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Predicting the Pandemic Effect of COVID 19 on the Nigeria Economic, Crude Oil as a Measure Parameter Using Machine Learning

In: Decision Sciences for COVID-19

Author

Listed:
  • Cecilia Ajowho Adenusi

    (Nigeria Master Affiliate)

  • Olufunke Rebecca Vincent

    (Federal University of Agriculture)

  • Jesufunbi Bolarinwa

    (Federal University of Agriculture)

  • Ologunye Oluwakemi

    (Redeemer University)

Abstract

The spread of the Covid-19 pandemic in Nigeria has had a great impact on the economy. Prior to 2019, the crude oil price (US $/l) ranged from 62 to 79.59 starting in 2018. The year 2019 ranges between 59.1 to 73.65 per barrel. It will be between 14.28 and 66.65 per barrel in 2020. The Covid-19 pandemic will commence around December 2019 in China before being discovered outside China in the year 2020. Because of the aforementioned crude oil prices, crude oil prices increased until the year 2020, when there was a total lockdown on the export of oil products, causing crude oil prices to fall. This study investigates the impact of the pandemic on the Nigerian economy, utilizing crude oil as a good parameter measure. This was achieved by using a machine model (random tree) for prediction, and the results were further compared (Sequential Minimal Optimization (SMOreg), decision table, Random Forest, M5 tree model (M5P) and Gaussian Processes) for better accuracy. The results obtained thus far from the combination of datasets used can be used to manage the Nigerian economy, particularly the crude oil industry, in search of ways to mitigate the damage caused by the pandemic.

Suggested Citation

  • Cecilia Ajowho Adenusi & Olufunke Rebecca Vincent & Jesufunbi Bolarinwa & Ologunye Oluwakemi, 2022. "Predicting the Pandemic Effect of COVID 19 on the Nigeria Economic, Crude Oil as a Measure Parameter Using Machine Learning," International Series in Operations Research & Management Science, in: Said Ali Hassan & Ali Wagdy Mohamed & Khalid Abdulaziz Alnowibet (ed.), Decision Sciences for COVID-19, chapter 0, pages 79-93, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-87019-5_5
    DOI: 10.1007/978-3-030-87019-5_5
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