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Blackbox testing using fuzzy clustering based on boundary value analysis on the text opinion mining application in traditional culture arts presentation

Zubair, Anis, Sonalitha, Elta, Asriningtias, Salnan Ratih, Nurdewanto, Bambang, Yudhistiro, Kukuh and Mujahidin, Irfan (2020) Blackbox testing using fuzzy clustering based on boundary value analysis on the text opinion mining application in traditional culture arts presentation. In: IC-SMART Proceeding on International Conference of Science Management Art Research Technology, Bandung.

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Abstract

The success of organizing a traditional work of art cannot be separated from the important role of
data and information obtained from the public in general and viewers or art connoisseurs in particular.
This information is an indicator that can be used to measure the amount of public attention to traditional
arts, which is an effort to promote traditional cultural arts. Data and information related to traditional
artworks were obtained from filling out the instruments that were distributed to the public online to
produce an opinion form that contained a complete description with a discussion containing the aesthetic
of the artwork. Opinion data is needed as a measure of progress and preservation of a work of art. The
linguistic measurement of opinion can be solved using fuzzy methods in a cryptic form that can be
weighted. In this study, the authors tested the audience opinion text mining application on the
presentation of traditional cultural artworks using fuzzy clustering using the functional testing method
(Black box testing). Through this test will be discussed related to the menu or module to produce
information.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Nama : Elta Sonalitha NIDN : 0712017902
Uncontrolled Keywords: Text mining, fuzzy clustering, art, black-box testing
Divisions: Fakultas Teknik > S1 Teknik Elektro
Depositing User: Surya Dannie
Date Deposited: 13 Nov 2021 22:36
Last Modified: 24 Feb 2023 02:09
URI: https://eprints.unmer.ac.id/id/eprint/1006

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