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Deteksi Topik Tentang Tokoh Publik Politik Menggunakan Latent Dirichlet Allocation (LDA)

Authors: Faizun Nuril Hikmah; Setio Basuki; Yufis Azhar;

Deteksi Topik Tentang Tokoh Publik Politik Menggunakan Latent Dirichlet Allocation (LDA)

Abstract

Twitter merupakan salah satu Social Networking yang memperbolehkan pengguna untuk mengirim dan membaca sebanyak 140 karakter. Berdasarkan survey sekitar 500 juta tweet tiap harinya yang dikirim melalui twitter. Data-data tersebut dapat berupa opini-opini publik mengenai politik, tokoh publik, makanan, dan lain sebagainya. Data tersebut akan diolah dengan teknik Topic Detection untuk menghasilkan suatu topik yang sedang marak dibicarakan masyarakat tentang tokoh publik politik. Permasalahan dalam penulisan ini yaitu, bagaimana mengekstraksi suatu tweet tentang tokoh publik politik dari pengguna Twitter. Data tweet yang diambil tentang tokoh publik politik diantaranya yaitu mengenai Joko Widodo, Basuki Tjahaja Purnama (Ahok), Anies Baswedan, Sandiaga Uno, dan Habib Rizieq Shihab. Dengan adanya data atau tweet tentang tokoh publik politik dapat diolah menggunakan metode Agglomerative untuk mengcluster tiap data yang akan digunakan sebagai topik acuan, LDA (Latent Dirichlet Allocation) yang akan berfungsi sebagai pemodelan topik dari tweet-tweet yang telah tercluster, serta TF-IDF untuk mengetahui tweet mana saja yang mengandung kata-kata dalam LDA yang akan dijadikan sebagai topik acuan. Sehingga akan menghasilkan deteksi topik yang relevan berdasarkan tweet mengenai tokoh publik politik.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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