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All Journal VISI PUSTAKA: Buletin Jaringan Informasi Antar Perpustakaan
Wishnu Hardi
National Library of Australia
Library & Information Science

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ANALISIS ARSITEKTUR SISTEM TROVE NATIONAL LIBRARY OF AUSTRALIA Wishnu Hardi
VISI PUSTAKA: Buletin Jaringan Informasi Antar Perpustakaan Vol 19, No 1: April 2017
Publisher : Perpustakaan Nasional RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37014/visipustaka.v19i1.6

Abstract

In 2008, the National Library of Australia initiated an ambitious project to create a "national discovery system" that connects all libraries in Australia. The project, called 'Trove', was launched in 2009 after being released in beta format for 6 months. Trove not only replaces the 8 collection service systems, but also provides a new experience to the public and researchers in and outside Australia by opening access to more extensive and varied contents. This paper discussed the background of the emergence of Trove, how the architecture of information technology systems is, content coverage, and what suggestions to further development of Trove are like.
PENGELOMPOKAN TOPIK DOKUMEN BERBASIS TEXT MINING DENGAN ALGORITME K-MEANS: STUDI KASUS PADA DOKUMEN KEDUTAAN BESAR AUSTRALIA JAKARTA Wishnu Hardi; Wisnu Ananta Kusuma; Sulistyo Basuki
VISI PUSTAKA: Buletin Jaringan Informasi Antar Perpustakaan Vol 21, No 1: April 2019
Publisher : Perpustakaan Nasional RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37014/visipustaka.v21i1.77

Abstract

The Australian Embassy in Jakarta is storing a wide array of media release document. Analyzing particular and vital patterns of the documents collection is imperative as it will result in new insights and knowledge of significant topic groups of the documents. K-Means algorithm was used as a non- hierarchical clustering method which partitioning data objects into clusters. The method works through minimizing data variation within cluster and maximizing data variation between clusters. Of the documents issued between 2006 and 2016, 839 documents were examined in order to determine term frequencies and to generate clusters. Evaluation was conducted by nominating an expert to validate the cluster result. The result showed that there were 57 meaningful terms grouped into 3 clusters. “People to people links”, “economic cooperation”, and “human development” were chosen to represent topics of the Australian Embassy Jakarta media releases from 2006 to 2016. This research concluded that text mining can be used to cluster topic groups of documents. It provides a more systematic clustering process as the text analysis is conducted through a number of stages with specifically set parameters.
Co-Authors Sulistyo Basuki Wisnu Ananta Kusuma