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All Journal JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan JE-Unisla JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) ALINIER: Journal of Artificial Intelligence & Applications Jurnal Fortech SinarFe7 Journal FORTEI-JEERI Jurnal FORTECH Journal of Renewable Energy and Smart Device Jurnal JEETech DIMAS-UNDAR Nucleus Journal
Hidayatul Nurohmah
Universitas Darul Ulum
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Rekonfigurasi Jaringan Distribusi Radial 65 Bus Berbasis Binary Particle Swarm Optimization (BPSO) Machrus Ali; Hidayatul Nurohmah; Dwi Ajiatmo
Jurnal JEETech Vol. 3 No. 1 (2022): Nomor 1 May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v3i1.3108

Abstract

The configuration of a radial distribution network is difficult to simplify because it is very complex. This network reconfiguration is used to redesign the configuration of the radial distribution network by opening and closing switches on the distribution network. The feeder of Purwoasri, The feeder of Purwoasri, Rayon Kertosono has 65 buses which cause the Mojokerto area to have a very large loss so it needs to be reconfigured.. The resulting power flow will result in network power losses due to configuration. The reconfiguration process will be repeated until a configuration form that produces the smallest power losses is obtained. The number of feeders and buses on the network will be difficult if done manually and takes a very long time, so solving the problem must use a computer program. Network reconfiguration using the Matlab 2013a program will analyze its power flow using the Newton Raphson method and using the Binary Particle Swarm Optimization (BPSO) artificial intelligence method. Before reconfiguration, the network experienced losses of 1169,1374 kWatt after reconfiguration experienced losses of 635,7444 kWatt. The results of the reconfiguration can reduce losses of 635,74440 kWatt or 45,6228 % from the previous loss.
Komparasi PID, FLC, dan ANFIS sebagai Kontroller Dual Axis Tracking Photovoltaic berbasis Bat Algorithm Hidayatul Nurohmah; Machrus Ali; Dwi Ajiatmo
Jurnal JEETech Vol. 3 No. 2 (2022): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Photovoltaic is a renewable electrical energy generator that is very suitable for tropical countries that get a lot of sunlight. However, this generator has low efficiency. To overcome this deficiency, several researchers have optimized the conventional dual-axis tracking solar method. Research is needed to optimize using artificial intelligence, in this case, the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Bat Algorithm (BA). By comparing the performance of the model without control, conventional PID model, PID Auto tuning MatLab, Fuzzy Logic Controller (FLC) method, ANFIS method, and ANFIS-BA method. The simulation results show that the best model design on the horizontal axis and vertical axis dual tracking photovoltaic is ANFIS-BA with the smallest overshot, smallest undershot, and the fastest settling time of all model designs.
Optimasi SMES untuk Load Frequency Control pada PLTMH Menggunakan ICA dan BA Machrus Ali; Hidayatul Nurohmah; Muhammad Agil Haikal
Jurnal JEETech Vol. 6 No. 1 (2025): Nomor 1 May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v6i1.6110

Abstract

Micro hydro power plants (MHPPs) are increasingly important for decentralized renewable electrification, especially in isolated and rural grids where low inertia makes frequency highly sensitive to abrupt consumer-load variations. The main problem addressed in this study is that governor-turbine dynamics and conventional controller tuning are often insufficient to suppress transient frequency deviation rapidly, while previous MHPP load frequency control (LFC) studies commonly report ICA, BA, SMES, or CES results separately and in per-unit form, making practical comparison less direct. This paper contributes a current benchmark-based synthesis and normalized comparative analysis of Superconducting Magnetic Energy Storage (SMES)-assisted LFC for a 40 kVA, 32 kW, 50 Hz MHPP using the Imperialist Competitive Algorithm (ICA) and the Bat Algorithm (BA) with Integral Time Absolute Error (ITAE) as the optimization objective. Literature benchmark data are reprocessed by converting per-unit overshoot into Hz and by calculating reduction relative to the uncontrolled condition to provide a transparent and reproducible engineering interpretation. ICA-based PID-SMES gives a frequency overshoot of -4.11 x 10^-5 pu (-0.002055 Hz), whereas BA-based SMES-PID gives -4.038 x 10^-5 pu (-0.002019 Hz). Compared with the uncontrolled system, the overshoot reduction reaches 87.07% for ICA and 87.30% for BA. The main contribution of this work is a clarified research-gap map, a normalized ICA-BA comparison on a comparable MHPP benchmark, and a replicable basis for future equal-condition MATLAB/Simulink validation.
Optimalisasi Luberan Sumber Air Melalui Pembangunan Pembangkit Picohydro Menggunakan Axial-Turbine di Desa Ngampungan, Bareng, Jombang Hidayatul Nurohmah; Machrus Ali; Laudhie Primadonni Kusumajaya; Achmad Afandi
Jurnal Pengabdian Masyarakat Universitas Darul Ulum Vol 5 No 1 (2026): DIMAS-UNDAR
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/dimas-undar.v5i1.5103

Abstract

Pandansili Tourism Site in Ngampungan Village, Bareng District, Jombang Regency, is a bathing tourism destination developed by the village-owned enterprise and Tourism Awareness Group since 2019. The situational analysis indicates that the partner requires renewable-energy innovation to reduce operational costs, strengthen educational tourism, and improve management capacity. This community service program utilizes spring-water overflow through a picohydro power plant design using an axial turbine. The technical data refer to the ZD760-LM-(18-20) axial-flow turbine-generator with 220 V AC rated voltage, 2 kW rated power, 1-5 m operating head, 0.02-1.0 m3/s water-flow range, and continuous-duty operation. At a nominal head of 3 m with turbine efficiency of 0.65 and generator efficiency of 0.85, the discharge required to produce 2 kW is approximately 0.123 m3/s. The implementation method consists of partner coordination, discharge and head survey, SWOT analysis, intake-turbine-generator-control-panel design, operation-maintenance training, and energy-utilization evaluation. The SWOT analysis shows an IFE score of 5.56 and an EFE score of 5.01, placing Pandansili development in Quadrant I with an aggressive/offensive strategy. The energy output is directed to tourism-area lighting, renewable-energy educational information boards, simple sensor/monitoring loads, and demonstration loads. The program is expected to improve energy independence, add educational tourism value, and strengthen Pokdarwis competence in managing appropriate technology based on local potential.
Optimasi Thermal Oil Heater Menggunakan PSO Sebagai Tunning PID Controller Enggal Indra Gunawan; Machrus Ali; Hidayatul Nurohmah
Nucleus Journal Vol. 1 No. 2 (2022): November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v1i2.43

Abstract

Optimasi Optimization of the auto temperature control system on the thermal oil heater system using PSO as a PID Controller tunning. Making a PSO-based Simulink tuning PID controller for thermal oil heater temperature in the 2013a Matlab program. Thermal oil heater simulation using PSO as a PID Controller tunning is the best result among other design methods. With kp = 2,057, ki = 1.337, kd = 0.148, we get an overshot value of = 0.002, undershot = 0, at a settling time of 4.521 seconds. This shows that the PID-PSO controller is the best method with the smallest overshot at 0.002, the smallest undershot at 0, and the fastest settling time at 4.521 seconds.
Desain Controller Pada Heating Furnace Berbasis Metode Firefly Algorithm (FA) Febrian Rizal Anas; Dwi Ajiatmo; Hidayatul Nurohmah; Machrus Ali
Nucleus Journal Vol. 1 No. 2 (2022): November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v1i2.1202

Abstract

Furnace is an equipment used to heat or change shape. Process control has become increasingly important in industry, as a consequence of global competition, Year after year, furnaces have improved in both process and industrial equipment. The tuning process ensures that system performance meets operating objectives. Artificial Intelligent (AI)-based intelligent control has developed a lot to improve conventional controls to control voltage loads and is always under constant assessment of the variable. In this research task, it will be discussed about the control of the furnace temperature so that it remains constant with PID and by tuning the Firefly Algorithm (FA) with changes in the output voltage obtained which have better settling time, overshoot and undershoot.
Optimasi Perancangan Sistem Kontrol Mesin CNC Pengebor PCB berbasis Ant Colony Optimization Hidayatul Nurohmah; Elfizar Novrianto; Machrus Ali
Nucleus Journal Vol. 2 No. 2 (2023): November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v2i2.2202

Abstract

A Print Circuit Board (PCB) is a micro (small) sized board that contains various electronic components that are used in an automatic circuit. PCB drilling is usually done manually with human power, which takes a lot of time when there are more and more holes in the PCB. And precision is required when the drill bit touches the PCB board which creates frictional forces and can cause drilling errors. This research uses data collection after carrying out several simulation methods using Matlab 13a. With optimal division methods including without control, Conventional PID, auto PID and PID - ACO. The aim of this research is to determine the advantages of the Ant Colony Optimization (ACO) method in controlling Computer Numerical Control (CNC) machines. The simulation results show that the best optimization method is produced by the PID - Ant Colony Optimization method which produces overshoot: 0.1199, undershoot: 0.0544, and settling time at 2.532 seconds which is the smallest value, while the design without control never reaches stable steady with the largest undershot. : 0.523. so PID - Ant Colony Optimization was chosen as the best method and is suitable for use in controlling PCB Drilling CNC Machines. By applying the PID - Ant Colony Optimization method to the CNC PCB Drilling Machine, it will be able to produce more precise drilling results
AI-Assisted PID Tuning for Voltage Control of an Axial-Flow Pico-Hydro Generator Machrus Ali; Hidayatul Nurohmah; Muhammah Agil Haikal; Yanuar Mahfudz Safarudin
Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v3i2.691

Abstract

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.
RTC-Scheduled ESP32 IoT Prototype for Automated Hydroponic Nutrient Irrigation Hidayatul Nurohmah; Machrus Ali; Ciptian Weried Priananda
Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v3i2.694

Abstract

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.
Optimasi Pembangkitan Ekonomis Berbasis Whale Optimization Algorithm Pada Sistem Multimesin Hidayatul Nurohmah; Arya Sula Cakra Buana; Rukslin Rukslin; Machrus Ali; Muhammad Ruswandi Djalal
Jurnal FORTECH Vol. 6 No. 2 (2025): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6102

Abstract

This study addresses the problem of generation cost optimization for thermal power plants in the Sulbagsel multimachine power system. An advanced swarm intelligence approach, the Whale Optimization Algorithm (WOA), is employed as the primary optimization technique. WOA, inspired by the bubble-net hunting strategy of humpback whales, has emerged as a promising metaheuristic with strong capabilities in exploration and exploitation. The main objective of this study is to minimize thermal generation costs while ensuring effective performance under real system operating conditions. To provide a comparative benchmark, Particle Swarm Optimization (PSO) is also applied to the same problem. Statistical evaluation is conducted to assess convergence behavior, accuracy, and consistency of both methods. The results indicate that WOA demonstrates superior balance between exploration and exploitation, leading to stable convergence and reliable solutions. Under peak daytime load conditions, PSO achieves a cost reduction of 23.02%, whereas the proposed WOA-based method achieves a comparable reduction of 23.78%. Although PSO yields a slightly higher cost saving, WOA demonstrates stronger robustness and statistical reliability across multiple trials. These findings confirm that WOA is a competitive alternative for generation cost optimization in complex multimachine systems, offering significant potential for future applications in economic dispatch problems with larger-scale renewable energy integration.
Co-Authors Abdul Natsir Achmad Afandi Achmad Zaini Agus Raikhani Ahmad Fauzi Ridhwan Andi Imran Arya Sula Cakra Buana Budi Utomo Budiman Choiruddin Ciptian Weried Priananda Dwi Ajiatmo DWI WULANDARI Elfizar Novrianto Enggal Indra Gunawan Febrian Rizal Anas Karim Hanjaya Kholish Fadlili Laudhie Primadonni Kusumajaya Luqman Hakim M Agil Haikal M. Ilham Romli M. Teguh Proyoga Machrus Ali Machrus Ali Mahrus Ali Miftahul Djanah Muhammad Ade Yusuf Alghifrani Muhammad Agil Haikal Muhammad Ruswandi Djalal Muhammad Yusuf Yunus Muhammah Agil Haikal Muhlasin Rukslin Rukslin Rukslin Siti Arifah Venda Kusuma Apsari Wahyu Cahyono Yanuar Mahfudz Safarudin Yoga Arie Pambayun