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Karina M., Rahma
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Computer Science & IT

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Public Sentiment and GoTo Stock Price Movement in Indonesia: A Null-Relationship Study Using Naïve Bayes and Non-Parametric Measures Pramesti, Dita; Fakhrurroja, Hanif; Karina M., Rahma
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.46447

Abstract

The expiration of the lock-up period for PT GoTo Gojek Tokopedia Tbk's shares led to a sharp stock price decline and public discourse on Twitter. This study aims to examine the statistical relationship between public sentiment and GoTo’s stock price movement in Indonesia. Tweets were classified into positive or negative sentiment using the Naïve Bayes classifier, selected for its computational efficiency on large-scale textual data. The model achieved 70% accuracy, with a precision of 82% and F1-score of 75%. The sentiment polarity was then compared with stock trends across 39 distinct trading periods using four non-parametric statistical tests: Chi-Square (p = 0.6398), Cramer’s V (0.014), Goodman-Kruskal’s Lambda (0.053), and Mann-Whitney U test (p = 0.8994). None of these tests showed a statistically significant association between sentiment polarity and stock price movement. These findings highlight that while public sentiment may reflect short-term public interest, it does not reliably capture the market’s behavioral dynamics—especially in cases of investor decisions driven by broader macroeconomic or institutional factors. Sentiment data, therefore, should be considered as a complementary, rather than primary indicators in stock price analysis.
Co-Authors Dita Pramesti Fakhrurroja, Hanif