CD Skripsi

Topic Clustering Terhadap Dokumen Twitter Berbahasa Indonesia Menggunakan Mini Batch K-Means Clustering (Studi Kasus Pemilihan Presiden Indonesia 2019)

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Elections become one of the important indicators in a country's democracy, elections are identical to the campaign, one of the media that can be used as a means of the campaign is social media such as Twitter. The information content contained on Twitter is also very diverse. Therefore, it is needed an automatic topic detection method such as the Mini Batch K-means clustering method that makes it easy for users to access information. In this study, the approach used is the Mini Batch method which only uses a small group of data in the clustering process. The results of this study found that the results of clustering for tweet data with keywords Jokowi - Maruf Amin and Prabowo - Sandiaga Uno obtained eight cluster groups, based on testing with Sum of Squared Error (SSE) with a range of SSE values of 1275-1200, to obtain a K value the most optimum is eight clusters.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 05.119 (0050)

Penerbit

Pekanbaru : Universitas Riau - FMIPA - Sistem Informasi., 2019

Deskripsi Fisik

xi, 45 hlm.: ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 05.119 (0050)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

ELFITRA

Versi lain/terkait

Lampiran Berkas

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