Skripsi

ANALISIS SENTIMEN PADA OPINI PUBLIK TENTANG ANGKUTAN ONLINE MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) BERBASIS MOBILE

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Penilaian

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Online transportation provides convenience for people to find transportation services with fixed fares. However, online transportation has shortcomings such as inexperienced drivers, potential delays, and mismatched user expectations. Therefore, sentiment analysis is needed to assess public satisfaction with online transportation. Deep learning approaches such as Convolutional Neural Network (CNN) can be used for sentiment analysis. CNN can automatically extract relevant features from text data, recognize important patterns in the text, and efficiently handle varying lengths of text data. In this study, text data is transformed into Word Embedding using Word2Vec to implement CNN for sentiment analysis. The data used is obtained from Google Play Reviews, consisting of 6000 reviews with 3000 positive labels and 3000 negative labels. The data is divided into 3600 training data, 1200 validation data, and 1200 test data. The research results show an accuracy, precision, recall, and f1-score of 91.00%, 91.08%, 91.00%, and 91.00% on the test data.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002433	T99841	T1134682023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1134682023

Publisher

Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xvi,72 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Data Processing
Jurusan Teknik Informatika

Specific Detail Info

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Statement of Responsibility

FIRA

Other version/related

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