TOPIC MODELING FOR INDONESIAN TEXT

Parmadi, Rasyiid Indra (2019) TOPIC MODELING FOR INDONESIAN TEXT. S1 - Sarjana thesis, Universitas AMIKOM Yogyakarta.

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Abstract

Reading is the activity of perceptual, analyzing, and interpreting what is done by the reader to get the message to be conveyed by the author in the writing media. Along with current technological developments, technology has changed the way a person reads a text, especially text that is in electronic media. Generally, a reader must read the text that is in a particular file thoroughly to find out what topics can be obtained from the text. This becomes a problem in terms of the time and magnitude of the effort used by the reader. This research will make a document summarization program, especially in Indonesian text using the Maximum Marginal Relevance or MMR algorithm. The MMR algorithm is a simple and efficient text summarization algorithm. With text summarizing programs, change someone to find and find out what topics are available in the text without having to read the text thoroughly. This program will produce topics or conclusions from a text and help someone to find out what topics are in the text without reading it. This program will help someone who doesn't like the process of reading a lot of text. After getting the topic, he will look for other explanations about the topic from the internet to learn manually.

Item Type:

Thesis (S1 - Sarjana)

Contributor:

Pembimbing
Setyanto, Arief

Uncontrolled Keywords:

Summarization, Indonesian Text, Maximum Marginal Relevance (MMR).

Subjects:

000 - Komputer, Informasi dan Referensi Umum > 000 Ilmu komputer, ilmu pengetahuan dan sistem-sistem > 000 Ilmu komputer, informasi dan pekerjaan umum

Divisions:

Fakultas Ilmu Komputer > Informatika

Depositing User:

RC Universitas AMIKOM Yogyakarta

Date Deposited:

17 Nov 2022 08:51

Last Modified:

15 Nov 2023 07:59

URI:

http://eprints.amikom.ac.id/id/eprint/11297

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