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dc.contributor.advisorAdrianto, Hari Agung
dc.contributor.authorPamungkas, Praditya
dc.date.accessioned2014-04-24T00:52:25Z
dc.date.available2014-04-24T00:52:25Z
dc.date.issued2014
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/68626
dc.description.abstractThere are currently the most used data model is relational. This model a database as a set of data that is stored in structural rows and columns. Besides the popullarity, the relational data model is lacking in the implementation of data is large and has a high complexity. Different of the relational model, MonetDB using a column store method to divide the data into sections binary tables . This method is only necessary to call the data, resulting method is faster. Anggi ( 2013 ) have tested the MonetDB as a spatial and non spatial data storage, but not yet visualize data from MonetDB. This result successfully visualize spatial data using a simple query “like” and “and” the average time 1 second , while the complex spatial queries using “joins”, “constains” and “Intersect” with average time more than 20 minutes. So it looks that MonetDB also can process spatial data simple and complex . But in the process of complex spatial data visualization that require run-time is relatively long .en
dc.language.isoid
dc.titleVisualisasi Data Spasial di MonetDB Menggunakan OpenJUMPen
dc.subject.keywordvisualizeen
dc.subject.keywordOpenJUMPen
dc.subject.keywordMonetDBen
dc.subject.keywordspatial dataen


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