information Systems | |
DOI | https://doi.org/10.1051/matecconf/20165803005 | |
Published online | 23 May 2016 |
Forecasting the Number of Patients Diseases Using Backpropagation
Faculty of Engineering, University of Trunojoyo Madura, Indonesia
Email: aery_r@yahoo.com
Forecasting with various types of disease is important for health centers, because it can be used to help the health center management in conducting strategic planning and decision making. Health Care Center Torjun in Indonesiahas made estimationabout the number of patients with various types of diseases, such as Acute Respiratory Infections(ISPA), RA(Rheumatoid Arthritis), diarrhea, HT(Hypertension), Skin Allergies, Conjunctivitis, Asthma, Febrile, TB(Tuberculosis). Lung, scabies, Gastritis, typus and scarlet fever with reports the number of patients with certain diseases in the coming period and prepare the necessary needs both medical services and as well as drugs for use later. In this study, Artificial Neural Network (ANN) is one model that is used to identify patterns of images of people with various kinds of diseases. Backpropagation is one of the popular models of Neural Networkwhich is used for forecasting, prediction, and decision makers based on the input of data entry that has been studied in advance. The resultsis HT (0.35 %)with parameters for forecasting system using Neural Network Backpropagation is the best of the trial results that shows disease HT which are obtained from the experiments. They predict the number of patients with a disease that needs to be watched for in the coming period and prepare all the needs of both medical and medication needed to handle the number of people with the disease.
Key words: Forecasting / Health Care Center / Diseases / Backpropagation
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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