Nuryadi, Didik
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CRYPTO NARRATIVES SENTIMENT ANALYSIS ON BITCOIN PRICE PREDICTION USING THE NAIVE BAYES METHOD Nuryadi, Didik; Manongga, Daniel H.F.; Sembiring, Irwan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6116

Abstract

Globalization affects many aspects of human life with consequences that may be positive or negative. Advances in information technology, which significantly assist many human activities, are one of the ele-ments affected. As a new product of financial technology, cryptocur-rency has revolutionized the global payment system. Bitcoin has expe-rienced significant price increases in recent years, often caused by eco-nomic and psychological market factors. Sentiment analysis of the bitcoin crypto narrative is essential for understanding market behavior and predicting price trends because market sentiment has been proven to influence bitcoin price movements. Therefore, this research aims to investigate the crypto sentiment narrative regarding Bitcoin price movements using a sentiment analysis approach with the Naïve Bayes classification method. The dataset used in this research comes from crypto narratives that are considered to influence bitcoin price move-ments, which were collected from October 2022 to April 2024. This re-search succeeded in classifying the data tested using 10-fold cross-validation testing, with an average of 76.13%. The precision score for the positive opinion class was 63.92%, and the precision score for the negative opinion class reached 81.77%. The average recall value for the positive class was 61.69%, and for the negative class, it reached 83.12%. This data shows that Naïve Bayes is quite good at analyzing crypto sentiment narratives regarding bitcoin price movements.