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Charis Fathul Hadi
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Prodi Teknik Elektro, Fakultas Teknik , Universitas PGRI Banyuwangi Jl.Ikan Tongkol No. 22 Banyuwangi 68416, Jawa Timur
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Journal Zetroem
Published by Universitas PGRI Banyuwangi
ISSN : 2656081X     EISSN : 2656081X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
jurnal zetroem yang dapat dimuat dalam jurnal ini meliputi bidang keilmuan Teknik Elektronika, Teknik Kendali, Sistem Tenaga, Telekomunikasi, Informatika, Sistem Distribusi. Makalah dapat berupa ringkasan laporan hasil penelitian atau kajian pustaka ilmiah. Makalah yang akan dimuat hendaknya memenuhi format yang telah ditentukan.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 171 Documents
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Virtual Private Network for Data and Information Communication Security:Testing on Zyxel USG 2200 Router Nurwahidah Jamal; Ihsan Ihsan; Kety Lulu Agustin; Andi Yasir Amsal; Farida Farida; Mariatul Kiptiah
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7830

Abstract

This study evaluates the efficacy and security robustness of a Remote Terminal Unit (RTU) data connection protected by a Virtual Private Network (VPN) deployed on the Zyxel USG 2200 router. The aim is to evaluate the effects of IPsec and SSL VPN implementations on network performance, particularly in terms of latency and packet loss, and to assess system resilience against cyberattacks through penetration testing. An experimental methodology was employed, involving the configuration of IPsec/SSL on the Zyxel router and VA modem, conducting packet transmission tests, and performing a security evaluation using Kali Linux tools (Hydra, NMAP, and Metasploit). The results indicate superior network performance, with latency values of 1.8 ms and 5.1 ms, and packet loss rates of 0.14% and 0.81%, signifying that the communication channel is exceptionally reliable and appropriate for real-time RTU applications. Port scanning revealed five open ports (21, 22, 53, 80, 443), but all penetration attempts were futile. Hydra faced failure due to a key-exchange mismatch; NMAP was unable to identify appropriate authentication keys despite numerous attempts, and Metasploit experienced connection issues during exploitation efforts. These findings validate that the established encryption and authentication systems offer sufficient defense against brute-force and fundamental exploitation threats. The research reveals that deploying IPsec and SSL VPN on the Zyxel USG 2200 enhances communication security while maintaining network performance. Future studies should incorporate long-term load testing and more sophisticated, multi-layered attack scenarios to achieve comprehensive security certification.
Chemical Composition Analysis and Heat Absorption Potential of Andesite Stone as Absorber Material in Thermoelectric Generators Septiannissa Azzahra; Samsurizal; Aryana Rachmad Sulistya; Azli bin Yahya
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7998

Abstract

The performance of thermoelectric generators is strongly influenced by heat absorption and thermal management on the hot side because these factors determine the temperature gradient and electrical energy output produced. Conventional ceramic materials commonly used as thermal media generally have high production costs and limited heat absorption capacity creating the need for alternative materials that are natural economical and sustainable. This study investigates andesite stone as a potential natural heat-absorbing material for thermoelectric generators through chemical composition analysis using the X-ray fluorescence method. The results show that the andesite sample is dominated by silica and alumina forming a stable aluminosilicate structure. Other identified compounds include iron oxide calcium oxide and magnesium oxide. Iron oxide contributes to increased radiation heat absorption through higher emissivity while calcium oxide and magnesium oxide improve crystal lattice stability and resistance to thermal shock. The very low loss on ignition value of 0.02% indicates minimal volatile compounds suggesting excellent thermal and chemical stability at high temperatures. Based on the relationship between composition and material properties the studied andesite stone is estimated to have moderate thermal conductivity and effective thermal buffering capability which are beneficial for maintaining a stable temperature gradient in thermoelectric generator systems. Overall these findings indicate that andesite stone has strong potential as a natural heat-absorbing or coating material in thermoelectric generator applications and can become a more economical and environmentally friendly alternative to conventional synthetic ceramic materials for future sustainable energy systems and broader industrial thermal applications worldwide.
Transforming Investment Structures in Capital-Intensive Electricity Utilities: A Managed Service Approach for CapEx-to-OpEx Transformation Ignatius Rendroyoko; Najahul Imtihan; Ishak Sinaga
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8135

Abstract

Electric utilities operate in a capital-intensive environment characterized by substantial infrastructure investment requirements, long asset life cycles, regulated tariffs, and relatively stable financial returns. Increasing electricity demand and energy transition initiatives have intensified the need for alternative financing mechanisms that support infrastructure expansion while maintaining service reliability and affordability. This study evaluates the transformation of conventional Capital Expenditure (CapEx)-based investment structures into Operating Expenditure (OpEx)-based arrangements through managed service models in electricity utilities. Using a mixed-method explanatory case study and techno-economic analysis, the study examines managed service implementation for 160 kVA distribution transformers in Indonesia's electricity distribution sector. The analysis incorporates lifecycle cost evaluation, cash flow assessment, and financial indicators including Net Present Value (NPV) and Internal Rate of Return (IRR). The results show that the managed service model improves financial flexibility by replacing large upfront investments with predictable periodic payments and transferring operational risks to service providers. However, this flexibility is accompanied by an approximately 15% increase in lifecycle NPV compared with the conventional Total Expenditure (TOTEX) model. These findings demonstrate that managed services represent a viable alternative financing strategy for capital-intensive electricity utilities facing investment constraints
Analysis of Overloading Impact on Harmonic Content and Loss of Life in Distribution Transformers Kartika Tresya M; Alex Fernandes; Welly Okke; Nurmiati Pasra⁠; Samsurizal; Tony Koerniawan
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8136

Abstract

In the wake of Indonesia’s accelerating power infrastructure growth, maintaining distribution system integrity is essential to meet the increasing electricity demand from both residential and industrial sectors. This study investigates the operational performance of the PGCE distribution transformer at the Lemah Abang Customer Service Unit (ULP), which experienced severe overloading with a peak loading of 113.82%, exceeding the maximum allowable loading limit of 80% specified in SE No. 0017.E/DIR/2014. The overload condition resulted in excessive thermal stress and a 17% voltage drop, exceeding the permissible service voltage variation specified in SPLN 1:1995. To address these problems, a load-splitting strategy was implemented through the installation of an SNTR insertion transformer. A comparative quantitative (before–after) analysis was conducted using field measurement data to evaluate transformer loading, voltage drop, and transformer loss of life before and after the technical intervention. The results show that the loading of the PGCE distribution transformer was reduced to approximately 76–77%, restoring its operation to within the recommended loading limit. In addition, the voltage drop decreased from 17% to 4.5%, satisfying the service voltage requirement of +5% to −10%. The reduction in transformer loading also lowered thermal stress on the winding insulation, thereby reducing the transformer loss of life and improving asset reliability. These findings demonstrate that load splitting combined with the installation of an insertion transformer is an effective engineering solution for mitigating transformer overloading, improving voltage quality, and extending transformer service life. 
Design, Construction, and Performance Analysis of a Portable Solar Panel for Efficient Smartphone Charging Tri Joko; Erlina; Doni Pratama
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8137

Abstract

This study aims to design, construct, and analyze the performance and efficiency of a portable solar panel system specifically developed for smartphone battery charging as an environmentally friendly alternative energy solution. With the increasing reliance on portable electronic devices and the urgent need to reduce fossil fuel dependency, a highly mobile and efficient charging system is required for outdoor or off-grid situations. The research utilizes a quantitative experimental method, employing a 20 Watt-Peak monocrystalline solar panel, a 12V 7Ah storage battery, a Solar Charge Controller (SCC) to regulate energy flow safely, and a buck converter to adjust the output voltage for smartphones. The portable system was integrated into a compact suitcase design for high mobility. Performance testing was conducted over seven consecutive days from 08:00 to 16:00, measuring voltage, current, power output, charging time, and overall system efficiency. The results indicate that the solar panel's output power is highly dependent on sunlight intensity, reaching its maximum peak of up to 15.40 W at midday while maintaining a relatively stable voltage range. The system demonstrated the capability to gradually and safely charge a smartphone battery up to 80% capacity. The highest overall system charging efficiency recorded during the testing period was 55.5%. In conclusion, the designed 20 WP portable solar panel system exhibits stable performance and adequate efficiency, making it a highly practical, reliable, and sustainable off-grid power source for charging portable electronic devices.
Image-Based Spatial Shading Analysis for Power Performance Degradation in Photovoltaic Systems Andi Makkulau; Ramlah; Alex Fernandes; Syaripudin Ardiansyah
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8306

Abstract

Partial shading is one of the dominant causes of energy performance degradation in static photovoltaic (PV) systems, especially in tropical environments where dust accumulation and vegetation growth frequently occur. Conventional shading analysis in photovoltaic energy studies is commonly conducted using geometric simulation or irradiance‑based modelling without explicitly identifying physical shading objects on the PV surface. This paper proposes a computer vision‑based approach to quantitatively detect shading objects and statistically evaluate their impact on PV energy performance. A Python–OpenCV framework was developed to calculate pixel‑based shading area on a 10 Wp static PV module. Electrical parameters including voltage, current, and output power were experimentally measured under shading levels ranging from 10% to 100%. Statistical analyses consisting of Pearson correlation, linear regression, significance testing, and one‑way Analysis of Variance (ANOVA) were applied. The results show a very strong negative correlation between shading area and both current and power output (r = −0.98, p < 0.001). Linear regression indicates that shading area explains 96.1% of current variation (R² = 0.961), while ANOVA confirms statistically significant differences in energy output across shading levels (p < 0.01). These findings demonstrate that computer vision‑based shading quantification provides a statistically robust and energy‑oriented framework for analysing performance degradation in static photovoltaic systems.
Study of Smart Microgrid Technology on a Laboratory Scale Grid System Heri Suyanto; Erlina
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8309

Abstract

The utilization of renewable energy sources to meet electricity demand has become increasingly important. However, comparative studies on the technical and economic performance of on-grid and off-grid smart microgrid systems remain limited. This study aims to evaluate the configuration and performance of a smart microgrid system by comparing different operating configurations using HOMER software. The system was modeled by defining the electrical load, simulating the proposed configurations, and evaluating their technical and economic performance based on power output, Net Present Cost (NPC), and Cost of Energy (COE). The results show that the proposed grid-connected smart microgrid provides the best overall performance, with approximately 80% of the electrical energy demand supplied by the photovoltaic (PV) system and the remaining 20% provided by the PLN grid, demonstrating effective utilization of renewable energy resources. Economically, the proposed system achieves an NPC of Rp. 828,391,700 and a COE of Rp. 419.28, which are lower than those of the off-grid configuration (NPC of Rp. 2,664,679,000 and COE of Rp. 3,151.07) and the grid-only configuration (NPC of Rp. 906,104,800 and COE of Rp. 1,071.00). These findings indicate that integrating photovoltaic generation with the utility grid offers a more cost-effective and reliable solution while significantly increasing the contribution of renewable energy to the electricity supply. Therefore, the proposed smart microgrid configuration can serve as a practical reference for the design and economic evaluation of future grid-connected renewable energy systems.
Real-Time Vehicle Detection and Counting Using YOLOv8 and ByteTrack Multi-Object Tracking on Surveillance Cameras Filantropi Yusuf Aji Cahyono; Raden Arief Setiawan; Angger Abdul Razak
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8313

Abstract

Vehicle counting in tourist area parking facilities is typically performed manually, leading to counting errors and the inability to provide real-time capacity updates. This study proposes an automated real-time vehicle detection and counting system integrating YOLOv8s as the object detector and ByteTrack as the Multi-Object Tracking algorithm on surveillance camera footage to support parking capacity management. The dataset consists of 1,377 images across two vehicle classes, cars and motorcycles, prepared through a data-leakage-free pipeline with a 70/20/10 training-validation-test split followed by horizontal flip augmentation applied exclusively to the training subset. The model was trained for 50 epochs on an NVIDIA GeForce RTX 4050 GPU. A virtual counting line positioned at 70% of the frame height, combined with ByteTrack's persistent unique ID mechanism, enables precise vehicle entry and exit counting while preventing double counting. Evaluation results show that the YOLOv8s model achieved precision of 0.904, recall of 0.961, F1-score of 0.930, and mAP@0.5 of 0.969. Vehicle counting evaluation over a 30-minute test video yielded a counting accuracy of 96.875%, MAE of 2.25, and MAPE of 3.125%. The system operated at an average processing speed of 37.82 FPS, exceeding the real-time threshold of 25–30 FPS. These results indicate that the proposed system has the potential to serve as an alternative solution for automated parking capacity management at tourist area facilities.
Analysis of the Achievement of Indonesia's Nationally Determined Contribution Target in 2030 Musa Partahi Marbun; Dandi Jiwo Lazuardi
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8372

Abstract

Global climate diplomacy through the Paris Agreement obligates every member state to update their greenhouse gas (GHG) emission reduction commitments through the Nationally Determined Contribution (NDC) document. As a form of national implementation, the Government of Indonesia sets an emission reduction target in 2030 of 31.89% for the CM1 or unconditional scenario in the Enhanced NDC (ENDC) document. Furthermore, PT PLN (Persero) is mandated to contribute directly to GHG emission reductions by 127 Million Tons of CO2 in 2030 based on the unconditional scenario (CM1). However, along with the progress of GHG emission reduction achievements which have dynamics, there is a potential gap in achieving the GHG emission reduction target. Thus, an analysis of the fulfillment of the GHG emission reduction target by PT PLN (Persero) in 2030 is needed, as well as mapping the achievement prognosis and the challenges per mitigation activity. The use of a descriptive-analytical method based on literature study and review of regulatory documents of the Government of Indonesia and PT PLN (Persero), as well as emission reduction calculations, is carried out based on mathematical formulas that refer to the BAU scenario calculation in the ENDC. The analysis is focused on the comparison of three main data trends: the initial target of the ENDC document for the 2021–2030 period, the historical realization of emission reductions for the 2021–2025 period, and the prognosis of emission reductions for the 2026–2030 period across four main activities of PLN.
Comparing Machine Learning and Neuro-Fuzzy Models for Hydropower Prediction Under Seasonal Operating Conditions Daniel Rohi; Akhmad Solikin
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.8441

Abstract

Accurate prediction of hydropower energy production is essential for operational planning and decision-making under varying hydrological conditions. However, comparative evaluations of high-accuracy data-driven models and interpretable intelligent models using real operational data remain limited. This study aims to compare the performance of Machine Learning and Neuro-Fuzzy approaches for predicting energy production at the Sengguruh Hydropower Plant, Indonesia. One year of engineering-validated operational data consisting of discharge, reservoir and tailrace water levels, operation time, turbine efficiency, and derived hydraulic head were used for model development and evaluation. Three Machine Learning models, namely Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Regression (SVR), were compared with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Model performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination (R²). The results indicate that Machine Learning models achieved superior predictive performance, with Random Forest providing the highest accuracy (RMSE = 8.42 MWh/day, MAE = 6.35 MWh/day, and R² = 0.982). In contrast, the ANFIS model produced lower prediction accuracy but offered a more interpretable representation of hydropower operating behavior. Correlation analysis further indicates that operation time and inflow discharge are the most influential operational variables associated with energy production. The findings demonstrate that Machine Learning approaches are more suitable for high-accuracy forecasting and operational optimization, whereas Neuro-Fuzzy models provide advantages in interpretability and operational representation. These results contribute to the development of intelligent hydropower forecasting systems that balance predictive performance and engineering understanding.

Page 17 of 18 | Total Record : 171

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