Sentiment Analysis of JNT Express, JNE and Sicepat Customer Satisfaction on Twitter Using Multinomial Naïve Bayes Method

The number of online buying and selling transactions through e-commerce as well as the need to deliver personal goods has led to an increase in the number of people using goods delivery services. Goods delivery service companies that are a favorite among Indonesians are JNT Express, JNE and Sicepat. Currently, these companies have been actively using various communication media, including Twitter to interact with their customers. Customer opinions about delivery services often appear on Twitter and sometimes become the main issue that steals the attention until it becomes a headline and becomes a hot conversation among the public. Analyzing customer sentiment through comments on Twitter is very important for JNT Express, JNE, and Sicepat. The Multinomial Naïve Bayes method was used to explore customers' views on their delivery services. A total of 1069 comment data was obtained using Google Collaboratory with the help of tweet-harvest from January 1, 2023 to December 31, 2023. The sentiment classification process was performed by utilizing Naïve Bayes classification to identify whether the reviews are positive, negative, or neutral. The classification results of the dataset with a composition of 75% of the training data and 25% of the test data on the JNT Express expedition obtained an accuracy result of 80%, JNE obtained an accuracy result of 75% and Sicepat 67%. For datasets with 80% and 20% composition, JNT Express obtained an accuracy of 77%, JNE 74% and Sicepat 65%.

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Publication Details

Published
2024-09-26
DOI
https://doi.org/10.1109/eecsi63442.2024.10776297
Citations
6
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
2.08
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article

Sentiment Analysis of JNT Express, JNE and Sicepat Customer Satisfaction on Twitter Using Multinomial Naïve Bayes Method

M Yoka Fathoni, Zahra Fikri Ayu Nirwana
6 citations
Sentiment Analysis and Opinion Mining
2.08
article

Sentiment Analysis of JNT Express, JNE and Sicepat Customer Satisfaction on Twitter Using Multinomial Naïve Bayes Method

M Yoka Fathoni, Zahra Fikri Ayu Nirwana
article en
6 citations

Abstract

The number of online buying and selling transactions through e-commerce as well as the need to deliver personal goods has led to an increase in the number of people using goods delivery services. Goods delivery service companies that are a favorite among Indonesians are JNT Express, JNE and Sicepat. Currently, these companies have been actively using various communication media, including Twitter to interact with their customers. Customer opinions about delivery services often appear on Twitter and sometimes become the main issue that steals the attention until it becomes a headline and becomes a hot conversation among the public. Analyzing customer sentiment through comments on Twitter is very important for JNT Express, JNE, and Sicepat. The Multinomial Naïve Bayes method was used to explore customers' views on their delivery services. A total of 1069 comment data was obtained using Google Collaboratory with the help of tweet-harvest from January 1, 2023 to December 31, 2023. The sentiment classification process was performed by utilizing Naïve Bayes classification to identify whether the reviews are positive, negative, or neutral. The classification results of the dataset with a composition of 75% of the training data and 25% of the test data on the JNT Express expedition obtained an accuracy result of 80%, JNE obtained an accuracy result of 75% and Sicepat 67%. For datasets with 80% and 20% composition, JNT Express obtained an accuracy of 77%, JNE 74% and Sicepat 65%.

Institut Teknologi Telkom Purwokerto (ID)
Decent work and economic growth
Openalex Percentile: Top 11%
Sentiment Analysis and Opinion Mining
2.08
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