IMPLEMENTASI ALGORITMA MODIFIED GUSTAFSON-KESSEL UNTUK CLUSTERING TWEETS PADA AKUN TWITTER LAZADA INDONESIA

*Ratna Kencana Putri  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Budi Warsito  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Mustafid Mustafid  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Published: 30 Aug 2019.
Open Access Copyright 2020 Jurnal Gaussian
License URL: http://creativecommons.org/licenses/by-nc-sa/4.0

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Abstract

Online social media is a new kind of media which is steadily growing and has become publicly popular. Due to its ability to spread informations rapidly and its easiness to access for internet users, social media provides new alternative to conduct advertising and product segmentation. Twitter is one of the most favored social media with 19.5 million users in Indonesia to the date. In this research, the application of text mining to cluster tweets from the @LazadaID Twitter account is done using the Modified Gustafson-Kessel clustering algorithm. The clustering process is executed five times with the number of cluster starts from two to six cluster. The results of this research indicate that the optimum number of clusters formed based on the Partition Coefficient and Classification Entropy validation index are three clusters. Those three clusters are tweets containing electronic stuff offers, discounts, and prize quizes. Tweets with the most retweets and likes are prize quiz tweets. PT Lazada Indonesia could use this kind of tweet to conduct advertising on social media Twitter because the prize quiz tweets are liked by the @LazadaID Twitter account followers.

Keywords: Twitter, advertising, Lazada Indonesia, Gustafson-Kessel Clustering algorithm, validation index
Keywords: Twitter, advertising, Lazada Indonesia, Gustafson-Kessel Clustering algorithm, validation index

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