VOIR brand product reviews using a semantic analysis / Aina Zuliana Zulkefli ... [et al.] - Zulkefli, Aina Zuliana; Aminuddin, Raihah; Yaakob, Farah Nisa Syahindah; Bonyamin, Nursyamiza Azwa (Faculty of Computer and Mathematical Sciences, 2021)
Online customers could have difficulties in making decision to buy a product due to a massive number of product reviews. Therefore, this project focuses on the implementation of an approach to analyse the VOIR brand product reviews using a semantic analysis. The main goal of this project is to develop a web-based system that will provide a data visualization of VOIR product reviews from an online store, Shopee. The methodology of this project is using waterfall model. There are four phases involved in this project (i) problem assessment, (ii) design, (iii) development and (iv) results. MySQL database and Python programming language will be used to develop the system. The analysis of the VOIR product review was done using sentiment analysis technique. The system will perform a sentiment analysis of the VOIR product reviews and further categorize the positive, negative, and neutral reviews via data visualization methods such as word cloud, line graph, and pie chart. This web-based system can help customer in making decision when buying a product. At the same time, sellers can use the analysis output to improve their services and products. In the future, the system could be developed for mobile application to ease their users to keep track the highest quality of VOIR products based on customers’ reviews.