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All Journal Computer Architecture and Signal Processing Software Engineering in Computing Systems
Bobby Kurniawan
Universitas Komputer Indonesia

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Adaptive-Cognitive Smart Farming Architectures for Food Security Resilience: A Systematic Literature Review of IoT and AI-Based Approaches Ridho Taufiq Subagio; Zainal Arifin Hasibuan; Bobby Kurniawan; Sri Supatmi; Hidayat Hidayat; Citra Noviyasari
Computer Architecture and Signal Processing Vol. 1 No. 2 (2026): June: Computer Architecture and Signal Processing
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/casp.v1i2.445

Abstract

Food security resilience has become an increasingly critical global concern due to the combined effects of climate change, population growth, and resource scarcity. Conventional agricultural practices are no longer sufficient to meet rising food demands, thereby necessitating the adoption of intelligent and adaptive technological solutions. Smart farming, enabled by the integration of the Internet of Things (IoT) and Artificial Intelligence (AI), has emerged as a promising approach to enhance agricultural productivity, efficiency, and sustainability. However, existing smart farming systems remain fragmented and lack adaptive and cognitive capabilities required to dynamically respond to environmental variability. This study proposes an adaptive-cognitive smart farming architecture that integrates IoT, AI, edge-fog-cloud computing, federated learning, and digital twin technologies into a unified framework. A Systematic Literature Review (SLR) is conducted to synthesize insights from 60 high-quality publications indexed in IEEE, Elsevier, and Scopus databases. The proposed architecture adopts a multi-layered design consisting of sensing, edge-fog, cloud, cognitive, and application layers, enabling real-time data processing, distributed intelligence, and adaptive decision-making. To validate the proposed model, experimental simulations are performed using key performance indicators, including accuracy, mean squared error (MSE), latency, and resource efficiency. The results indicate that the proposed approach achieves superior performance, with an accuracy of 89%, a substantial reduction in latency, and improved resource utilization. These findings demonstrate that incorporating adaptive and cognitive intelligence significantly enhances system responsiveness and decision-making capabilities. This study contributes to both theory and practice by introducing a comprehensive framework for next-generation smart farming systems, ultimately supporting food security resilience in an increasingly uncertain environment.
Success Factors of Government Digital Applications in Public Service Delivery: A Systematic Literature Review Rifqi Fahrudin; Zainal Arifin Hasibuan; Bobby Kurniawan; Sri Supatmi
Software Engineering in Computing Systems Vol. 1 No. 2 (2026): May: Software Engineering in Computing Systems
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/secons.v1i2.395

Abstract

The rapid development of digital government applications has significantly transformed public service delivery; however, their success remains inconsistent due to the complexity of multiple influencing factors. Many government digital systems experience low adoption, usability challenges, and limited impact on service quality, indicating the need for a comprehensive understanding of the determinants of success. This study aims to identify and synthesize the critical success factors of government digital applications in public service delivery. To achieve this objective, a systematic literature review (SLR) was conducted using the Scopus database, applying a predefined search strategy and PRISMA-based screening process. From an initial set of 176 articles, 44 relevant studies were selected and analyzed using a coding framework to classify success factors into four dimensions: technological, organizational, user, and governance. The results show that digital government success is inherently multidimensional, with user-related factors such as trust, usability, and satisfaction emerging as the most dominant, while technological factors function as enabling components and organizational and governance factors ensure sustainability and effectiveness. Furthermore, the findings reveal significant research gaps, particularly the lack of integrated frameworks and the fragmented treatment of success factors in existing studies. This study concludes by proposing an integrated classification framework that provides a comprehensive understanding of digital government success and offers practical guidance for policymakers in designing more effective and sustainable digital public services.
Co-Authors Citra Noviyasari Hidayat Hidayat Ridho Taufiq Subagio Rifqi Fahrudin Sri Supatmi Zainal Arifin Hasibuan