STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Vol 6, No 1 (2021)

Tren Marketplace Berdasarkan Klasifikasi Ulasan Pelanggan Menggunakan Perbandingan Kernel Support Vector Machine

Dwi Latifah Rianti (Universitas Singaperbangsa Karawang)
Yuyun Umaidah (Universitas Singaperbangsa Karawang)
Apriade Voutama (Universitas Singaperbangsa Karawang)



Article Info

Publish Date
05 Aug 2021

Abstract

Currently, many Indonesian people like to conduct online trading transactions. However, a number of business people find it difficult to choose a marketplace to market their products. One of the reasons is because they rarely pay attention to the marketplace trends that consumers are discussing. Therefore, analyzing trends on social media such as Twitter, it becomes very important for business people to understand the pattern of consumer tendencies towards their services or products. So the purpose of this study is to create a model that can analyze marketplace trends based on the classification of customer reviews on Twitter using the SVM algorithm. The kernels used are linear, RBF, sigmoid, and polynomial with parameter optimization using grid search. The methodology used is KDD. The results of the evaluation of the best classification model are the sigmoid kernel with 92% accuracy, 92% precision, 92% recall, and 92% F1 score and parameters C=100, =0.01, and r=1. Market trend results based on the highest percentage of positive reviews are Tokopedia, Shopee, and lastly Bukalapak.

Copyrights © 2021






Journal Info

Abbrev

STRING

Publisher

Subject

Computer Science & IT Mathematics

Description

STRING (Satuan Tulisan Riset dan Inovasi Teknologi) focuses on the publication of the results of scientific research related to the science and technology. STRING publishes scholarly articles in Science and Technology Focus and Scope Covering: 1. Computing and Informatics 2. Industrial Engineering ...