Marketplace Sentiment Analysis Using Naive Bayes And Support Vector Machine

PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)

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Title Marketplace Sentiment Analysis Using Naive Bayes And Support Vector Machine
 
Creator Azhar, Muhamad
Hafidz, Noor
Rudianto, Biktra
Gata, Windu
 
Description Abstract
 
Technology implementation in the marketplace world has attracted the attention of researchers to analyze the reviews from customers. The Klik Indomaret application page on GooglePlay is one application that can be used to get information on review data collection. However, getting information on consumer’s opinion or review is not an easy task and need a specific method in categorizing or grouping these reviews into certain groups, i.e. positive or negative reviews. The sentiment analysis study of a review application in GooglePlay is still rare. Therefore, this paper analysis the customer’s sentiment from klikindomaret app using Naive Bayes Classifier (NB) algorithm that is compared to Support Vector Machine (SVM) as well as optimizing the Feature Selection (FS) using the Particle Swarm Optimization method. The results for NB without using FS optimization were 69.74% for accuracy and 0.518 for Area Under Curve (AUC) and for SVM without using FS optimization were 81.21% for accuracy and 0.896 for AUC. While the results of cross-validation NB with FS are 75.21% for accuracy and 0.598 for AUC and cross-validation of SVM with FS is 81.84% for accuracy and 0.898 for AUC, while there is an increase when using the Feature Selection (FS) Particle Swarm Optimization and also the modeling algorithm SVM has a higher value compared to NB for the dataset used in this study.
 
Keywords: Naive Bayes, Particle Swarm Optimization, Support Vector Machine, Feature Selection, Consumer Review.
 
Publisher LPPM Universitas Islam 45 Bekasi
 
Date 2020-09-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://jurnal.unismabekasi.ac.id/index.php/piksel/article/view/2272
10.33558/piksel.v8i2.2272
 
Source PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic; Vol 8 No 2 (2020): September 2020; 91 - 100
2620-3553
2303-3304
10.33558/piksel.v8i2
 
Language eng
 
Relation http://jurnal.unismabekasi.ac.id/index.php/piksel/article/view/2272/1749
 
Rights Copyright (c) 2020 PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
 

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