CRC – Clothing Review Classification using sentiment analysis / Nur Suhailayani Suhaimi ... [et al.]

Suhaimi, Nur Suhailayani and Sharip, Anis Afiqah and Arbin, Norazam and Azyan Izzati, Azyan Izzati (2023) CRC – Clothing Review Classification using sentiment analysis / Nur Suhailayani Suhaimi ... [et al.]. In: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2023). Faculty of Computer and Mathematical Sciences, Kampus Jasin, p. 6. (Submitted)

Abstract

Safehse is a clothing brand established in 2020. Safehse clothing highlights the essence of South Korean streetwear and puts it under the spotlight. The customer text review is one of the features that Safehse have to play a role in helping the customer to make their purchasing decision. However, Safehse encountered a few problems with the current process of identifying genuine or fake reviews, time-consuming to classify positive and negative from the customer text review, and misleading or misunderstanding reviews that need to be clarified for the customers. In order to reduce and minimize the problem, Safehse needs to use the classification of text reviews by using sentiment analysis. This research project aims to develop a system to classify text reviews for Safehse, which can identify positive and negative reviews. The sentiment analysis technique used for this text review classification is supervised machine learning that anticipates occurrences by combining what it has learned from prior and current data with labels. The outcome of this text review classification is to display the categorized reviews with the calculated tokenization. As for the result of this project, the system will display the categorized review with the classification of positive and negative. The project will also display the genuine or fake review categories with the percentage of criteria from the data training. In average, more 75 % of sample data are correctly classified based on their pre-defined classes and more 55 % of data precisely categorized into fake or genuine label. For future enhancement of this project, a mobile application feature can be added to ease the text classification process quickly.

Metadata

Item Type: Book Section
Creators:
Creators
Email / ID Num.
Suhaimi, Nur Suhailayani
suhailayani@uitm.edu.my
Sharip, Anis Afiqah
anis588@uitm.edu.my
Arbin, Norazam
noraz574@uitm.edu.my
Azyan Izzati, Azyan Izzati
azyanizzati19@gmail.com
Contributors:
Contribution
Name
Email / ID Num.
Patron
Md Badarudin, Ismadi
UNSPECIFIED
Advisor
Jasmis, Jamaluddin
UNSPECIFIED
UiTM Representative
Jono, Mohd Hajar Hasrol
UNSPECIFIED
Director
Suhaimi, Nur Suhailayani
UNSPECIFIED
Team Member
Mat Zain, Nurul Hidayah
UNSPECIFIED
Team Member
Abdullah Sani, Anis Shobirin
UNSPECIFIED
Team Member
Halim, Faiqah Hafidzah
UNSPECIFIED
Team Member
Abd Kadir, Siti Aisyah
UNSPECIFIED
Team Member
Jalil, Ummu Mardhiah
UNSPECIFIED
Subjects: T Technology > T Technology (General) > Information technology. Information systems
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Event Title: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2023)
Event Dates: 8th November 2023
Page Range: p. 6
Keywords: Text mining; Sentiment analysis; Classification
Date: 2023
URI: https://ir.uitm.edu.my/id/eprint/93560
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93560

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