0,0

dari 5

Text Summarization is a tool used to generate a short form of text that contains important information that is needed by the user automatically. In this study, Text Summarization was conducted on Indonesian news using K-Means method. The news is taken from CNN Indonesia with a free topic. K-Means is used to classify sentences that already have weight in the news with 2 clusters, namely text summaries and not text summaries. The initial centroid is selected based on the sentence with the largest value and the sentence with the smallest value. The test conducted on Indonesian news with a total 50 news and tested for feasibility using a questionnaire. K-Means was successfully summarizing the news with an average 27.3 % of original news length and gain 87% good summarize based on respondents from questionnaire.

Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002179	T54049	T540492021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title: -
Call Number: T540492021
Publisher: Inderalaya : Fakultas Ilmu Komputer, Prodi Teknik Informatika., 2021
Collation: xv, 79 hlm,: ilus.; 29 cm
Language: Indonesia
ISBN/ISSN: -
Classification: 004.07
Content Type: -
Media Type: -
Carrier Type: -
Edition: -
Subject(s): Prodi Teknik Informatika
Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Specific Detail Info: -
Statement of Responsibility: MURZ

Other version/related

No other version available

File Attachment

PERINGKASAN TEKS DENGAN METODE K-MEANS

Comments

You must be logged in to post a comment