The collected mineral potential prediction data will be made into an interactive map, so that it will help users in exploring mineral potential in Indonesia.

The G-Mine database standard will be developed through this process to produce mineral potential prediction, which is the processing of geophysical anomaly data, geological data of research locations, and mineral potential databases.

The data that has been collected is loaded and processed using geophysical software and generated geophysical anomaly data that can be interpreted.

The data collected comes from data obtained in the field using geophysical methods, geological data on research locations, and data on mineral potential from the ministry of energy and natural resources.

Research of G-Mine is the result of various literature studies that we have conducted through journals and papers by previous research. So, we also make this research based on existing scientific studies.

Indonesia is a country that has a fairly high level of vegetation density, it making difficult to approach using remote sensing or similar methods. Until now, there hasn’t been a comprehensive integration of geological and geophysical data that can help to delineate an area of ​​potential mineral deposits. Then coupled with the not yet massive use of technology applications (machine learning, artificial intelligence, deep learning) in helping to predict the potential for mineral deposits. Therefore, the aim of our research is to research and design solutions related to mineral exploration in Indonesia using our website-based software called G-Mine.