The main objective of this research is trying to investigate the benefits of machine learning implementation in large genomics data analysis. High dimensionality is one criteria which consequently make genomics data hard to be analysed. Currently, statistical approach is still the first choice of method to analys this data. However, computational power can limit the performance of this method. Therefore, an alternative method using machine learning approach has to be proposed to carefully mine important and useful information from genomics data. This proposed method can potentially provide a good quality knowledge base that can support researchers and physicians decision making that leads to the enhancement of health services quality. Besides of that, interpretability is also another important factor in proposing the method. A good method has to provide additional information which explain the predictive capability.This research can be theoretically give a new perspective in treating genomics data as a machine learning object.

AI, health informatics, medical informatics, data integration, machine learning

• Siti Safariana Rahmawati, S.Kom., M.TI.

• Arif Budiarto, S.Kom, M.Sc.