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All Journal Teknika: Jurnal Sains dan Teknologi Jurnal IPTEK Jurnal Rekayasa Mesin Science and Physics Education Journal (SPEJ) INOVTEK POLBENG INTEGRITAS : Jurnal Pengabdian International Journal of Marine Engineering Innovation and Research Journal of Management and Bussines (JOMB) Journal of Embedded Systems, Security and Intelligent Systems Indonesian Journal of Maritime Technology or abbreviated (ISMATECH)
Santoso, Budhi
Politeknik Negeri Bengkalis
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Journal : journal of embedded systems security and intelligent systems

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IoT–DSS-Based Fleet Management System for Enhancing the Operational Efficiency of Fishing Vessels Romadhoni; Budhi Santoso; Johny Custer; M. Nur Faizi; Mohamed Nasir Alivi; Abdul Razak Shaari
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 2 (2026): June 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.2615

Abstract

Purpose - This study aims to develop an IoT–Decision Support System (DSS)-based Smart Fleet Management System (SFMS) to improve the operational efficiency of small- to medium-scale fishing vessels through real-time monitoring and data-driven decision-making. Design/methods/approach – The proposed system integrates IoT sensors (GPS, fuel flow, temperature) with an ESP32 microcontroller for real-time data acquisition and transmission via MQTT to a cloud platform. A hybrid DSS combining linear regression and fuzzy logic is developed to analyze vessel performance and generate operational recommendations. Field validation was conducted on three fishing vessels, with 1,200 telemetry samples for regression modeling, 300 decision samples for DSS evaluation, and 4,320 data packets for communication analysis. Findings - The implementation of SFMS resulted in significant improvements in operational performance. Fuel consumption decreased by 20.0% (from 50.7 L/h to 40.6 L/h), idle operational time was reduced by 28.9% (from 3.8 to 2.7 hours/day), and the Operational Efficiency Index (OEI) improved by 22.7% (from 0.110 to 0.135 kn/L). The DSS achieved an accuracy of 92.7% in decision recommendations, while system reliability reached 99.2% uptime with low latency and acceptable packet loss (1.48%). Research implications/limitations – Although effective, the study is limited by a small number of vessels and the lack of synchronized environmental data, suggesting the need for broader validation. Originality/value – This study presents a cost-effective and scalable IoT–DSS framework tailored for small-scale fisheries, supporting sustainable operations and maritime digital transformation.
Edge-Based Early Warning for High-Speed Boat Stability Monitoring Muhammad Asep Subandri; Jamal; Fajar Ratnawati; I Gusti Agung Putu Mahendra; Agus Tedyyana; Budhi Santoso
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 3 (2026): September 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i3.11866

Abstract

Purpose - This study aims to develop and evaluate an edge-based early warning prototype for monitoring the stability of high-speed boats using real-time motion data. Design/methods/approach – The study employs an engineering prototype validation design consisting of system requirement analysis, architecture design, implementation, and validation. The system integrates an IMU (MPU-6050) for motion sensing, a Raspberry Pi-based edge computing unit for real-time processing, rule-based classification (Normal/Warning/Critical), and an MQTT-based communication framework connected to the SHISTAMO dashboard. Prototype validation includes functional testing, platform integration, and operational monitoring using controlled scenarios and expert-labeled events. Findings - The results show that the prototype successfully performs end-to-end integration from sensing to visualization. The system achieved 90.4% classification accuracy, with high recall in detecting critical conditions (96.7%), ensuring reliable identification of high-risk events. The local alarm response time was 182 ms, while the dashboard update delay averaged 1.24 s, indicating near-real-time performance. Communication reliability was also high, with 98.8% data delivery success and 97.2% offline synchronization. Research implications/limitations – The findings demonstrate prototype-level feasibility; however, validation is limited to controlled scenarios and does not yet represent diverse sea conditions. The rule-based thresholds and comfort proxy require further calibration and validation through extended sea trials and reference instrumentation. Originality/value – This study contributes an integrated edge-based maritime monitoring prototype that combines motion sensing, offline-capable alarming, real-time telemetry, and fleet-level logging in a single system, specifically tailored to the operational needs of high-speed boats.
Co-Authors Abdul Razak Shaari Agus Tedyyana, Agus Alfanda, Benedicta Dian Aprizawati Aprizawati Ariany, Zulfaidah Berlian Arswendo Adietya Bobi Satria Faizi, M Nur Fajar Ratnawati Hardiyanto Hardiyanto, Hardiyanto I Gusti Agung Putu Mahendra Jamal Jamal Jamal Johny Custer Juanda Kiki Dwi Wulandari M Ikhsan M Ikhsan Mohamed Nasir Alivi Muhammad Alimul Hafiz Muhammad Asep Subandri Muhammad Helmi Nasution, Polaris Pardi Pardi Polaris Nasution Primaningtyas, Widya Emilia Romadhoni Sarwoko Sarwoko Sarwoko Sarwoko Sidik Purwoko Suardi Supriyadi Supriyadi Zulfaidah Ariany