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Taxonomy of Artist and Art Works Using Hybrid TF-IDF Fuzzy C-Means Clustering

Nurdewanto, Bambang, Sonalitha, Elta ORCID:, Zubair, Anis, Asriningtias, Salnan Ratih and Mujahidin, Irfan ORCID: (2020) Taxonomy of Artist and Art Works Using Hybrid TF-IDF Fuzzy C-Means Clustering. International Journal of Advanced Science and Technology, 29 (3). pp. 12066-12075. ISSN 2005-4238 ; 2207-6360 (Online)

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The Indonesian government has just promulgated a Law on the promotion of culture (Law No.5 2017). The Government, through the Tourism Office, determines the method of classification of cultural data using the Taxonomy method. The purpose of this study is taxonomy or mapping of big data art activists in the city of Malang, East Java, Indonesia based on the expertise of each person, so that it will facilitate the search for data for reference decision making. This research tests the calculation based on word linguistics and multi tagging from the data that the artist fills in online instruments. This study proposes the TF-IDF Fuzzy C-Means hybrid as a method of resolving these problems. TF-IDF is used as a feature extraction while Fuzzy C-Means as a clustering method. To find out the performance of the proposed method, this study uses the Variant cluster (V) technique. Based on the research analysis, the level value of V = 0.0000163 is getting smaller. This shows that all cluster variants are getting better.

Item Type: Article
Additional Information: Elta Sonalitha NIDN: 0712017902
Uncontrolled Keywords: Taxonomy of Artist, TF-IDF, Fuzzy C-Means Clustering
Subjects: N Fine Arts > NX Arts in general
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Teknik > S1 Teknik Elektro
Depositing User: Rita Juliani
Date Deposited: 05 Mar 2023 11:07
Last Modified: 05 Mar 2023 11:07

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