COVID-19 Incidence Prediction Model Based on Community Behavior With Neural Networks
Keywords:Behavior prediction model, COVID-19 incidence, Neural network
BACKGROUNDS : The COVID-19 pandemic has created a global health emergency that requires a public health response to prevent the spread of the virus.
AIM: The purpose of this study was to determine the prediction model for the incidence of COVID-19 based on community behavior.
METHODS: This study used a cross-sectional study design. The study population was all people aged >18 years in Medan City and obtained a sample of 395 people with stratified random sampling technique. The research instrument used a questionnaire in google form, then, using Microsoft Office Excel, we transferred the data from the survey to a computer program. Furthermore, the data was analyzed using the neural networks method. Then the features importance will be calculated using the Random Forest with Mean Decrease Impurity (RF-MDI) method.
RESULT: The results showed that based on the confusion matrix, the prediction value for those who did not suffer from COVID-19 was correct from negative data = 8, the correct prediction value for COVID-19 from positive data = 8. While the incorrect prediction value for machines that predicted negative results but the actual data was positive = 2, and predicts a positive result but the actual data is negative = 4. Thus, based on the neural net classification method, the accuracy value is 72%. The results of this study indicate that poor preventive behavior by the community greatly affects the spread of COVID-19 cases.
CONCLUSION: Poor community behavior, such as not limiting their interaction/contact with other people, not exercising frequently, leaving the house without keeping a safe distance, and not washing hands regularly, can all impact COVID-19 transmission in the community
Keywords: Behavior Prediction Model, COVID-19 Incidence, Neural Network
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Copyright (c) 2022 Victor Hulu, RNS Fransiska, Widya Yanti Sihotang, Suharni Sinaga, Frans Judea Samosir, Astaria Br Ginting, Riska Wani Eka Putri, Lam Murni Br Sagala, Yuni Vivi Santri P, Nurhamida Fithri, Faradita Wahyuni, Putranto Manalu (Author)
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