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

TARIS, MUHAMMAD HADYAN and Utami, Alvi Syahrini and Darmawahyuni, Annisa (2023) ANALISIS SENTIMEN APLIKASI DUOLINGO DI GOOGLE PLAY STORE MENGGUNAKAN OPTIMASI SUPPORT VEKTOR MACHINE (SVM) BERBASIS PARTICLE SWARM OPTIMIZATION (PSO). Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Analisis Sentimen, Aplikasi Duolingo, Google Play Store, Support Vektor Machine (SVM), Particle Swarm Optimization (PSO)
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Hadyan Taris
Date Deposited:	03 Aug 2023 03:13
Last Modified:	03 Aug 2023 03:13
URI:	http://repository.unsri.ac.id/id/eprint/125320

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