OPINION MINING OF REGIONAL HEADS IN INDONESIA USING THE SUPPORT VECTOR MACHINE (SVM) METHOD

Dwi Hosanna Bangkalang


DOI: https://doi.org/10.29100/jipi.v9i3.5381

Abstract


Social media is one of the communication mediums commonly used by regional heads to disseminate information, develop their image, and influence society through digital media. As a result, the regional head’s opinion on an issue is one of the factors that piques public interest in knowing where the opinions of regional heads lie. Opinion mining is the process of obtaining information or the analysis and summarization of opinions that are automatically voiced on particular topics or issues. A method is required to convert the regional leaders’ social media tweets into information and ideas that can be valuable for the community in order to see the trend of regional heads’ opinions and discussion topics on social media. One method that can be used is mining the opinion of regional heads to find out their topics and sentiments in the new normal. The opinion mining method used is sentiment analysis using the Support Vector Machine (SVM) algorithm. The SVM algorithm uses a target label that will be predicted from a labeled dataset to find the optimal hyperplane that categorizes sentiment. This study aims to determine the opinion of the regional heads regarding the chosen topic for the current period of time. The findings of this study identify the regional head sentiment tendency based on model evaluations with an accuracy rate of more than 80%.


Keywords


opinion mining, sentiment analysis, support vector machine, regional heads

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