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ANALISIS SENTIMEN KOMENTAR PENGGUNA TERHADAP LAYANAN PAYLATER DI PLATFORM X MENGGUNAKAN KOMBINASI BI-DIRECTIONAL LONG SHORT-TERM MEMORY (BILSTM) DAN FASTTEXT

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The rapid growth of digital financial services in Indonesia has accelerated the adoption of PayLater features across various online transaction platforms. This trend has led to diverse public opinions and sentiments, particularly on social media platform X (Twitter). This study aims to analyze public sentiment toward PayLater services and compare the performance of the Bidirectional Long Short-Term Memory (BiLSTM) model with the BiLSTM model enhanced with FastText word embedding in classifying sentiments into three categories: positive, neutral, and negative. A total of 2,491 tweets were collected, consisting of 529 positive, 873 neutral, and 1,089 negative tweets. The dataset underwent text preprocessing, including case folding, cleansing, slang word normalization, tokenizing, and padding. Manual annotation was applied for sentiment labeling. Both models were evaluated using accuracy, precision, recall, and F1-score. The results show that the BiLSTM model achieved an accuracy of 82.05%, while the BiLSTM + FastText model outperformed with an accuracy of 91.02%. These findings indicate that integrating FastText embedding improves sentiment classification performance due to its ability to capture richer word representations in informal social media language. This study provides valuable insights for PayLater service providers in understanding user perception and supporting strategic decision-making Keywords: Sentiment Analysis, PayLater, BiLSTM, FastText, Social Media

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Detail Information

Series Title

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Call Number

T1900552025

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xiv, 97 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

006.312 07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Analisis Data--Data Sentimen

Specific Detail Info

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Statement of Responsibility

MI

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