Computational science in general emerged many decades ago enhancing theory and experiment. Specifically, computational geography arose in the 1980s due to the reductionist limitations of initial GIS software constraining deep analyses of rich geographic data. The utilization of computational method for spatial data analysis has become more probable with the emergence of relational databases. The main purpose of this review is to discuss the application of computational technique and geocomputation in the spatial analysis of geographical phenomenon. First, the literature search and data synthesis was conducted. Then, discussion was done on computational method, geocomputation, spatial data representation, storage, and organization, spatial analytics, and GeoAI. Summarily, geocomputation as concept has been used to define the application of computer-intensive approaches to discern knowledge, especially those that apply non-conventional data clustering and analysis methods. Nowadays, computational method and geocomputation can be used to integrate many areas or fields to enable spatial analyses that require computational resources or ontological paradigms that may not be found in the traditional GIS software suites.