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All Journal Jurnal Teknologi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURIKOM (Jurnal Riset Komputer) Jurnal Teknologi
Farasalsabila, Fidya
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Deteksi Cyberbullying Menggunakan BERT dan Bi-LSTM Farasalsabila, Fidya; Utami, Ema; Hanafi, Hanafi
Jurnal Teknologi Vol 17 No 1 (2024): Jurnal Teknologi
Publisher : Jurnal Teknologi, Fakultas Teknik, Universitas AKPRIND Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/jurtek.v17i1.4636

Abstract

Cyberbullying is a digital problem that is not a new phenomenon. This existed before the advent of social networks, and cyberbullying has a wide impact, including a person's mental and physiological conditions such as sadness, anxiety and depression. The main objective of this research is to develop an effective cyberbullying detection system using natural language processing techniques. The method used in this research includes the application of the BERT (Bi-Directional Encoder Representations from Transformers) and Bi-LSTM (Bi-Directional Long Short-Term Memory) models as a deep learning approach to analyze text and detect cyberbullying behavior. This approach allows the system to understand complex language contexts and capture patterns that traditional methods may find difficult to identify. Testing was carried out using a dataset that included various types of Indonesian language texts containing cyber bullying acts. The research results show that the combination of BERT and Bi-LSTM is able to provide superior detection performance with a high accuracy rate of 90% and the ability to identify variations of cyber bullying. This research makes a significant contribution to efforts to protect individuals from the negative impacts of cyber bullying through the development of a sophisticated and adaptive detection system.
Deteksi Cyberbullying Menggunakan BERT dan Bi-LSTM Farasalsabila, Fidya; Utami, Ema; Hanafi, Hanafi
Jurnal Teknologi Vol 17 No 1 (2024): Jurnal Teknologi
Publisher : Jurnal Teknologi, Fakultas Teknik, Universitas AKPRIND Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/jurtek.v17i1.4636

Abstract

Cyberbullying is a digital problem that is not a new phenomenon. This existed before the advent of social networks, and cyberbullying has a wide impact, including a person's mental and physiological conditions such as sadness, anxiety and depression. The main objective of this research is to develop an effective cyberbullying detection system using natural language processing techniques. The method used in this research includes the application of the BERT (Bi-Directional Encoder Representations from Transformers) and Bi-LSTM (Bi-Directional Long Short-Term Memory) models as a deep learning approach to analyze text and detect cyberbullying behavior. This approach allows the system to understand complex language contexts and capture patterns that traditional methods may find difficult to identify. Testing was carried out using a dataset that included various types of Indonesian language texts containing cyber bullying acts. The research results show that the combination of BERT and Bi-LSTM is able to provide superior detection performance with a high accuracy rate of 90% and the ability to identify variations of cyber bullying. This research makes a significant contribution to efforts to protect individuals from the negative impacts of cyber bullying through the development of a sophisticated and adaptive detection system.
Boosting Methods for Multi-label Data Cyberbullying Farasalsabila, Fidya; Aritonang, Mhd Adi Setiawan; Jabnabillah, Faradiba; Moniva, Anip; Lestari, Verra Budhi; Handayani, Rizky
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8721

Abstract

Easy accessibility to the internet and social media allows individuals to communicate anonymously, providing opportunities for abusive and harmful behavior. The psychological impact of cyberbullying can be very detrimental, triggering stress, depression, and even causing more serious consequences such as suicide. This paper describes cyberbullying sentiment analysis with a focus on the use of four different boosting methods, namely Gradient Booster, Gradient Booster, XGBoost, AdaBoost, dan LightGBM on a multi-label public dataset covering 6 categories. The aim of this research is to compare and analyze the relative performance of these boosting methods in overcoming the challenges of multi-label sentiment analysis in the context of cyberbullying. Results reveal that XGBoost and LightGBM have a tendency to more effectively overcome the challenges of detecting cyberbullying in more complex categories, making a positive contribution to the development of superior detection systems in the context of multi-label sentiment analysis. This research contributes to the field by providing a comparative analysis of state-of-the-art boosting algorithms, highlighting their strengths in multi-label classification tasks, and offering practical insights for developing more accurate and reliable cyberbullying detection systems. The findings from this study are expected to serve as a reference for future development of machine learning-based tools that can help mitigate the psychological harm caused by online abuse, particularly in detecting subtle and complex forms of cyberbullying behavior.
Pelatihan dasar pemrograman untuk membangkitkan minat siswa pada dunia pemrograman di SMA Kartini Batam Nasution, Nadia Widari; Candra, Joni Eka; Farasalsabila, Fidya; Reza, Widya; Kurnia, Okki; Simatupang, Devid Trinaldo
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 5 (2025): September (In Progress)
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i5.33988

Abstract

AbstrakTuntutan global menuntut dunia pendidikan untuk selalu dan senantiasa menyesuaikan perkembangan teknologi terhadap usaha dalam peningkatan mutu pendidikan. SMA Kartini Batam adalah sekolah menengah atas swasta di Batam, Kepulauan Riau. Dengan visi dan misi yang jelas, SMA Kartini di Yayasan Keluarga Batam bertujuan untuk menciptakan lingkungan pembelajaran yang dinamis, iklusif, dan mendukung pengembangan karakter positif. Pemrograman Dasar adalah salah satu mata pelajaran dasar dalam bidang Teknologi, Informasi, dan Komunikasi (TIK). Pada pembelajaran sekarang ini sangat penting memiliki pengetahuan TIK. Namun, SMA Kartini Batam belum terbiasa menggunakan bahasa pemrograman Python untuk pemrograman. Oleh karena itu, dasar pemrograman penting dipelajari khususnya siswa/i jurusan teknik informatika dan komputer. Menerapkan dasar pemrograman di sekolah dapat membantu meningkatkan minat siswa dalam bidang teknologi seperti pembuatan aplikasi, game dan website. Dengan adanya pelatihan dasar pemrograman bagi siswa/i SMA Kartini Batam sebagai landasan yang penting untuk mempelajari bahasa pemrograman dan mengembangkan keterampilan pemrograman. Python merupakan bahasa pemrograman yang populer dan mudah dipelajari. Python banyak digunakan dalam pengembangan perangkat lunak, data science, dan machine learning. Menerapkan dasar pemrograman di sekolah juga dapat membantu meningkatkan minat siswa dalam bidang teknologi seperti pembuatan aplikasi, game dan website. Kata kunci: teknologi; dasar pemrograman; python; minat siswa; mutu pendidikan. AbstractGlobal demands require the world of education to always and continuously adapt to technological developments in efforts to improve the quality of education. SMA Kartini Batam is a private high school in Batam, Riau Islands. With a clear vision and mission, SMA Kartini at the Batam Family Foundation aims to create a dynamic, inclusive learning environment and support positive character development. Basic Programming is one of the basic subjects in the field of Technology, Information, and Communication (ICT). In today's learning, it is very important to have knowledge of ICT. However, SMA Kartini Batam is not yet accustomed to using the Python programming language for programming. Therefore, basic programming is important to learn, especially for students majoring in informatics and computer engineering. Implementing basic programming in schools can help increase student interest in technology fields such as application, game and website development. With basic programming training for SMA Kartini Batam students as an important foundation for learning programming languages and developing programming skills. Python is a popular and easy-to-learn programming language. Python is widely used in software development, data science, and machine learning. Implementing basic programming in schools can also help increase student interest in technology fields such as application, game and website development. Keywords: technology; basic progamming; python; student interests; quality of education.
Co-Authors candra, joni eka Ema Utami Hanafi Hanafi Handayani, Rizky Jabnabillah, Faradiba Kurnia, Okki Lestari, Verra Budhi Mhd Adi Setiawan Aritonang Moniva, Anip Nasution, Nadia Widari Simatupang, Devid Trinaldo Widya Reza