Publication Search

This study aims to investigate the factors influencing the continuance intention of Al-Kautsar Senior High School students in using metaverse-based learning media. The background of this research lies in the rapid adoption of immersive technologies in education, while students’ levels of acceptance have not yet been fully understood. The objective is to identify the antecedents of satisfaction, which subsequently influence continuous intention. The research model examines the effects of perceived interactivity, perceived sociability, perceived enjoyment, perceived ease of use, perceived security, and social influence on satisfaction. A quantitative approach was employed by distributing questionnaires to students, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that satisfaction is a very strong and statistically significant predictor of continuous intention to use metaverse applications (β = 0.716, p < 0.001). The six hypothesized antecedent variables were not found to have a significant individual effect on satisfaction. In conclusion, for digital native students at Al-Kautsar Senior High School, factors such as ease of use, interactivity, and enjoyment have shifted from being drivers of satisfaction to becoming basic expectations (hygiene factors). Satisfaction itself emerges as the primary determinant, likely influenced by more substantive elements such as content quality or pedagogical design rather than merely the technical features of the platform.

When creating databases for GIS-applications often existing maps are scanned and vectorised for used. However, vectorisation becomes obsolete when GIS-objects can be referred to both in theme and geometry in a raster environment. This article shows to use model spatial data raster and vector for GIS - applications in both the graphical and image structure. Geographical data must first be converted into a computer- readable format before it can be used in a GIS. Spatial data are "elements that can be stored in map form." These elements correspond to a uniquely defined location on the Earth's surface. Spatial data have also been describe as “any data concerning phenomenon a really distributed” in two or more dimensions. (Peuquet and Marble, I990.) Data model is the rules to convert real geographical variation into discrete objects. There are two main GIS data models - vector and raster. Each of the two data models has specific types of data, analysis and displays that can handle better than the other system. The vector model represents geographical reality as a series of discrete objects or features, classified as points, line's or areas (polygons). The geographical co-ordinates describing the locations of these features are stored in the computer database which lies at the heart of the GIS. In the raster model a regular grid of cells, or pixels, is used to encode the features found on the earth's surface. Each pixel has a number associated with it representing; the value of a geographical phenomenon, such as terrain elevation, soil type or biomass. Layers of raster grids covering the same region can be built up to represent further variables.