Big Data Integration Design for General Election in Indonesia

The use of big-data analysis in elections in Indonesia has been started since the Governor Election of DKI-Jakarta in 2012 until the Presidential Election in 2019. However, its use is limited to using analytical sentiment to map support and predict election results using social-media data. We see that there is a great opportunity to use big data for a broader election, which is to facilitate the fulfillment of the information and analysis needs of all election stakeholders. But the main problem in using big-data is the integration of big data from various sources with a variety of different formats and large volumes, in addition to the issues of analysis and visualization. For this reason, in this paper, we propose a big-data integration design to meet the needs of elections in Indonesia. This big-data integration design was developed based on election regulations in Indonesia, knowledge of big-data, and the use of a NoSQL database to store unstructured data. The election big-data integration design that we propose includes (1) the information needs of each election stakeholder; (2) the potential for big-data in fulfilling the information needs of every election stakeholder; (3) big-data analysis architecture for elections; (4) big-data integration architecture for elections; (5) crawler architecture; and (5) technology architecture that can implement big-data integration design for elections. Currently, the implementation of this design is in progress in the P3MI-ITB research project.