PEMETAAN TREN DAN METODOLOGI ANALISIS SENTIMEN: SEBUAH TINJAUAN LITERATUR
DOI:
https://doi.org/10.23969/jp.v10i04.33375Keywords:
accuracy, algorithm, data mining, lstm, sentiment analysisAbstract
The rapid evolution of information and communication technology, driven by progressive development in AI and machine learning, has profoundly transformed sentiment analysis. This study provides a systematic literature review of sentiment analysis methodologies, evaluating their effectiveness across datasets, algorithms, platforms, and accuracy levels. The result indicates that trending topic on social media dominates current research. Moreover, Google Play Store serves as the primary data source, and LSTM is the most widely used algorithm. These findings highlight the necessity of robust methodologies to refine sentiment classification, improve model accuracy, and mitigate biases in text-based data. By identifying prevalent techniques and tools, this study advances sentiment analysis methodologies, facilitating improved data-driven decision-making in fields.
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