Sentiment Analysis in the Sales Review of Indonesian Marketplace by Utilizing Support Vector Machine

Anang Anggono Lutfi,Adhistya Erna Permanasari,Silmi Fauziati

doi:10.20473/jisebi.4.1.57-64

Anang Anggono Lutfi, Adhistya Erna Permanasari + Show 1 more

Open Access

https://doi.org/10.20473/jisebi.4.1.57-64

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Abstract

The online store is changing people’s shopping behavior. Despite the fact, the potential customer’s distrust in the quality of products and service is one of the online store’s weaknesses. A review is provided by the online stores to overcome this weakness. Customers often write a review using languages that are not well structured. Sentiment analysis is used to extract the polarity of the unstructured texts. This research attempted to do a sentiment analysis in the sales review. Sentiment analysis in sales reviews can be used as a tool to evaluate the sales. This research intends to conduct a sentiment analysis in the sales review of Indonesian marketplace by utilizing Support Vector Machine and Naive Bayes. The reviews of the data are gathered from one of Indonesian marketplace, Bukalapak. The data are classified into positive or negative class. TF-IDF is used to feature extraction. The experiment shows that Support Vector Machine with linear kernel provides higher accuracy than Naive Bayes. Support Vector Machine shows the highest accuracy average. The generated accuracy is 93.65%. This approach of sentiment analysis in sales review can be used as the base of intelligent sales evaluation for online stores in the future.

Highlights

Information technology is utilized in many sectors of communitie’s life
The experiment was conducted using Support Vector Machines (SVM) and Naive Bayes (NB) accuracy results when it is using 25%, 50%, 75%, and 100% of the features with highest Term Frequency-Inverse Document Frequency (TF-IDF)
This paper intends to classify the texts using Support Vector Machine and Naive Bayes to figure out the sentiment of the sales review

Summary

Introduction

Information technology is utilized in many sectors of communitie’s life. The utilization of information technology helps people to solve various problems. The online store is an example of information technology utilization in the economic sector. The existence of online stores has indirectly changed people’s shopping behavior in purchasing goods and service. The change of behavior happens around the world, including in Indonesia. In 2016, the internet user in Indonesia reached 132.7 million people [1]. Over half of the users (84.2 million) have ever conducted an online transaction. There are around 46.1 million users doing online transaction more than once a month, 18.8 million users doing it less than once in a month, 6.2 million users doing it once a week, and over 5 million doing it more than once a week. The data show that the active internet users in Indonesia are active in doing online transaction

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