Image of ANALISIS PERBANDINGAN RATING-BASED DAN INSET LEXICON-BASED DALAM PROSES LABELING ANALISIS SENTIMEN (STUDI KASUS: ULASAN APLIKASI GOBIZ DI GOOGLE PLAY STORE)

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ANALISIS PERBANDINGAN RATING-BASED DAN INSET LEXICON-BASED DALAM PROSES LABELING ANALISIS SENTIMEN (STUDI KASUS: ULASAN APLIKASI GOBIZ DI GOOGLE PLAY STORE)

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Digital transformation has had a significant impact on various sectors, including Micro, Small and Medium Enterprises (MSMEs). The GoBiz application, as Gojek's business partner platform for GoFood services, plays an important role in supporting digital transformation in the MSME sector, so it is necessary to understand users' views on this application. To analyze user perceptions of this application, sentiment analysis research was conducted using 5,000 GoBiz user reviews from the Google Play Store. This research compares two labeling methods, namely Rating-based and Inset Lexicon-based, then evaluated with the Support Vector Machine (SVM) algorithm. The analysis process includes data selection, text preprocessing, data transformation using TF-IDF, SVM application with 10-fold cross-validation, and visualization of results through WordCloud. The test results show that Rating-based labeling gets 87% accuracy, 86.7% precision, 87.1% recall, and 86.8% f1-score. Meanwhile, Inset Lexicon-based labeling achieved 89.7% accuracy, 89% precision, 89.8% recall, and 89.3% f1-score. These findings show that the combination of Inset Lexicon-based labeling method and SVM algorithm is more effective in classifying the sentiment of user reviews and provides a more accurate understanding of users' perceptions of the GoBiz app.

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Inventory Code Barcode Call Number Location Status
2507000990T166015T1660152024Central Library (Reference)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1660152024
Publisher
: Prodi Sistem Informasi, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xiii, 65 hlm.; tab.; 29 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
005.360 7
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Sistem informasi
Specific Detail Info
-
Statement of Responsibility
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