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All Journal Prosiding National Conference for Community Service Project Jurnal Informatika
Muthia Andini
Universitas Internasional Batam
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education

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Peran Bawaslu dan Mahasiswa Universitas Internasional Batam dalam Membangun Sifat Partisipatif Pemilu kepada Pemilih Pemula SMA Negeri 24 Batam Sandy Estrina Claudya; Natasya Cahyani; Icha Heriaty Togatorop; Ethan Abednego Tjahyadi; Muthia Andini; Maya Marsevani; Antoni Foo Siang An; Marsheila Pratista; Frandy Tansri; Melvina Tan; Benson Pang Tian Poh; Winson Winson; Rizky Putra; Wildan Laksamana Sakti
National Conference for Community Service Project (NaCosPro) Vol 5 No 1 (2023): The 5th National Conference for Community Service Project 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v5i1.8287

Abstract

Sekolah merupakan tempat penyaluran ilmu pengetahuan dan keterampilan. Tidak hanya selalu mengenai pendidikan akademik serta non-akademik, sekolah dapat menjadi tempat yang tepat dalam menyalurkan pendidikan politik. Mengingat murid SMA/SMK/sederajat merupakan pemilih pemula yang memerlukan pemahaman mengenai pemilu. Tujuan PKM ini adalah memberikan pengetahuan politik serta meningkatkan partisipatif pemilu bagi pemilih pemula dengan sasaran sebanyak 400 siswa/i kelas XI dan XII SMA Negeri 24 Batam. Metode yang digunakan adalah pendidikan masyarakat dengan teknik pengumpulan data observasi. Adapun analisa data yang digunakan berbentuk kualitatif dengan sumber data sekunder berupa materi seputar pengetahuan pemilu dari Bawaslu. Adapun kesimpulan yang diperoleh melalui kegiatan PKM yang telah dilakukan, yaitu meningkatkan pengetahuan pendidikan politik bagi pemilih pemula, meningkatkan partisipatif pemilih pemula dengan mengikut sertakan murid SMA Negeri 24 Batam dalam lomba guna menyerukan pemilu, serta menjaga kualitas pemilih yang cerdas di masa depan.
Semi-Supervised Bullying Detection in Narrative Student Counselling Reports Using a Hybrid CNN-LSTM with Pseudo-Labelling Suwarno Suwarno; Muthia Andini; Mangapul Siahaan
Jurnal Informatika Vol. 13 No. 1 (2026): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ji.v13i1.11512

Abstract

Bullying incidents in schools are often documented in narrative student counselling reports containing informal language, emotional expressions, and contextual dependencies, which pose challenges for automated text classification, particularly under limited labeled data conditions. This study aims to develop a bullying detection model for narrative student counselling reports using a Hybrid CNN-LSTM architecture combined with a pseudo-labelling-based semi-supervised learning approach. The proposed model is trained through a two-stage process, consisting of pre-training on approximately 70,000 publicly available abusive-language texts and fine-tuning using 1,000 anonymized student counselling reports validated by guidance counsellors. Pseudo-labelling is employed to expand the training data while preserving domain relevance and adhering to ethical considerations. Experimental results show that the proposed model achieves an accuracy of 0.8698, a recall of 0.8570, and an F1-score of 0.7951. Although the precision value (0.7415) is relatively lower, higher recall is prioritized to reduce the risk of overlooking potential bullying cases in the school counselling context. Comparative analysis with Logistic Regression and Linear SVM indicates that the Hybrid CNN-LSTM model demonstrates more stable performance when processing longer narrative inputs that require contextual interpretation. This study contributes empirical evidence on the effectiveness of semi-supervised deep learning for bullying detection in low-resource, narrative student counselling data, a setting that remains underexplored in prior work.
Co-Authors Antoni Foo Siang An Benson Pang Tian Poh Ethan Abednego Tjahyadi Frandy Tansri Icha Heriaty Togatorop Marsevani, Maya Marsheila Pratista Melvina Tan Mungkap Mangapul Siahaan Natasya Cahyani Rizky Putra Sandy Estrina Claudya Suwarno Liang Wildan Laksamana Sakti Winson Winson