Sonalitha, Elta, Zubair, Anis, Mulyo, Priyo Dari, Asriningtias, Salnan ratih, Nurdewanto, Bambang, Prambanan, Bondhan Rio and Mujahidin, Irfan (2020) Combined text mining: Fuzzy clustering for opinion mining on the traditional culture arts work. International Journal of Advanced Computer Science and Applications (IJACSA), 11 (8). pp. 294-299. ISSN 2156-5570 (e) ; 2158-107X (p)

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Abstract

The Indonesian government is currently
intensifying work programs in the field of traditional arts and
culture. In order to realize the promotion of the country's
culture, the government has enacted a law on cultural promotion.
One indicator of the achievement of the promotion of culture,
among others, with the collection of data on traditional culture,
the data mapping and data inventory can be processed into
information and knowledge. In this research, indicators of
performance indicators were compiled from connoisseurs of
traditional works of art using data in the city of Malang, East
Java, Indonesia. The results of the audience's opinion on cultural
offerings can be used as a benchmark for the success of the
promotion of traditional culture. When the culture is explored
and tried to be displayed again, it is important to know the
audience's satisfaction and understanding of the display that has
just been witnessed. The results of the description of respondents
in the form of opinions on the artwork will be collected as data
processed using Text Mining with the Clustering of Fuzzy C�Means method to determine the audience's opinion about Feeling
, which is related to feelings when viewing the beauty of the
artwork, Value is related to the assessment to an art work that
can be in the form of art weights contained in the work of art,
and Emphasizing , which is related to empathy or respect for the
art world, including professions related to the world such as
dancers, musicians and others. The results achieved from this
study show that has good performance on the proposed method.
This can be known from the results of data testing using cluster
variance V = 0.00000217901. Based on these values it can be
concluded that the value of all cluster variants is good.

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