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Sentiment Analysis of Digital Literacy in Society Towards Financial Technology Lending Using The Naive Bayes
Abstract
The existence of financial technology lending (pinjol), as a fintech innovation, has become a hot topic in society. Its emergence, driven by the rapid growth of the internet and ease of access to information, has a significant impact on the financial sector. Behind its convenience, this service also faces various issues due to the low digital literacy of the public. Therefore, the Financial Services Authority (OJK) uses the social media platform X (Twitter) to monitor public opinion regarding this matter. Based on this background, this research is conducted to analyze the sentiment of the Indonesian public by categorizing it into positive and negative. The text classification in this study utilizes the effective and accurate Naïve Bayes algorithm, with a dataset of 2179 tweets obtained through crawling. The implementation steps of the method include literature study, data collection, preprocessing, labeling, Naïve Bayes implementation, results, and evaluation.
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DOI: https://doi.org/10.17509/coelite.v5i2.90572
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