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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.
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
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.