NURUL HUSNA BINTI ROSLI
Nurul Husna binti Rosli is a final year student who currently pursuing her studies at Universiti Sains Malaysia in Computer Sciences course. She takes Information System Engineering as her major with a minor in Management. Hence, she had done her 6 months of internship as a web developer trainee at Pejabat Daerah dan Tanah Seberang Perai Selatan. During her time in undergrad, she participated in various of volunteering activities such as Penang International Science Fair and INTEL Aspire Minds Innovation Space Challenge 4.0 In her free time, Husna enjoys baking and watching movies!
Matrix No:
137149
Student Email:
Supervisor:
Dr. Pantea Keikhosrokiani
Supervisor Email:
SC046
Big Medical Data Mining System for COVID-19 with AI features: Big Med System
In last December of 2019, an outbreak of a new pandemic diseases called coronavirus disease (COVID-19) occurred. Hence, nowadays in the advancement of technology with the regard of the fourth industrial revolution fake news and misinformation of this pandemic disease has spread rapidly on social media. People tends to share information and news without verifying it with the authority on their social media platform. It is one of a quickest way for the people to interact and share breaking news with each other across the country. Some of the information are unfiltered and had reach out thousands of people. This had created unnecessary panic and fears to people across the nation.
Therefore, a web-based system name BigMed system is proposed to act as fake news detection tools of COVID-19 news. The detection of fake news used passive-aggressive algorithm from classifying 1000 of data. Hence this system also comes with other features such as providing genuine information of COVID-19 disease such as displaying daily cases, displaying preventive measure that could be taken to prevent COVID-19 disease from spreading . Finally this project will be useful to give users regarding COVID-19 and use it as a reference anytime.
