Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes

Abstract

The rapid development of E-commerce has given rise to many marketplaces in Indonesia such as Tokopedia, Shopee, Lazada. Tokopedia, Shopee and Lazada applications are applications that help sellers and buyers to make sales and purchase transactions for goods and services. Until now, of the three major E-Commerce applications, around 100 million users have downloaded the three E-Commerce applications. With the launch of some of these applications, it has caused a lot of opinions and criticisms from the public. Based on this, a sentiment analysis of the Naïve Bayes algorithm was carried out to find out how the sentiment of users compares to the E-Commerce application on the Google Play Store. This research uses the Knowledge Discovery in Database (KDD) method which consists of 5 stages, namely data selection, preprocessing, transformation, data mining, and evaluation. The data used is a review of 500 E-Commerce applications per each application. At the data mining stage, it is carried out with 3 scenarios data sharing is 80:20, 70:30 and 60:40. The best results were obtained in scenario 1 (80:20) on the Shopee application using the Naïve Bayes algorithm which resulted in an accuracy of 92%, precision of 92.13%, recall of 98.8% and f1-score of 95.35%.