Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Vol 5 No 6 (2021): Desember 2021

Perbandingan Naïve Bayes, SVM, dan k-NN untuk Analisis Sentimen Gadget Berbasis Aspek

Jessica Widyadhana Iskandar (Universitas Kristen Satya Wacana)
Yessica Nataliani (Universitas Kristen Satya Wacana)



Article Info

Publish Date
30 Dec 2021

Abstract

The Samsung Galaxy Z Flip 3 is one of the gadgets that are currently popular among the public because of its unique shape and features. Youtube is one of the social media that can be accessed and enjoyed by the public, one of which is gadget review content on the GadgetIn channel. Youtube can provide information, whether people accept or are interested in this new gadget or not. This study aims to determine the sentiment of a gadget producer. Based on the results of the analysis and testing that has been carried out on the Youtube comments of the Samsung Galaxy Z Flip 3 gadget with a total of 9,597 comments, more users gave positive opinions in the design aspect and negative opinions on the price, specifications and brand image aspects. By using the CRISP-DM model and comparing the Naïve Bayes (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) classification methods, it is proven that the SVM classification model shows the best results. The average accuracy of SVM is 96.43% seen from four aspects, namely the design aspect of 94.40%, the price aspect of 97.44%, the specification aspect of 96.22%, and the brand image aspect of 97.63%.

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Journal Info

Abbrev

RESTI

Publisher

Subject

Computer Science & IT Engineering

Description

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat ...