Article Per Year (5 Year)
p-Index From 2019 - 2024
3.533
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan dan Pengajaran Indonesian Journal of Artificial Intelligence and Data Mining JSiI (Jurnal Sistem Informasi) Jurnal Ilmiah Media Sisfo Jurnal Nasional Komputasi dan Teknologi Informasi Indonesian Journal on Learning and Advanced Education (IJOLAE) Journal of Information System,Graphics, Hospitality and Technology Jurnal Nasional Ilmu Komputer JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Indonesian Journal of Informatic Research and Software Engineering Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Karya Abdi Masyarakat Journal of Business Studies and Management Review J-Icon : Jurnal Komputer dan Informatika Jurnal Pengabdian Masyarakat (JPM) Pinang Masak Jurnal Sistem Informasi dan Ilmu Komputer
Utomo, Pradita Eko Prasetyo
Univeristas Jambi
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Physics Public Health Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Indonesian Journal of Artificial Intelligence and Data Mining

 1 
Sentiment Analysis Of Cyberbullying On Twitter Using SentiStrength Ulfa Khaira; Ragil Johanda; Pradita Eko Prasetyo Utomo; Tri Suratno
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.9145

Abstract

Cyberbullying is a form of bullying that takes place across virtually every social media platform. Twitter is a form of social media that allows users to exchange information. Bullying has been a growing problem on Twitter over the past few years. Sentiment analysis is done to identify the element of bullying in a tweet. Sentiments are divided into 3 classes, namely Bullying, Non-Bullying and neutral. There are three steps to classify cyberbullying i.e. collection of data set, preprocessing data, and classification process. This research used sentiStrength, an algorithm which uses a lexicon based approach. This SentiStrength lexicon contains the weight of its sentiment strength. The assessment results from 454 tweets data obtained 161 tweet non-bullying (35.4%), 87 tweet neutral (19.1%), and 206 tweet bullying (45.4%). This research produces an accuracy value of 60.5%.
Co-Authors Agung Mahadewa Arsa, Daniel Aulia Dwiza Puteri Ayu Indryani Azhari SN Benedika Ferdian Hutabarat Benedika Ferdian Hutabarat Bisma Aulia Cepi Ramdan Dedy Setiawan Desi Musfiroh Dwi Agus Kurniawan Dwi Agus Kurniawan Edi Saputra Elisa, Edi Ghaitsa Althafah Wandira Imelda Raudati Indra Weni Jefri Marzal Jefri Marzal Khaira, Ulfa Lucky Enggraini Fitri Made Gitra Aryawan Mauladi Mauladi Mauladi Mauladi Muhammad Iqbal Muksin Alfalah Ragil Johanda Reni Aryani Repaldi Handi Saputra Riyan Mahmudin Rizka Octavia Sandra Rizqa Raaiqa Bintana Salmah Nur Zahra Septika Sari Sari Sulfiyandi Sulfiyandi Suwannit Chareen Chit Sylvia Kartika Wulan Bhayangkari Tasia Maidi Saputri Tri Suratno Tri Suratno Tri Ulfa Khaira Ulfa