Analisis Semiotika Makna Nasionalisme melalui Text Mining pada Media Sosial Twitter di Kejuaraan AFF Tahun 2020
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Abstract
This study visualises semiotic analysis of the meaning of nationalism in the 2020 ASEAN Football Federation championship using the constructivist paradigm. The primary data were collected through non-participant observation using Text Mining techniques with the help of a rapid miner. The method of this research consists of several stages including text processing and the use of the K-Means clustering technique to obtain data groupings that have similarities. Furthermore, the results of clustering were analyzed using the theory of semiotic triangle meaning Charles S. Peirce. The results showed that the sign includes texts that have the full meaning of nationalism or the teachings of love for the homeland. Sentences tweeted on Twitter social media are divided into state symbols represented by words such as national team as many as 22653 words, PSSI as many as 5097 words, and garuda with 1170 words. The attitude of nationalism is represented by words such as enthusiasm as many as 1893 words, fighting as many as 982 words, supporting as many as 11747 words, proud as many as 612 words, and hope as many as 506 words. Meanwhile, the cluster evaluation shows that 17 of the 28 available clusters have interpretations of nationalism values that emphasize texts that contain an attitude of national spirit through the 2020 AFF Cup final match.
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