| Abstrakt: |
Along with the development of data science, of course, there are also various innovative solutions to support data processing. These solutions often bring with them new data science trends that are rapidly changing the way we work and live our lives. The trend of data science is using a small dataset, which has a smaller volume and is easy to access and process. It is energy-efficient, has lower costs, and can work without an internet connection. Some of the research is to create tools and platforms that anyone can use to build their own Machine Learning (ML) applications. Currently, there are many innovations in big data processing that are rooted in geospatial data. Everyone carries at least one piece of hardware that monitors their movements that generate spatial data. Also, the drone and IoT industries are highly developed and collect spatial data in real-time. So, there is a lot of data available that is rooted in spatial data. The approach in this research will be utilizing the Geospatial tools for data science to work with vector and raster data types and how to manipulate them, implement time series analysis on maps and perform geospatial analysis using vector data. [ABSTRACT FROM AUTHOR] |
