Vol. 1 No. 2 (2025): REGULAR ISSUE JUNE

This issue is available online during June 2025 for the regular issue of June 2025. All articles in this issue (5 original research articles) were authored/co-authored by 12 authors from 5 countries (Indonesia, India, Malaysia, Pakistan, Thailand).

DOI: https://doi.org/10.63913/jds.v1i2

Published: 2025-06-02

Articles

Emotion Detection in Railway Complaints Using Deep Learning and Transformer Models: A Data Mining Approach to Analyzing Public Sentiment on Twitter

Jeffri Prayitno Bangkit Saputra, Aayush Kumar

109-122
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Gender-Based Analysis of New Year Resolutions on Twitter: A Clustering Approach Using K-means Algorithm

Agung Dharmawan Buchdadi, Ammar Salamh Mujali Al-Rawahna

123-137
- PDF
Mining Public Sentiment and Trends in Social Media Discussions on Indonesian Presidential Candidates Using Support Vector Machines

Satrya Fajri Pratama, Arif Mu'amar Wahid

138-151
- PDF
Sentiment Analysis of Public Discourse on Pakistan's Political Parties: A Comparative Study Using VADER and TextBlob Algorithms on Twitter Data

Muhamad Irfan, Abdul Sattar, Ahmad Sher, Muhamad Ijaz

152-167
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Sentiment Analysis of Tweets on Afghan Women’s Rights Using Naive Bayes Classifier: A Data Mining Approach to Understanding Public Discourse

Thosporn Sangsawang, Liu Yang

168-182
- PDF

ISSN 3089-7297 (Online)
Organizer / Collaboration	:	Fakultas Sains dan Teknologi UIN Syarif Hidayatullah Jakarta
Published by	:	Bright Publisher
Website	:	jds.mbicore.com
Mailing Address	:	Graha Permata Estate, Jl. HM Bahrun Blok H9, Sokayasa, Berkoh, Kec. Purwokerto Tim., Kabupaten Banyumas, Jawa Tengah 53146
Email	:	arif@amikompurwokerto.ac.id (principal contact)
		editor@jds.mbicore.com (managing editor)

Vol. 1 No. 2 (2025): REGULAR ISSUE JUNE

Articles

Emotion Detection in Railway Complaints Using Deep Learning and Transformer Models: A Data Mining Approach to Analyzing Public Sentiment on Twitter

Gender-Based Analysis of New Year Resolutions on Twitter: A Clustering Approach Using K-means Algorithm

Mining Public Sentiment and Trends in Social Media Discussions on Indonesian Presidential Candidates Using Support Vector Machines

Sentiment Analysis of Public Discourse on Pakistan's Political Parties: A Comparative Study Using VADER and TextBlob Algorithms on Twitter Data

Sentiment Analysis of Tweets on Afghan Women’s Rights Using Naive Bayes Classifier: A Data Mining Approach to Understanding Public Discourse

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