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All Journal Jurnal Sistem Informasi dan Sistem Komputer PERAHU (PENERANGAN HUKUM) : JURNAL ILMU HUKUM
Handoyo, Kevin
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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STRATEGI MENGHADAPI CYBERBULLYING DI MEDIA SOSIAL PADA MAHASISWA SEMESTER BARU DI INDONESIA Nugroho, Isaac Yeremia; Handoyo, Kevin; Wijaya, Ricky Junianto; Juniarto, Claudio Erlisto Candra; Mahendrasusila, Fernandi
PERAHU (PENERANGAN HUKUM) : JURNAL ILMU HUKUM Vol 13 No 1 (2025): PERAHU (PENERANGAN HUKUM) : Jurnal Ilmu Hukum
Publisher : Universitas Kapuas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51826/perahu.v13i1.1454

Abstract

Cyberbullying on social media has become a significant challenge for new semester students in Indonesia, who are still adapting to their new academic and social environments. A lack of awareness and skills in dealing with cyberbullying can negatively impact their mental health and academic performance. This study aims to explore strategies that students can apply in facing cyberbullying, both through preventive and responsive approaches. The research employs a qualitative approach using in-depth interviews and surveys conducted with new semester students at several universities in Indonesia. The findings indicate that students tend to adopt strategies such as limiting social media interactions, enhancing digital literacy, and seeking support from friends and family. The implications of this study are expected to provide recommendations for educational institutions in designing educational programs and policies to help students cope with challenges in the digital world.
Prediksi Dampak Gempa Bumi di Indonesia Dengan Menggunakan Artificial Neural Network Handoyo, Kevin; Finsensia Riti, Yosefina; Junianto Wijaya, Ricky
Jurnal Sistem Informasi dan Sistem Komputer Vol 11 No 1 (2026): Vol 11 No 1 - 2026
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v11i1.964

Abstract

Penelitian ini memiliki tujuan untuk membangun sistem prediksi dampak gempa bumi di Indonesia dengan mengimplementasikan metode kecerdasan buatan yaitu Artificial Neural Network (ANN). Dataset yang digunakan adalah data gempa bumi Indonesia tahun 2023–2025 yang telah melalui proses preprocessing, labeling, dan penyeimbangan kelas dengan metode SMOTE. Model ANN dirancang dengan 24 input neuron, dua hidden layer, dan output 3 kelas dampak. Pelatihan model dilakukan menggunakan data training sebesar 70% dan data testing sebesar 30%. Evaluasi dilakukan dengan menggunakan matrik evaluasi seperti accuracy, precision, recall, dan F1-score. Hasil yang diperoleh menunjukkan accuracy ANN sebesar 99% dan F1-score tinggi pada semua kelas termasuk kelas minoritas. Pengujian lanjutan menunjukkan model tetap akurat dalam memprediksi dampak berdasarkan input magnitudo dan kedalaman.
Co-Authors Finsensia Riti, Yosefina Junianto Wijaya, Ricky Juniarto, Claudio Erlisto Candra Mahendrasusila, Fernandi Nugroho, Isaac Yeremia Wijaya, Ricky Junianto