Nowadays, students have learn to accept the reality of online learning. Therefore, this quantitative study aims to explore how behaviour and social factors can influence online learning. 203 participants responded to the instrument which is a survey. The findings show that the implication of online and distance learning (ODL) is to help students in getting to know each other as well as having the social, cognitive and situational presence. The instrument of teaching, social and cognitive presence based on Social Cognitive Theory (SCT) is measured in order to improve the management of ODL in university during post-COVID-19 pandemic. The first research question looks at how behaviour factors (social presence) influence online presence. Next the study also investigates how cognitive factors influence online presence. The final research question looks at how situational factors (teaching presence) influence online presence. In overall, ODL management in post-COVID-19 pandemic is expected to be more challenging than during or before the pandemic. The shift that happen caused a lot of physical, mental, and emotional responses from the teaching and learning community in general. Instrument teaching, social and cognitive presence are investigated thoroughly and interesting results found in this study is beneficial for future decision support system (DSS) development in the case for community of inquiry.

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Replicated linear functional relationship model is often used to describe relationships between two circular variables where both variables have error terms and replicate observations are available. We derive the estimate of the rotation parameter of the model using the maximum likelihood method. The performance of the proposed method is studied through simulation, and it is found that the biasness of the estimates is small, thus implying the suitability of the method. Practical application of the method is illustrated by using a real data set.

For years, researchers have been studying the factors that influence stock market performance. Typically, it concentrates on Malaysia's macroeconomic conditions. The goal of this study is to close the gap by examining the elements that influence the stock market's production in Malaysia. More precisely, it includes real exchange rate, money supply, inflation rate inflation rate and US stock market in measuring their relationships with the performance of the Malaysian stock market price. This analysis attempts to expand the existing literature. It will focus on the industrial products and services sector and will collect Bursa Malaysia data as a dependent variable sample. World Bank Data were collected for independent variable data on monthly basis from 2016 until 2020. Based on the results, three out of four variables were found to be significant. Real exchange rate, money supply, and the performance of the US stock market were either substantially negative or positive in comparison to the performance of the Kuala Lumpur Industrial Product (KLIP) stock market. On the other hand, there was an insignificant relationship between the Kuala Lumpur Industrial Product (KLIP) stock market and inflation rate (CPI).

In studies of potential wind energy, knowing statistical distribution of wind direction provides useful information in making predictions and gives a better understanding of the behavior of the wind direction. Malaysia experiences two monsoon seasons per year, namely Southwest Monsoon and Northeast Monsoon and in this paper, our interest is to investigate whether the direction of wind data in monsoon seasons can be modelled using replicated LFRM with von Mises distribution. The beauty of this model is that it considers the error terms in both x and y variables. This study considers the bivariate relationship of directional wind data where errors are present in both. Here, we propose a replicated functional relationship model, with the von Mises distribution to describe the relationship of the wind direction data. In the parameter estimation, maximum likelihood method is considered with pseudo-replicated group of the replicated form of the functional relationship. The novelty of this approach is that assumption on the ratio of concentration parameters is no longer deemed necessary. Also, we derive the covariance matrix of the parameters based on Fisher Information. From the Monte Carlo simulation study, small bias measures were obtained, suggesting the viability of the model. Based on the simulation study, it can be concluded that the wind direction of the two monsoons in Malaysia can be modelled using replicated linear functional relationship model.