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ANALISIS SENTIMEN APLIKASI DUOLINGO DI GOOGLE PLAY STORE MENGGUNAKAN OPTIMASI SUPPORT VEKTOR MACHINE (SVM) BERBASIS PARTICLE SWARM OPTIMIZATION (PSO)

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Duolingo is one of the popular online learning applications in Indonesia, released in 2011. In order to compete with other competitors and increase its popularity, user satisfaction becomes one of the crucial aspects that Duolingo needs to pay attention to. Based on the identification results of online reviews on the Duolingo application in the Google Play Store, there are differences in user perceptions, indicating disparities in the services received by each user, resulting in various positive and negative reviews. This research aims to determine user satisfaction by utilizing online review data of the Duolingo application on the Google Play Store. The evaluation results show that the SVM model with a 90:10 ratio demonstrates the highest performance with an accuracy of 77%, precision of 76.74%, and an F1-score of 85.16%. As for recall, the SVM model with a 70:30 ratio shows the highest performance with a precision value of 99.51%.

Availability
Inventory Code Barcode Call Number Location Status
2307005295T125320T1253202023Central Library (Referens)Available
Detail Information
Series Title
-
Call Number
T1253202023
Publisher
Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xix, 72 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
003. 07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
analisis
Jurusan Teknik Informatika
Specific Detail Info
-
Statement of Responsibility
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