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Sosialisasi dan Gerakan Bersih Pesisir Pantai Sebagai Upaya Mengurangi Sampah di Kawasan Pantai Carita Kabupaten Pandeglang – Banten Samroh; Wulan, Anjelis Ratu; Yamin, Muhammad Ikrar; Saromah; Arainy, Corizon Sinar; Soderi, Ahmad; Juwari; Diantoro, Karno; Abdurrohman; Sitorus, Anwar T; Rinaldo
Babakti: Journal of Community Engangement Vol. 2 No. 1 (2025): April
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/babakti.v2i1.131

Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kesadaran dan partisipasi masyarakat dalam menjaga kebersihan lingkungan pesisir pantai di Desa Sukarame, Pandeglang, Banten. Metode yang digunakan meliputi penyuluhan, diskusi, dan kegiatan bersih pantai yang melibatkan warga desa sebagai peserta aktif. Observasi awal menunjukkan bahwa akumulasi sampah domestik, terutama plastik, menjadi masalah utama yang mengancam ekosistem laut dan mengurangi daya tarik wisata. Melalui pendekatan edukasi dan pemberdayaan, kegiatan ini memberikan pemahaman tentang pentingnya pengelolaan sampah yang berkelanjutan dan mendukung implementasi kebijakan pemerintah terkait penanganan sampah laut. Hasil kegiatan menunjukkan adanya peningkatan pemahaman masyarakat tentang dampak buruk sampah terhadap lingkungan pesisir. Partisipasi aktif warga terlihat dari antusiasme dalam diskusi dan keterlibatan langsung dalam aksi bersih pantai. Selain itu, kegiatan ini berhasil memotivasi warga untuk membentuk kelompok peduli lingkungan yang fokus pada pengelolaan sampah dan pengembangan potensi lokal. Demonstrasi pengolahan sampah juga mendorong kreativitas peserta dalam menghasilkan produk bernilai ekonomis dari bahan daur ulang. Dengan kolaborasi lintas sektor, program ini diharapkan dapat menciptakan perubahan positif dalam pola pikir dan perilaku masyarakat. Namun, diperlukan upaya berkelanjutan untuk menjaga kesadaran dan partisipasi masyarakat dalam jangka panjang. Kegiatan ini menjadi model yang dapat direplikasi di daerah lain untuk mendukung pelestarian lingkungan pesisir.

Sosialisasi dan Gerakan Bersih Pesisir Pantai Sebagai Upaya Mengurangi Sampah di Kawasan Pantai Carita Kabupaten Pandeglang – Banten Samroh; Wulan, Anjelis Ratu; Yamin, Muhammad Ikrar; Saromah; Arainy, Corizon Sinar; Soderi, Ahmad; Juwari; Diantoro, Karno; Abdurrohman; Sitorus, Anwar T; Rinaldo
Babakti: Journal of Community Engangement Vol. 2 No. 1 (2025): April
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/babakti.v2i1.131

Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kesadaran dan partisipasi masyarakat dalam menjaga kebersihan lingkungan pesisir pantai di Desa Sukarame, Pandeglang, Banten. Metode yang digunakan meliputi penyuluhan, diskusi, dan kegiatan bersih pantai yang melibatkan warga desa sebagai peserta aktif. Observasi awal menunjukkan bahwa akumulasi sampah domestik, terutama plastik, menjadi masalah utama yang mengancam ekosistem laut dan mengurangi daya tarik wisata. Melalui pendekatan edukasi dan pemberdayaan, kegiatan ini memberikan pemahaman tentang pentingnya pengelolaan sampah yang berkelanjutan dan mendukung implementasi kebijakan pemerintah terkait penanganan sampah laut. Hasil kegiatan menunjukkan adanya peningkatan pemahaman masyarakat tentang dampak buruk sampah terhadap lingkungan pesisir. Partisipasi aktif warga terlihat dari antusiasme dalam diskusi dan keterlibatan langsung dalam aksi bersih pantai. Selain itu, kegiatan ini berhasil memotivasi warga untuk membentuk kelompok peduli lingkungan yang fokus pada pengelolaan sampah dan pengembangan potensi lokal. Demonstrasi pengolahan sampah juga mendorong kreativitas peserta dalam menghasilkan produk bernilai ekonomis dari bahan daur ulang. Dengan kolaborasi lintas sektor, program ini diharapkan dapat menciptakan perubahan positif dalam pola pikir dan perilaku masyarakat. Namun, diperlukan upaya berkelanjutan untuk menjaga kesadaran dan partisipasi masyarakat dalam jangka panjang. Kegiatan ini menjadi model yang dapat direplikasi di daerah lain untuk mendukung pelestarian lingkungan pesisir.

The Role of Edge Computing in Secure and Scalable IoT Systems: A Global Perspective Arainy, Corizon Sinar
Digitus : Journal of Computer Science Applications Vol. 3 No. 1 (2025): January 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i1.856

Edge computing has emerged as a pivotal paradigm for optimizing performance, privacy, and deployment within Internet of Things (IoT) ecosystems. This narrative review aims to synthesize the latest scholarly insights into how edge computing addresses key challenges in latency reduction, data security, and resource orchestration. Drawing on a structured literature search from major academic databases, the review analyzed empirical and theoretical contributions spanning various edge-IoT implementations. The findings indicate that edge computing enhances system responsiveness by relocating data processing to proximity of data sources, leading to improved latency and throughput. In applications such as smart cities and remote healthcare, this shift enables more efficient bandwidth usage and timely decision-making. Moreover, privacy-centric technologies including federated learning, blockchain, and zero-trust architectures have proven effective in mitigating data security risks across distributed environments. Despite these advantages, systemic challenges persist, particularly regarding policy, infrastructure, and organizational readiness. Deployment in developing countries often encounters limitations due to regulatory ambiguity and insufficient digital capacity. Successful strategies observed globally emphasize the importance of hybrid cloud-edge-fog architectures and localized deployment models aligned with regional capabilities. This study underscores the need for collaborative public-private innovation, policy reform, and inclusive digital infrastructure development to fully realize the benefits of edge computing in diverse IoT contexts.

Real Time Mobility Intelligence: Evaluating Kafka Based Pipelines in Global Smart Transit Systems Sugianto; Arainy, Corizon Sinar
Digitus : Journal of Computer Science Applications Vol. 3 No. 4 (2025): October 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i4.959

Real-time streaming architectures are redefining the landscape of urban transit analytics by enabling low latency, data driven decision making. This study evaluates and compares the real time data processing capabilities of public transit systems in London, New York, and Singapore. The objective is to determine how architectural choices, data freshness, and machine learning integration influence key performance indicators such as latency, ETA accuracy, and anomaly detection. The methodology involves a multi city case study, where Kafka based pipelines integrated with Apache Flink and Spark were assessed for ingestion, processing, and service delivery. Datasets included GTFS Realtime, SIRI feeds, and contextual APIs (e.g., speed bands and crowd density). Metrics for evaluation included feed latency, mean absolute error (MAE) and root mean square error (RMSE) for ETA, and response times for anomaly detection. The results demonstrate that Singapore’s transit system outperformed its counterparts with the lowest latency (~12s), highest ETA accuracy (MAE = 18s; RMSE = 25s), and superior anomaly detection via multi sensor fusion. London and New York, while technologically robust, faced constraints due to longer feed update intervals and integration complexities. Kafka ML's online learning enhanced model adaptability, significantly reducing ETA prediction errors across dynamic conditions. Furthermore, stress testing revealed Singapore’s architecture as the most resilient under peak load. The study concludes that the effectiveness of real-time urban transit systems depends on harmonizing streaming infrastructure... Singapore’s architecture may serve as a potential reference model for other cities, while recognizing contextual differences in implementation. Singapore’s architecture offers a scalable template for other cities. Ethical considerations, including data governance and passenger privacy, are essential for sustainable implementation.

Hybrid Deep Learning Models for Intrusion Detection in Cloud Networks: A Benchmark-Based Comparative Study Abdurrohman; Arainy, Corizon Sinar
Digitus : Journal of Computer Science Applications Vol. 2 No. 1 (2024): January 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i1.1116

The increasing complexity of cyber threats targeting cloud infrastructures demands advanced and adaptive intrusion detection systems (IDS). This study explores the application of deep learning (DL) models—Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and a hybrid CNN+BiLSTM architecture—for detecting network intrusions using benchmark datasets CIC-IDS2017 and UNSW-NB15. This study contributes by demonstrating how hybrid CNN+BiLSTM architectures enhance intrusion detection accuracy on benchmark datasets, offering low latency and improved recall for rare attack classes, thereby validating their suitability for real-time cloud security deployment. Results show that hybrid CNN+BiLSTM models outperform standalone CNN and LSTM architectures in detection performance, achieving accuracies up to 97.4% on CIC-IDS2017 and 96.85% on UNSW-NB15, while maintaining acceptable latency for real-time deployment. The hybrid model also demonstrates superior F1-scores for rare attack classes and lower false positive rates. The discussion highlights the importance of dataset quality, feature engineering, and the role of adversarial training and model optimization in enhancing robustness. In conclusion, this work affirms the value of hybrid DL architectures for cloud-based IDS and suggests future directions in federated learning, adaptive retraining, and deployment in edge environments.

Hybrid Governance and Policy Frameworks as Catalysts for Biotechnology Innovation: Global Lessons for Emerging Economies Arainy, Corizon Sinar; Sunarno
Novatio : Journal of Management Technology and Innovation Vol. 3 No. 1 (2025): January 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v3i1.853

Biotechnology is increasingly central to global innovation, with progress depending on effective collaboration between universities, industry, and policy frameworks. This study aims to examine institutional and policy drivers of university–industry collaboration (UIC) in biotechnology and identify models that accelerate commercialization and sustainable growth. Using qualitative comparative analysis (QCA) on four cases—SynbiCITE (UK), Bio Innovation Hub (Australia), Panjab University (India), and Oxford Science Enterprises (UK)—data were drawn from reports, policy documents, and innovation databases (WIPO, OECD, GEM). Results show that hybrid governance, flexible funding, transparent intellectual property (IP) frameworks, and targeted policy incentives shorten commercialization timelines, raise start-up survival above 65%, and boost joint patenting activity. University-linked venture capital provides patient capital and mentorship, while mission-driven R&D policies and balanced IP reforms enhance national alignment and innovation outputs. These findings suggest that integrated governance and policy strategies can foster competitive biotechnology ecosystems, and for emerging economies, adapting such models to local contexts offers pathways to accelerated innovation and long-term societal benefits.

Using Artificial Intelligence (AI) to Boost High School Students' Interest in Learning: A Community Service Project Diantoro, Karno; Arainy, Corizon Sinar; Soderi, Ahmad; Juwari; Sakti, Essy Malays Sari
Civitas : Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2024): September 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/civitas.v1i1.329

The advancement of artificial intelligence (AI) technology creates new educational opportunities. The purpose of this community service project is to use AI to boost secondary school students' interest in learning. AI-based tools are integrated into the learning process and a series of workshops are used to carry out the program. Among the techniques employed are AI tutoring systems, interactive learning materials, and teacher training. The quality of assignments, length of learning focus, and class participation all significantly rose as a result of the results, indicating a considerable improvement in students' enthusiasm for learning. According to post-program surveys, 90% of teachers believe AI is effective at increasing student engagement, and 85% of students feel that they are more interested in their classes. The infrastructure of technology and the initial adjustment to the new system present the biggest obstacles. To sum up, incorporating AI into education offers a lot of promise to boost student interest in studying, but doing so calls for a planned strategy and continuous assistance.

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