Ali Ali

Rapid advancements in information technology have significantly changed in various aspects of life, including in the fields of economics and investment. Metaverse, a concept of a virtual world that allows for social, economic, and cultural interactions in a digital environment, has emerged as one of the most prominent innovations in recent years. The millennial generation, often referred to as digital natives, has shown a strong interest in adopting this new technology. However, many millennials still do not know how to invest through technological advancements in the metaverse. The purpose of this study is to analyze the variables that influence the interest of the millennial generation in metaverse investment. This study uses a quantitative method with respondents who are millennials in Jepara Regency aged 19–21 years. The sampling technique uses purposive sampling. Data were collected through a questionnaire with a google form distributed to 92 millennial respondents spread across Jepara Regency. Respondent data were analyzed with the help of analysis software. The results showed that 72% of the millennial generation in Jepara Regency were interested in utilizing technological advances properly, one of which is by investing through the metaverse. The findings indicate a clear interest and effort among millennials in Jepara Regency to invest in the metaverse. This study may contribute to strategies aimed at increasing millennial participation in metaverse-based investment in the region.

In this paper, we present an intensive investigation of the finite volume method compared to the finite difference methods. In order to show the main difference in the way of approaching the solution, we take the Burgers equation and the Buckley–Leverett equation as examples to simulate the previously mentioned methods. On the one hand, we simulate the results of the finite difference methods using the schemes of Lax–Friedrichs and Lax–Wendroff. On the other hand, we apply Godunov’s scheme to simulate the results of the finite volume method. Moreover, we show how starting with a variational formulation of the problem, the finite element technique provides piecewise formulations of functions defined by a collection of grid data points, while the finite difference technique begins with a differential formulation of the problem and continues to discretize the derivatives. Finally, some graphical and numerical comparisons are provided to illustrate and corroborate the differences between these two main methods.