Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Eneng Tita Tosida, Yeni Herdiyeni, Marimin, Suprehatin

Judul : The Potential for Implementing a Big Data Analytic-based Smart Village in Indonesia
Abstrak :

Smart village is one of the solutions to reduce poverty in rural areas. The main objective of this research is to map the potential implementation of the concept of smart villages based on big data analytics in Indonesia. This research was conducted through the elaboration of text mining-based Systematic Literature Review (SLR) with multiple regression analysis of the 2018 Village Potential Data in Indonesia. The contribution of this study is the production of a map describing the potential for implementing smart villages based on big data analytics in Indonesia. SLR cluster analysis produces a dendrogram that maps the basic terminology of smart villages based on big data analytic. Indonesia has quite substantial economic and social capital resources, which has a positive effect on the poor and farmers/fishermen (R2 = 0.9759 and 0.9482) in the villages. This occurs through a mix of regional budget revenue (APBD) and local self-subsistent (Swadaya) funding schemes in the management of agricultural and non-agricultural small businesses in the village. Indonesia also has sufficient capital for managing information and communication technology (ICT) in the village for the development of big data analytic smart villages. There is a relatively strong influence on the poor and farmers/fishermen (R2 = 0.5946 and 0.6006). Therefore, the challenge for future research to develop a smart village model based on big data analytics that is appropriate to the territory of Indonesia. This model needs to be elaborated with diverse factors including economic, social, cultural and smart educational potential as well should include indicators of the potential for data technology available on various media, through the framework of agriculture big data analytic.

Tahun : 2020 Media Publikasi : Seminar Internasional
Kategori : Prosiding No/Vol/Tahun : 1 / 1 / 2020
ISSN/ISBN : -
PTN/S : IPB University Program Studi : ILMU KOMPUTER
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