KLASIFIKASI SENTIMEN REVIEW APLIKASI EDUTECH ZENIUS DENGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK

IMAN, MUHAMMAD NOUFAL RIFQI and Utami, Alvi Syahrini and Darmawahyuni, Annisa (2023) KLASIFIKASI SENTIMEN REVIEW APLIKASI EDUTECH ZENIUS DENGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

Zenius is one of the rapidly growing edutech applications in Indonesia. In the edutech industry, understanding and promptly responding to user reviews is crucial to enhance the quality of the application's services, enabling Zenius to remain competitive against other competitors. In order to achieve this, sentiment classification is used by classifying user reviews into positive, negative, or neutral categories using a classification algorithm. In this research, the Convolutional Neural Network (CNN) algorithm is used as the classification method, while Word2Vec is used as the word embedding technique. The dataset used in this research consists of 1,587 user reviews of the Zenius application obtained from the Google Play Store website. The results of the research demonstrate the best CNN model using a configuration of a learning rate=〖10〗^(-3), a batch size=16 and 3 convolution layers with an accuracy value of 84.28%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Zenius, Edutech Application, Review, Sentiment Classification, Convolutional Neural Network, Word2Vec
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 Noufal Rifqi Iman
Date Deposited:	05 Jul 2023 06:10
Last Modified:	05 Jul 2023 06:10
URI:	http://repository.unsri.ac.id/id/eprint/114370

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