JURNAL TEKNOLOGI DAN OPEN SOURCE
Vol 4 No 2 (2021): Jurnal Teknologi dan Open Source, December 2021

Particle Swarm Optimization-based Support Vector Machine Method for Sentiment Analysis in OVO Digital Payment Applications

Retno Sari (Universitas Nusa Mandiri)
Ratih Yulia Hayuningtyas (Universitas NUsa Mandiri)



Article Info

Publish Date
20 Dec 2021

Abstract

Sentiment analysis is used to analyze reviews of a place or item from an application or website that then classified the review into positive reviews or negative reviews. reviews from users are considered very important because it contains information that can make it easier for new users who want to choose the right digital payment. Reviews about digital payment ovo are so much that it is difficult for prospective users of ovo digital payment applications to draw conclusions about ovo digital payment information. For this reason, a classification method is needed in this study using support vector machine and PSO methods. In this study, we used 400 data that were reduced to 200 positive reviews and 200 negative reviews. The accuracy obtained by using the support vector machine method of 76.50% is in the fair classification, while the accuracy obtained by using the support vector machine and Particle Swarm Optimization (PSO) method is 82.75% which is in good classification.

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Journal Info

Abbrev

JTOS

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknologi dan Open Source menerbitkan naskah ilmiah. yang berkaitan dengan sistem informasi, teknologi informasi dan aplikasi open source secara berkala (2 kali setahun). Jurnal ini dikelola dan diterbitkan oleh Program Studi Teknik Informatika Fakultas Teknik, Universitas Islam Kuantan ...