Clustering of Citizen Science Prospect to Construct Big Data-based Smart Village in Indonesia

Abstract

The development of citizen science as the foundation of a smart village is one of the solutions to reduce poverty in rural areas. The main objective of this research is to map the prospect cluster of citizen science to construct big data-based smart villages in Indonesia. This research was conducted through a cluster analysis of 2018 village potential data in Indonesia, using a combination of k-means, expected maximum and density-based algorithms. The contribution of this research resulted in a map of prospect of citizen science clusters for smart villages in 33 provinces in Indonesia. The data used was limited to village administrative areas, so DKI Jakarta was not included in this study. The main factors that attribute to this cluster analysis are ICT infrastructure, management of villagers' participation in ICT activities, renewable energy, transportation, agricultural business activities and nonagricultural small and medium enterprises. The results of the clusters show that there are 3 clusters of citizen science potential to develop smart Indonesian villages, namely the very potential (11%), potential (60%) and quite potential (29%) clusters. This citizen science prospects cluster map is visualized on spatial data based on the provinces in Indonesia. Province Bangka Belitung Island, West Java, Central Java, East Java, Yogyakarta, Banten and Bali are potential provinces for developing citizen science in order to construct big data-based smart villages. The results of this cluster were validated with the dendogram structure of the systematic literature review (SLR). The dendogram structure shows the keywords that correspond to the main attributes used in the clustering process. This validation process is an innovative finding in the smart village research ecosystem.