Covid19 and Higher Education: A Degree Course Recommender System Based on Personality Using Rule-Based

As a result of the pandemic Covid19 and the enforcement of Movement Control Order (MCO) in Malaysia, it is difficult for the Ministry of Education to explain the selection of courses at the university. Current systems such as “Selangkah ke UiTM,” “eSemak Politeknik” and “EduAdvisor” concentrate only on SPM graduates. As a result, this study proposes a recommendation system that can provide recommendations for the course to suit students’ personalities. Diploma of Computer Science students from the Faculty of Computer and Mathematical Science (FSKM) at UiTM Melaka are selected as a case study. This system uses the rule-based approach that took psychometric test results: “Inventori Minat Kerjaya” and mapped it to the traits needed for the five courses offered at the faculty to help students determine the most appropriate course. This prototype system consists of 170 test questions, and the results of the top 3 IMK personalities are chosen to be mapped to the courses offered. Usability and accuracy testing has been carried out at an average rate of 77.5%, and accuracy is 66.7%.

A Social Media Mining Using Topic Modeling and Sentiment Analysis on Tourism in Malaysia During Covid19

Malaysia’s tourism is affected by the Covid19 pandemic and the MCO implementation, where borders are closed and non-essential activities are halted. Negative effects are also felt by Malaysians and are reflected in social media. This study examines two research questions, finding the issues that Twitter users have been addressing on tourism activities during the MCO period and analyze users’ sentiment regarding their ability to travel after MCO. 5000 data were extracted manually from 11357 data scraped from Twitter, of which 3243 were pre-processed keywords using RapidMiner. The results show that the topic of the debate focuses on three themes, namely the destination of tourism, future planning, and public emotions. In addition, 63% gave a positive view and 22% negative sentiment on domestic tourism. Overall, users of Twitter gave an optimistic outlook on domestic travel and hoped that Covid19 would soon be over.

In silico molecular docking and molecular dynamic simulation of potential inhibitors of 3C-like main proteinase (3CLpro) from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) using selected african medicinal plants

The Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is an infectious virus that causes mild to severe life-threatening upper respiratory tract infection. The virus emerged in Wuhan, China in 2019, and later spread across the globe. Its genome has been completely sequenced and based on the genomic information, the virus possessed 3C-Like Main Protease (3CLpro), an essential multifunctional enzyme that plays a vital role in the replication and transcription of the virus by cleaving polyprotein at eleven various sites to produce different non-structural proteins. This makes the protein an important target for drug design and discovery. Herein, we analyzed the interaction between the 3CLpro and potential inhibitory compounds identified from the extracts of Zingiber offinale and Anacardium occidentale using in silico docking and Molecular Dynamics (MD) Simulation. The crystal structure of SARS-CoV-2 main protease in complex with 02J (5-Methylisoxazole-3-carboxylic acid) and PEJ (composite ligand) (PDB Code: 6LU7, 2.16 Å) retrieved from Protein Data Bank (PDB) and subject to structure optimization and energy minimization. A total of twenty-nine compounds were obtained from the extracts of Z. offinale and the leaves of A. occidentale. These compounds were screened for physicochemical (Lipinski rule of five, Veber rule, and Egan filter), Pan-Assay Interference Structure, and pharmacokinetic properties to determine the Pharmaceutical Active Ingredients. Of the 29 compounds, only nineteen (19) possessed drug-likeness properties with efficient oral bioavailability and less toxicity. These compounds subjected to molecular docking analysis to determine their binding energies with the 3CLpro. The result of the analysis indicated that the free binding energies of the compounds ranged between − 5.08 and − 10.24 kcal/mol, better than the binding energies of 02j (− 4.10 kcal/mol) and PJE (− 5.07 kcal/mol). Six compounds (CID_99615 = − 10.24 kcal/mol, CID_3981360 = 9.75 kcal/mol, CID_9910474 = − 9.14 kcal/mol, CID_11697907 = − 9.10 kcal/mol, CID_10503282 = − 9.09 kcal/mol and CID_620012 = − 8.53 kcal/mol) with good binding energies further selected and subjected to MD Simulation to determine the stability of the protein–ligand complex. The results of the analysis indicated that all the ligands form stable complexes with the protein, although, CID_9910474 and CID_10503282 had a better stability when compared to other selected phytochemicals (CID_99615, CID_3981360, CID_620012, and CID_11697907). © 2020, Institute of Korean Medicine, Kyung Hee University.