Forecasting Number of COVID-19 in Bali Province Using Neural Network Algorithm

Ida Ayu Dian Kusuma Dewi, I. K. N. A. Jaya, Kadek Oky Sanjaya
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Abstract

COVID-19 (coronavirus disease 2019) is a large family of viruses that cause mild to severe illness, such as the common cold or colds and serious illnesses such as MERS and SARS. COVID-19 has become a pandemic, meaning that there has been an increase in cases of the disease which is quite fast and there has been spread between countries and caused enormous losses in various countries. The increasing number of COVID-19 cases every day in Indonesia, including in Bali Province and the resulting losses underlie the forecasting of the number of COVID-19 in Bali Province. Forecasting is carried out using the Neural Network algorithm for time series data on the number of COVID-19 in Bali Province. The data used is data on the number of COVID-19 in the Bali Province in the form of time series data sourced from the Bali Provincial Health Office. The entire forecasting process uses the Rapidminer Studio tools starting from preprocessing, modeling, testing and validation. The results of the RMSE (Root Mean Square Error) evaluation value based on testing for the positive patients were 18.956, the patients recovered were 15.413, the patients under treatment were 5.066 and the patients who died was 0.233.
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基于神经网络算法的巴厘省新冠肺炎病例预测
COVID-19(冠状病毒病2019)是一大类病毒,可引起轻微至严重的疾病,如普通感冒或感冒,以及中东呼吸综合征和非典型肺炎等严重疾病。COVID-19已经成为一种大流行,这意味着疾病病例的增加速度非常快,并且在国家之间传播,给各国造成了巨大损失。印度尼西亚(包括巴厘省)每天新增的COVID-19病例数量不断增加,由此造成的损失是预测巴厘省COVID-19病例数量的基础。利用神经网络算法对巴厘岛省COVID-19病例数的时间序列数据进行预测。所使用的数据是来自巴厘省卫生局时间序列数据形式的关于巴厘省COVID-19病例数量的数据。从预处理、建模、测试到验证,整个预测过程都使用Rapidminer Studio工具。检测阳性患者的RMSE(均方根误差)评价值为18.956,康复患者为15.413,治疗患者为5.066,死亡患者为0.233。
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