Skripsi

PERBANDINGAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE (SVM) PADA ANALISIS SENTIMEN.

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Penilaian

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The study aims to perform a sentiment analysis in user review data to find out user satisfaction in the Spotify apps. Sentiment analysis is the process of document classification and in this study is divided into two parts, namely positive class and negative class. Classification is very important in searching documents for developers. The classification process begins by dividing the data collection into training data and testing data. Training data used Naïve Bayes method and Support Vector Machine method to obtain classification model for class determination on testing data. Both of the method is used to classify the results of user review data written on review section of Spotify apps so as to produced the desired classification automatically. The results of this study shows that Support Vector Machine gets better score with an accuracy of 83%, precision of 89%, recall of 64%, and f-measure of 74% than Naïve Bayes with an accuracy of 61%, precision of 57%, recall of 43%, and f-measure of 49%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002954	T12426	T1242622023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1242622023

Publisher

Indralaya : Prodi Teknik Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xv, 88 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.740 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Komputer
Pemerosesan Data elektrinik

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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