Journal of Renewable Energy and Smart Device
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Articles
51 Documents
<![CDATA[AI-Assisted PID Tuning for Voltage Control of an Axial-Flow Pico-Hydro Generator ]]>
<![CDATA[Machrus Ali]]>;
<![CDATA[Hidayatul Nurohmah]]>;
<![CDATA[Muhammah Agil Haikal]]>;
<![CDATA[Yanuar Mahfudz Safarudin]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.691
<![CDATA[Pico hydropower is a renewable-energy option for isolated communities and low-head run-of-river sites, but axial-flow pico-hydro generators are vulnerable to voltage fluctuation when water flow, hydraulic head, or consumer load changes. This study proposes a novel and reproducible artificial-intelligence-assisted proportional-integral-derivative (PID) tuning framework for voltage control of a 220 V, 2 kW axial-flow turbine generator ZD760-LM-(18-20). The novelty lies in combining a voltage-control-oriented small-signal model of a low-head axial-flow pico-hydro unit, a nonminimum-phase hydraulic zero that represents inverse initial response, identical bounded PID-search constraints, and a composite objective that explicitly penalizes inverse dip, overshoot, settling time, ITAE, and IAE. The plant model combines actuator or electronic-load-controller dynamics, non-elastic water-column dynamics, turbine-generator dynamics, and sensor dynamics. PID gains obtained from Ziegler-Nichols (PID-ZN), Ant Colony Optimization (PID-ACO), and Particle Swarm Optimization (PID-PSO) are compared under Kp = 0-100, Ki = 0-50, and Kd = 0-10. Simulation results show that PID-ZN stabilizes the plant but requires a 6.80 s settling time and produces an ITAE of 2.9603. PID-ACO reduces settling time to 2.26 s and ITAE to 1.1320, whereas PID-PSO gives the lowest ITAE of 1.1311 with only 0.030% overshoot. Compared with PID-ZN, PID-PSO reduces settling time by 66.8% and ITAE by 61.8%. These results indicate that AI-based PID tuning can improve voltage quality in low-cost rural and off-grid pico-hydro systems using practical ELC or simple actuator implementations.]]>
<![CDATA[RTC-Scheduled ESP32 IoT Prototype for Automated Hydroponic Nutrient Irrigation ]]>
<![CDATA[Hidayatul Nurohmah]]>;
<![CDATA[Machrus Ali]]>;
<![CDATA[Ciptian Weried Priananda]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.694
<![CDATA[Reliable nutrient circulation is essential for small-scale hydroponic cultivation, but many Internet of Things (IoT) hydroponic systems depend on multi-parameter sensing, cloud-based decision making, or artificial-intelligence-assisted architectures that can be costly and difficult to reproduce in household and educational settings. This study designs and functionally evaluates a low-cost real-time-clock (RTC)-assisted ESP32 IoT prototype for scheduled hydroponic nutrient irrigation. The practical contribution is a reproducible entry-level automation baseline that helps household users, school laboratories, and community demonstration sites maintain predictable nutrient circulation without continuous manual checking. The system integrates an ESP32 microcontroller, DS3231 RTC, DHT11 temperature-humidity sensor, relay-driven DC nutrient pump, LCD, and Blynk monitoring interface. The main novelty is the use of battery-backed RTC scheduling as a local-first mechanism for routine nutrient-pump actuation, while the cloud dashboard is retained for supervision rather than as the sole timing dependency. This position differentiates the prototype from cloud-centered hydroponic systems whose irrigation execution may depend on network availability. The prototype was programmed to activate the nutrient pump at 07:00 and 16:00 for 10 s per event. Functional validation used four dimensions: environmental reading consistency, RTC timing consistency, pump actuation reliability, and IoT monitoring availability. Daytime DHT11 observations ranged from 29.1 to 31.2 °C and 62 to 68% RH, with mean values of 30.28 °C and 64.50% RH. The RTC showed a recorded 0-s difference from the daily reference time over five observation days within the resolution of the test. The pump executed all observed scheduled ON-OFF events, yielding 100% schedule execution success for two scheduled activations and 100% relay-pump state reliability for four observed states. The Blynk interface displayed temperature, humidity, and pump status during testing. These results demonstrate engineering feasibility for a reproducible scheduled nutrient-irrigation baseline suitable for household-scale hydroponic practice, student laboratories, and introductory IoT learning. The scope is deliberately bounded to prototype-level engineering feasibility: the study evaluates scheduling, actuation, and monitoring, but does not claim nutrient-dosing precision, flow-rate calibration, pH/EC regulation, or crop-yield improvement. Future work should include calibrated reference instruments, pH/EC and flow-rate measurement, nutrient-volume accuracy testing, network-performance analysis, power and cost benchmarking, and controlled plant-growth trials.]]>
<![CDATA[LNG-Based Decarbonization of Small-Scale Maritime Transport: A Technical and Economic Feasibility Study in North Kalimantan ]]>
<![CDATA[Henny Pasandang Nari]]>;
<![CDATA[Yong Wong Kim]]>;
<![CDATA[Mahadir Sirman]]>;
<![CDATA[Romy Sumardiawan]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.700
<![CDATA[Indonesia's vast natural gas reserves present a strategic opportunity to decarbonise its maritime sector, particularly in archipelagic regions such as North Kalimantan, where small wooden and fiberglass vessels rely on high-cost, high-emission diesel fuels, posing environmental and economic challenges. This study employed a mixed-methods approach, combining fuel consumption simulations with stakeholder surveys and interviews to evaluate the technical, economic, and policy feasibility of adopting liquefied natural gas (LNG) for non-conventional inter-island vessels. The technical analysis compared LNG and biodiesel performance on a Mitsubishi 89 kW marine engine regarding thermal efficiency, specific fuel consumption (SFC), and operational costs. Simulation results show that LNG-powered engines achieved 46.46% thermal efficiency and an SFC of 0.140 kg/kWh, compared to 33.85% and 0.1847 kg/kWh for biodiesel. An economic feasibility analysis across eight inter-island routes demonstrated fuel cost savings of 51–68% with LNG relative to biodiesel, with an estimated simple payback period of 3.2–4.5 years for dual-fuel engine retrofitting under baseline fuel price assumptions. Stakeholders acknowledged LNG's benefits but raised concerns about infrastructure limitations and regulatory readiness. This study concludes that LNG adoption for non-conventional vessels is economically and environmentally viable, particularly when aligned with Indonesia's broader energy transition strategies, and provides a scalable model for other archipelagic maritime regions seeking to reduce emissions and fuel dependency.]]>
<![CDATA[Development of a Modern Smart Agricultural System Based on IoT and Artificial Intelligence ]]>
<![CDATA[Denny Irawan]]>;
<![CDATA[Shofitri Juliana Setiyohadi]]>;
<![CDATA[Dewi Dewanti Subrata]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.702
<![CDATA[Abstract – Modern agriculture faces challenges in increasing productivity, efficiency, and sustainability, especially in horticultural commodities such as chilies that have high economic value. The efficiency in question includes the use of increasingly limited land for urban communities. This study proposes the integration of specific multisensor for comprehensive soil parameter monitoring with adaptive decision-making algorithms for chili cultivation in narrow urban areas. The Internet of Things (IoT) is used to monitor environmental conditions in real-time, such as temperature, soil moisture, pH, and nutrient levels (Nitrogen, Phosphorus, and Potassium), through sensors integrated with a wireless network based on the Blynk application and a camera module for early detection of diseases and pests. The collected data is then analysed and processed by a microcontroller using a precise Artificial Intelligence (AI) algorithm, namely the Fuzzy Logic algorithm, to monitor and control land conditions. The integration of IoT and AI is able to increase the efficiency of water and fertilizer use up to 90% of the standard, reduce the risk of crop failure, and improve the quality of chili production results where on the 90th day, chili plants have begun to bear fruit with a fruit diameter at the base of more than 1 cm, a fruit length of more than 3 cm, a stem diameter at the base of about 1 cm, many branches and dense leaves. Compared to conventional agricultural systems, the relevance obtained for urban farmers is: democratization of precision agriculture, optimization of operational costs, real-time risk mitigation, and independent food security. The novelty of this research is the use of adaptive AI Fuzzy Logic, and the integration of visual detection (camera) in one urban ecosystem resulting in high water and fertilizer use efficiency and providing a new contribution in the form of democratization of precision agriculture where industrial-level technology is simplified into a modular ecosystem that is affordable for urban communities. The system that has been built has a structure that allows for development to a broader level including: a modular ecosystem, commodity adaptability, cloud and big data integration, and the potential for vertical farming.]]>
<![CDATA[Modelling and Simulation of Multistep Constant Current Fast Charging for Lithium-Ion Batteries Using a PID Controlled Synchronous Buck Converter ]]>
<![CDATA[Monika Fahmi]]>;
<![CDATA[Deni Tri Laksono]]>;
<![CDATA[Dedi Tri Laksono]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.708
<![CDATA[High-current fast charging of lithium-ion batteries in electric motorcycles is challenged by current instability, voltage overshoot, and accelerated degradation caused by nonlinear electrochemical and thermal dynamics. Conventional single-stage buck converters exhibit limited capability in maintaining precise current regulation across wide state-of-charge (SoC) variations, thereby constraining both efficiency and operational safety. This study proposes a novel adaptive multistep constant-current (MS-CC) fast charging framework specifically tailored for electric motorcycle applications, implemented using a PID-controlled synchronous buck converter. Unlike existing MS-CC approaches, the proposed method introduces a unified control architecture that dynamically schedules five discrete current levels based on real-time voltage thresholds, enabling seamless transition between charging stages without inducing transient spikes. The system is modeled and validated in MATLAB/Simulink, with PID parameters tuned via the Ziegler–Nichols closed-loop method. Simulation results show that the charging current accurately tracks its reference within 0.25% across all stages, with negligible overshoot and stable transient performance. From a practical standpoint, the proposed strategy aligns with the operational constraints of electric motorcycles, such as compact onboard chargers, limited thermal management capacity, and frequent fast-charging cycles. Furthermore, the method reduces switching and conduction losses, mitigates thermal stress, and enhances overall charging efficiency while preserving electrochemical stability. These findings demonstrate that the proposed MS-CC control scheme not only advances the state-of-the-art in charging control strategies but also provides a viable, implementation-ready solution for next-generation electric motorcycle charging systems.]]>
<![CDATA[AI Enabled Smart Web Based System for Monitoring Sustainable Energy Usage in Construction Supply Management ]]>
<![CDATA[Evi Lestari Pratiwi]]>;
<![CDATA[Paula Dewanti]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.802
<![CDATA[The construction industry significantly contributes to global energy consumption and carbon emissions, necessitating innovative solutions for sustainable supply chain management. This study presents an AI-Enabled Smart Web-Based System for Monitoring Sustainable Energy Usage in Construction Supply Management, which innovatively integrates AI-driven energy prediction directly into procurement workflows. The system, developed using the Waterfall model and built upon a Laravel-MySQL-Python (Scikit-Learn) architecture, provides a robust platform for real-time procurement tracking and AI-driven energy usage prediction. Functional testing verified the system's operational reliability, achieving a 100% pass rate. The integrated AI prediction module demonstrated high accuracy with a Mean Absolute Error (MAE) of 0.62 kWh, effectively forecasting energy consumption associated with procurement transactions. User evaluations indicated a 92% overall satisfaction rate, highlighting significant improvements in data transparency, report generation speed, and enhanced understanding of energy-related impacts. This system offers a novel approach to bridge the critical gap between operational efficiency and environmental sustainability in construction supply chains, providing a scalable model for intelligent, energy-aware process transformation. This research contributes a scalable model for fostering sustainable digital transformation within the construction sector, aligning with global sustainability goals and promoting eco-efficient practices.]]>
<![CDATA[Mathematical Modeling of Gap Analysis in Academic Portfolio Assessment Using the Profile Matching Algorithm ]]>
<![CDATA[Ramadhani Noor Pratama]]>;
<![CDATA[Evi Lestari Pratiwi]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.809
<![CDATA[As the transition to lifelong learning continues to advance, Recognition of Prior Learning (RPL) programs have been widely adopted across the higher education sector. For a long time, manual evaluation relying on experience-based archives has consistently faced core pain points: high labor intensity, long processing time, and significant risk of subjective bias. It is therefore extremely urgent to implement and roll out improvements to information technology-driven business processes. To address this gap, this study developed an automated decision support system for archive evaluation. Its core innovation is adapting the Profile Matching algorithm from a static single-objective framework into a dynamic multi-objective gap analysis model. The system includes four core processes: matching applicants’ verified competencies with their course learning outcomes, categorizing course learning outcomes into core and secondary groups, calculating weighted gaps, and generating standardized credit recommendations. Tested on a small dataset containing only 10 historical archives, the system compressed the original multi-day evaluation period to less than 5 minutes. The system boasts both mathematical consistency and traceable audit trails, which allow it to eliminate evaluation bias and safeguard academic integrity. It can also be extended for use in scenarios including higher education micro-credential programs and human resource management.]]>
<![CDATA[Development Plan for a Micro-Hydropower Plant at the Suwung Wastewater Treatment Facility ]]>
<![CDATA[I Made Oka Widyantara]]>;
<![CDATA[Lie Jasa]]>;
<![CDATA[Ni Wayan Budiantari]]>;
<![CDATA[Made Wianda Indiraningtyas]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.819
<![CDATA[This study aimed to analyze the feasibility and design of a Micro Hydro Power Plant (PLTMH) system utilizing wastewater flow at UPTD PAL Provinsi Bali as a renewable energy source to support sustainable energy development and the “Bali Mandiri Energi Bersih 2045” program. The research employed a quantitative engineering design approach through field observations, hydraulic measurements, hydropower calculations, turbine design analysis, electrical power estimation, and preliminary infrastructure planning. Primary data included water discharge, flow velocity, head elevation, pH, and wastewater temperature obtained directly from IPAL Suwung, while secondary data were collected from scientific journals, technical references, and related regulations. The results showed that the wastewater flow at IPAL Suwung has significant hydropower potential with discharge values ranging from 0.2 m³/s to 0.83 m³/s and effective head values between 0.145 m and 0.745 m. Based on the engineering calculations, the proposed Overshot Waterwheel turbine system was capable of generating net electrical power ranging from 0.129 kW under actual minimum conditions to 1.242 kW under maximum engineering design conditions, with estimated annual energy production reaching 9,791.928 kWh. The proposed PLTMH system consists of integrated civil, mechanical, and electrical components, including a cross-flow turbine, pulley transmission system, supporting frame, pillow block bearings, permanent magnet generator, and electronic load control system, with a total estimated project cost of IDR 197,585,297. These findings show that the development of PLTMH at IPAL Suwung is technically feasible, economically reasonable, and environmentally sustainable for supporting renewable energy utilization in wastewater treatment facilities.]]>
<![CDATA[Assessment of Information Technology Governance Maturity Using COBIT 5: A Case Study in the Retail Sector ]]>
<![CDATA[Fenny Lestari]]>;
<![CDATA[A. Haidar Mirza]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.830
<![CDATA[This study evaluates the capability level of information technology (IT) governance for the ASSIST application in a retail company using the COBIT 5 framework. Unlike previous studies that focused on limited governance domains, this research provides a holistic evaluation covering governance, planning, implementation, service management, and performance monitoring processes to identify governance capability gaps and formulate strategic improvement priorities. A qualitative case study approach was employed through interviews, observations, and documentation analysis involving key organizational stakeholders. The assessment was conducted using the COBIT 5 capability model to measure current and expected governance capability levels. The results show that all evaluated domains achieved maturity scores above 86.00%. The average current maturity score reached 87.98%, while the expected capability level averaged 92.82%, resulting in an overall gap of 4.84%. All domains achieved Capability Level 5, showing that governance processes are well established and continuously improved. The largest gap was identified in the EDM domain, showing the need to strengthen executive oversight and strategic governance practices. These findings demonstrate that the ASSIST application is supported by a mature IT governance environment that aligns information technology with business objectives, enhances operational efficiency, supports service continuity, and provides practical guidance for governance optimization in the retail sector.]]>
<![CDATA[Implementation of Financial Dashboards as Strategic Decision-Making Instruments in Public Service Agency (BLU) Institutions of the Ministry of Transportation ]]>
<![CDATA[Sriyono]]>;
<![CDATA[Abdul Hamid Arribathi]]>;
<![CDATA[Nur Azizah]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.893
<![CDATA[This study aims to analyze the implementation of financial dashboards as strategic decision-making instruments in Public Service Agency (BLU) institutions within the Ministry of Transportation, especially on the Banten Maritime Polytechnic. The study employed a descriptive qualitative approach through a literature review by examining scientific journals, government regulations, official documents, BLU financial reports, and publications related to financial management information systems and dashboard implementation. The findings show that prior to the implementation of the financial dashboard, financial management processes, particularly Non-Tax State Revenue (PNBP) management, were still conducted conventionally through periodic and fragmented reports, resulting in delays in financial analysis and limitations in supporting strategic managerial decisions. Financial performance data show that PNBP realization increased from IDR 37.87 billion in 2021 to IDR 76.75 billion in 2022. Following the implementation of the financial dashboard in 2023, PNBP realization reached IDR 87.53 billion in 2023 and further increased to IDR 92.58 billion in 2025. The implementation of the dashboard integrated various financial modules into a single real-time digital platform capable of presenting financial information through interactive graphs, performance indicators, and analytical tables. Technically, the dashboard was developed using a centralized architecture that integrates data from e-Revenue, e-Planning, e-Expenditure, e-Revision, e-Honorarium, e-Official Travel, and e-PKP modules into a unified database that supports real-time data synchronization and financial analytics. The dashboard system enabled institutional leaders to monitor revenue realization, evaluate financial performance, identify revenue trends, compare inter-period financial achievements, and formulate data-driven financial policies more efficiently. The financial dashboards improve transparency, accountability, effectiveness, and responsiveness in BLU financial governance while strengthening strategic decision-making processes within public sector institutions.]]>
