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The COVID-19 pandemic, which began in Wuhan City, China in 2020, has thrown Malaysia's academic sector into disarray. Students' academic performance changes dramatically when they move from face-to-face classes to full implementation of online distance learning (ODL). The purpose of this study is to investigate the factors that affect students' academic performance during the COVID-19 pandemic using Multiple Linear Regression (MLR). The research was carried out at UiTM Perlis Branch, and 54 bachelor's degree students from four faculties were invited to take part. During the analysis, gender, hours students spent in online learning, hours students spent on preparation before class, number of subjects taken, credit hours, hometown areas and internet connection, act as independent variables whereas CGPA as the dependent variable, were examined. This study was carried out using SPSS software and Excel. The result shows that the hometown areas and hours students spent preparing before class contributed significantly to the model while others did not. It is shown that students who live in rural areas did much better in academic performance than students who live in cities, and the more students spend on preparing themselves before class, the lower is their CGPA. Other factors tend to be insignificant and it might be because of the limited time in collecting data, small sample size and unequally-sized groups. For future research, it is recommended to have more time in collecting data and add more sample sizes by extending it to diploma students to gain more accurate results.

This study describes the problem with the knapsack that occurred in the cargo flow. The problem of the knapsack is the problem of optimisation used to illustrate the problem and the solution in which each set of items has its own specific value and weight. With its total value as much as possible, the number of items that may become less or at least equal to or equal to the limit. Therefore, the aim of this study is to determine the minimum total cost of 30 shipments based on volume by using Artificial Bee Colony (ABC) algorithm in order to achieving the highest profit. ABC algorithm was derived from the bee colony which consists of four phases of initialisation, employed bees, onlooker bees and scout bees. Based on the result obtained, the total cost of the shipment is 402.377 tons per km which starting from the Shipment 25 with 2 560 000 tons per year for 0.111 tons per km and ends with Shipment 21 with 2 250 000 tons per year for 0.129 tons per km.