Euis Saraswati, Yuyun Umaidah, A. Voutama
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引用次数: 7

摘要

冠状病毒病(Covid-19)或通常称为冠状病毒。这种病毒传播非常迅速,甚至几乎感染了整个世界,包括印度尼西亚。大量的病例和病毒的快速传播使人们担心甚至害怕新冠病毒的日益传播。关于这种病毒的信息也在各种社交媒体上传播,其中之一就是推特。关于新冠病毒的各种舆论也在推特上广泛表达。推特上的观点包含积极或消极的情绪。推文中包含的情绪可以作为政府应对新冠病毒时考虑和评估的材料。基于这些问题,需要进行情绪分析分类,以找出对新冠病毒的民意。本研究采用反向传播的人工神经网络(ANN)算法。准确率为88.62%,精密度为91.5%,召回率为95.73%。结果表明,该人工神经网络模型对文本挖掘分类具有较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penerapan Algoritma Artificial Neural Network untuk Klasifikasi Opini Publik Terhadap Covid-19
Coronavirus disease (Covid-19) or commonly called coronavirus. This virus spreads very quickly and even almost infects the whole world, including Indonesia. A large number of cases and the rapid spread of this virus make people worry and even fear the increasing spread of the Covid-19 virus. Information about this virus has also been spread on various social media, one of which is Twitter. Various public opinions regarding the Covid-19 virus are also widely expressed on Twitter. Opinions on a tweet contain positive or negative sentiments. Sentiments of sentiment contained in a tweet can be used as material for consideration and evaluation for the government in dealing with the Covid-19 virus. Based on these problems, a sentiment analysis classification is needed to find out public opinion on the Covid-19 virus. This research uses Artificial Neural Network (ANN) algorithm with the Backpropagation method. The results of this test get 88.62% accuracy, 91.5% precision, and 95.73% recall. The results obtained show that the ANN model is quite good for classifying text mining.
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