Penerapan Model Cased Based Reasoning Dalam Diagnosa Penyakit Menular pada Bayi di Rumah Sakit Cut Meutia

Mauliza Mauliza, T Iqbal Faridiansyah

Sari


Information technology has developed very rapidly, especially in the health sector so that it can help doctors' performance in treating patients more effectively and efficiently. Technological developments in the health sector also from now on have started many new innovations, especially in curing infectious diseases in infants. infants at a young age are very susceptible to disease, especially infectious diseases. The disease is very dangerous for humans because it can be transmitted quickly through touch, saliva, air or other intermediaries. Limited information about infectious diseases, especially those that affect toddlers, is a problem and makes it difficult for parents to predict what diseases are affecting children. The purpose of this study is the existence of a model built with CBR can facilitate the steps of parents in diagnosing infectious diseases in infants; secondly, the existence of a system that is built can facilitate patients in monitoring the disease and the results used can be more measured by using a cased base reasoning model. Research methods collect data and information in the form of theories or methods or approaches that have developed and CBR models for infectious diseases in infants; the second is collecting infectious disease data in infants, symptom data, solution data and infectious disease
prevention data in infants. The research results are that a model built with CBR can facilitate the steps of parents in diagnosing infectious diseases in infants and the existence of a system so that it can facilitate patients in monitoring disease and the results used can be more measured by using a cased base reasoning model.


Kata Kunci


Expert System; cased base reasoning; Forecasting; Infectious Diseases; Double exponential smoothing

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Referensi


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