Visualization of Twitter Geo-location for Equalization Analysis of Smart Cities in Indonesia

Abstract

Indonesia has thousands of islands with 5 large island groups that are well known throughout the country. This then becomes a question of how capable Indonesia is to implement Smart City development in each of these regions. To answer this question, this study is designed to assist the government in analyzing the equal distribution of Smart City in Indonesia. The analytical material used was 381,362 Twitter data with the topic of Smart City by Drone Emprit. These tweets are grouped by region, province, and island. Drone Emprit has implemented several methods such as Machine Learning, Database Framework, Hadoop Framework, and Physical Hardware to visualize Smart City data spread throughout Indonesia. Seeing a tweet from an area indicates that the development of a Smart City has been implemented in that area. As a result, the islands of Sumatra and Sulawesi have achieved quite well, although they only cover 4 % and 2 % of the achievements of Java Island. Java Island has a dominance of 61 % with 2332 tweet data. The islands that never talk about Smart City are Kalimantan and Papua because these two islands have a percentage of talking about Smart City at exactly 0%. This data can be used by the government to pay more attention to the development of Smart City in areas that have a very small percentage.