Improved Model for Identifying the Cyberbullying based on Tweets of Twitter

Authors

  • Darwin Samalo Computer Science Department, BINUS Graduate Program – Master of Computer Science, Bina Nusantara University Jakarta, Indonesia
  • Rizky Martin
  • Ditdit Nugeraha Utama

DOI:

https://doi.org/10.31449/inf.v47i6.4534

Abstract

The surge of cyberbullying on social media platforms is a major concern in today's digital age, with its prevalence escalating alongside advancements in technology. Thus, devising methods to detect and eliminate cyberbullying has become a crucial task. This research meticulously presents a refined model for identifying instances of cyberbullying, building on previous methodologies. The process of devising the model involved a thorough literature review, object-oriented design, and decision tree methodologies to shape the labelling procedure and build the classifier. Data pre-processing was executed using RapidMiner, considering six intrinsic components. The final model successfully classified Indonesian-language tweets into five distinct categories: animal, psychology and stupidity, disabled person, attitude, and general bullying, with an accuracy rate of 99.56%.

Author Biography

Darwin Samalo, Computer Science Department, BINUS Graduate Program – Master of Computer Science, Bina Nusantara University Jakarta, Indonesia

Darwin Samalo was born in Bukit- tinggi, Indonesia. He is currently pursuing his master’s degree in computer science at Bina Nusantara University, Jakarta, Indonesia. His research inte- rest is regarding sentiment analysis, text mining, and machine learning. He is currently working as a Software Engi- neering on IT Division in Bina Nusan- tara. He helps to develop internal ap- plications that are used to help busi- ness units within the Bina Nusantara Group

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Published

2023-06-12

How to Cite

Samalo, D., Martin, R., & Utama, D. N. (2023). Improved Model for Identifying the Cyberbullying based on Tweets of Twitter. Informatica, 47(6). https://doi.org/10.31449/inf.v47i6.4534

Issue

Vol. 47 No. 6 (2023): Online-only issue

Section

Online-only

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