Building Predictive Model of Covid 19 Quarantine Impact on the Purchase of Environmentally Green Products by Using J48 and LMTAlgorithms

Mutasim Al Sadig, Nahid Osman Ali Babikir, Faisal Mohammed Nafie Ali,Khalid Nazim Abdul Sattar

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY(2022)

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摘要
When COVID 19 pandemic appeared, World Health Organization officially announced on January 30, 2020, that the outbreak of the virus constituted a health emergency, and most countries of the world announced a quarantine of all citizens as one of the precautionary to limit the epidemic spread. The Kingdom of Saudi Arabia is one of the countries that announced quarantine, which had an impact on all aspects of life. This study is related to the impact of quarantine on the purchase of green products and effects on the environment, that by using machine learning algorithms. J48 and ML algorithms were used to Build a predictive model to estimate the effect of the quarantine for covid 19 on the purchase of environmentally friendly food products that in Zulfi region of the Kingdom of Saudi Arabia and found that J48 algorithm have highest performance compared to LMT algorithm.
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关键词
green products, COVID-19, Classification, WEKA, environment
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