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All Journal Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika
Fahrul Kurniawan
Teknik Informatika, Universitas Islam Negeri Maulana Malik Ibrahim Malang
Computer Science & IT Decision Sciences, Operations Research & Management

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Analisis Sentimen Review Aplikasi Media Berita Online Pada Google Play menggunakan Metode Algoritma Support Vector Machines (SVM) Dan Naive Bayes Ulfa Kusnia; Fahrul Kurniawan

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v14i1.3116

Abstract

Online news media has become one of the most frequently consumed mass media by the public, which is able to beat the previous generation of media such as electronic media and print media. The advantage of online media compared to print media in general lies in its up-to-date, real-time and practical nature. In order to continue to maintain and improve the performance of online news media, public assessment of the services and news presented is very important. The public rating can be seen from the Google Play site in the user review column. Sentiment analysis can be used to analyze these reviews by classifying positive and negative reviews. The user review data was then labeled and analyzed using the Naïve Bayes algorithm and Support Vector Machines. The experimental results show that the accuracy of machine learning for sentiment analysis on online news media reviews Google Play reaches 90% and the deep learning approach outperforms Support Vector Machine (88%) while Naïve Bayes (87%).
Co-Authors Ulfa Kusnia