Prediction On Drug Abused Before Quarantine Of The Pandemic Covid-19 In Malaysia (2000-2019)

Mohamad Iqbal, Abdullah (2023) Prediction On Drug Abused Before Quarantine Of The Pandemic Covid-19 In Malaysia (2000-2019). Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.

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In 2020, a new virus made a big impact on all people around the world, with the first cases identified on the 12th of December, 2019 in Wuhan City, Hubei Province in China which known as the Coronavirus Virus Disease 2019 that forced almost all nations to make a lockdown to control the virus from the spread and causes more damages not only to the industry but also the mental health of people. This is quite worrisome as it might cause the increase of drug abusers among Malaysian because, over the five years, the number of drug abuse decreases very slowly and might be increasing during the lockdown due to the pandemic. This study aims to predict drug abuse before the quarantine of the pandemic COVID-19 in Malaysia. In this context, drug abuse means the person who uses the drug either prescription or over-the-counter by other means from what of their purposes. To test the prediction on what drug will be abused by the Malaysian, a data mining method has been used to get the result. The method used are Linear Regression and Random Tree, an Unsupervised Machine Learning from the Regression to predict drug abuse which is how many drug abusers will be in Malaysia that required variables from datasets such as year, value and etc. The results show that the prediction used is almost 80% accurate from the datasets that have been used. These results suggest that the potential drug abuse is more likely to be unchanged or might increase in response to the many factors, especially mental health, by the COVID-19 and its variants.

Item Type: Undergraduates Project Papers
Additional Information: SV: Dr. Nabilah Filzah Binti Mohd Radzuan
Uncontrolled Keywords: mental health, drug abuse
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computing
Depositing User: Mr. Nik Ahmad Nasyrun Nik Abd Malik
Date Deposited: 07 Feb 2024 03:44
Last Modified: 07 Feb 2024 03:44
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