Komparasi Paket R untuk Analisis Data Spasial dalam Penelitian Sosial

Abstract

This study examines a comparison of R packages used in spatial data analysis, with a focus on the sp, sf, raster, terra, and ggmap packages. Each package offers varying features, performance, and ease of use, which affect the effectiveness and efficiency of spatial data analysis. By utilizing diverse datasets, the researchers evaluate the strengths of each package in terms of vector data manipulation, raster data handling, and map visualization. The sp package, as one of the earliest packages for spatial data analysis in R, provides a solid foundation but has limitations in supporting modern data formats and efficiency. The sf package offers comprehensive support for the Simple Features standard, enhancing usability and performance for vector data with better integration into the R ecosystem. The raster package provides reliable tools for raster data manipulation and analysis, but it faces challenges in efficiency and ease of use with large datasets. The terra package addresses these shortcomings by improving efficiency and capabilities in handling large datasets and performing faster operations. On the other hand, the ggmap package offers powerful tools for interactive map visualization and web-based map data access, which are particularly useful for creating informative and interactive maps. The findings of this study provide practical guidance for researchers and practitioners in selecting the appropriate R package for their analysis needs. The study concludes that the choice of package should consider the type of data being analyzed, the goals of the analysis, and the features and performance of each package to ensure optimal results in spatial data analysis