Implementasi Machine Learning Dengan Metode Text Mining Pada Twitter - Sulaiman, Hamdun; Ryansyah, Muhamad; Widianto, Kudiantoro; Sidik, Sidik; Nugraha, Andria (Infotek: Jurnal Informatika dan Teknologi, 2024)
Currently PT. Telkom Indonesia (Indihome), uses the role of social media as a form of concern for its customers to handle complaints. Tweets from indihome customers on social media twitter are handled by the customer service division of Indihome. The manual of the categorization process carried out by the customer service division of Indihome on every narration of the "complain" complaint tweet that  goes  to  @indihome  twitter,  makes  the  process  considered  inefficient.  The purpose of this research is to provide solutions related to the problem of categorizing complaint tweets and to develop tools that can extract the narration of "complain" tweets in Indonesian. The research method used is comparative. On the other hand, gataframework and rapidminer tools are also used in this research to assist in preprocessing and cleaning of datasets to help create corpus and sentiment analysis. The total dataset after cleansing and preprocessing is 1,510. Based on the method proposed in this study on the Support Vector Machine classification algorithm, the highest  category  was  found  to  have  82.42%  accuracy,  75.33%  precision,  and 98.75% recall with an AUC of 0.826