Skripsi

KLASIFIKASI SENTIMEN KOMENTAR PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

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Penilaian

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The government's policy regarding coal transportation operations received various opinions from the public through comments on Instagram. People expressed their opinions about the impact they felt. The comments given are public opinions that are pro and contra related to the impact of the policy. The community's opinion is classified using the Support Vector Machine (SVM) method with polynomial, RBF, and sigmoid kernels. The highest accuracy results in the sigmoid kernel. The sigmoid kernel accuracy ratio is higher by 9.34% with 70% training data and 30% test data from 250 data. Increasing the amount of data has the potential to improve the performance of the SVM method. Key Word : Support Vector Machine, Sentiment Classification, Publik Opinion, Instagram.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000993	T139836	T1398362024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1398362024

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xviii, 87 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.754 07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Situs Jejaring Sosial

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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