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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar International Journal of Humanities Education and Social Sciences
Bagus Satrio Wicaksono
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Humanities Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences Other

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Maritime Cyber Geopolitics: New Threats to Maritime Security in the Digital Era Bagus Satrio Wicaksono; Asep Adang Supriyadi; Budiman Djoko Said; Pujo Widodo; Panji Suwarno
International Journal Of Humanities Education and Social Sciences (IJHESS) Vol 4 No 4 (2025): IJHESS FEBRUARY 2025
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhess.v4i4.1183

Abstract

The digital era has transformed the maritime sector, integrating the oceans into the global internet network and creating new opportunities in trade and communications. However, this connectivity has also created significant cyber threats, leading to the emergence of cyber maritime geopolitics—the struggle for power at sea through information and communications technology (ICT). These threats include cyberattacks on maritime navigation systems, critical infrastructure, and data theft, all of which can disrupt global trade and trigger conflict. As maritime security becomes increasingly important, countries need to increase international cooperation, strengthen cyber defenses, and develop effective strategies to combat these threats. This paper aims to understand the challenges of cyber maritime geopolitics and proposes a multisectoral approach involving various stakeholders. Through comprehensive qualitative research, including a literature review and document analysis, this research identifies patterns and offers insights into strengthening maritime security policies. This research underscores the need for international collaboration, technological advances and investment in cybersecurity to ensure sustainable maritime security in the digital era. For Indonesia, a country with extensive maritime interests, implementing this strategy is very important to protect maritime infrastructure and maintain regional stability.
Penerapan Explainable Boosting Machine Pada Hasil Pencarian Best Matching 25 Sebagai Rekomendasi Kualitas Buku Dengan Penjelasan Fitur Bagus Satrio Wicaksono; Intan Yuniar Purbasari; Henni Endah Wahanani
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 No. 03, September 2026 Produce
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.61788

Abstract

The rapid growth of digital book collections creates information overload, complicating book discovery for readers. Traditional BM25 search systems retrieve keyword-relevant documents but completely ignore book quality signals. Furthermore, conventional machine learning re-ranking models act as black-boxes, obscuring their decision-making processes, while post-hoc explanation methods only provide approximations that do not represent the model's exact logic. This study proposes a two-stage ranking architecture integrating an Explainable Boosting Machine (EBM) as a glass-box re-ranker over BM25 initial retrievals. Trained on 13.4 million Goodreads interaction records, the EBM predicts general book quality based on metadata. Evaluation using 50 queries demonstrates that EBM with feature interactions achieves an NDCG@10 of 0.9373, outperforming the BM25 baseline (0.9284) specifically on exploratory genre queries by prioritizing popular, high-quality books. Global interpretability analysis reveals that popularity contributes most significantly to prediction scores, whereas local explanations precisely map individual feature attributions. Ablation testing confirms the faithfulness of these explanations; removing dominant features consistently reduces prediction scores matching their exact shape function values. In conclusion, integrating EBM successfully enhances BM25 ranking quality through community-based signals while providing fully transparent and auditable feature explanations.
Co-Authors Henni Endah Wahanani Intan Yuniar Purbasari Pujo Widodo Said, Budiman Djoko Supriyadi, Asep Adang Suwarno, Panji