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Big Data for Government Policy: Potential Implementations of Big Data for Official Statistics in Indonesia


Big Data for Government Policy: Potential Implementations of Big Data for Official Statistics in Indonesia

Big Data is an umbrella term for explosion in the quantity and diversity of high frequency digital data and it is not usually coming from traditional sources. The speed and frequency by which data is produced and collected—by an increasing number of sources—is responsible for today’s data deluge: the amount of available digital data is projected to increase by an annual 40%. “Big Data for Development” is a concept that refers to the identification of sources of Big Data relevant to policy and planning of development programmes. It differs from both “traditional” development data and what the private sector and mainstream media call Big Data. Potential applicability of “Big Data for Development” at the most general level, when it is properly analysed, these new data can provide snapshots of the well-being of populations at high frequency, high degrees of granularity, and from a wide range of angles, narrowing both time and knowledge gaps.

This research discussed several possible implementations of Big Data to the official statistics in Indonesia. Furthermore, three case studies would be discussed: (1) predicting inter-city commuting patterns using twitter, (2) developing a statistical model to nowcast food prices using crowd sourcing, and (3) Mobile Position Data for Tourism Statistics.

The results show similar trend between crowdsourcing approach and BPS Survey for all commodities, between the twitter approach and the commuter survey 2014. For the MPD approach for tourist statistics, the number of visits based on the roaming and the visits based on the immigration are similar. The study reveals potential implementations of Bigdata in complementing official statistics for government policy in Indonesia.

Presented at the International Workshop on Big Data and Information Security (IWBIS). IWBIS  Universitas Indonesia (UI).



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October 4, 2017 Posted by | bigdata, Uncategorized | Leave a comment