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Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Published by Universitas Negeri Surabaya
ISSN : -     EISSN : 30640768     DOI : https://doi.org/10.26740/vubeta.v1i1
Core Subject : Science, Engineering,
Computer Science & IT Engineering Mechanical Engineering Transportation
Vokasi Unesa Bulletin Of Engineering, Technology and Applied Science is a peer-reviewed, Quarterly International Journal, that publishes high-quality theoretical and experimental papers of permanent interest, that have not previously been published in a journal, in the field of engineering, technology, and applied sciences that aim to promote the theory and practice of Engineering, Technology And Applied Science.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 21 Documents
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Search results for , issue "Vol. 2 No. 3 (2025)" : 21 Documents clear
An Emission and Weight-based Road Traffic Congestion Pricing System and Control with Consideration of Investment Worthiness Obari A. Johnson; Salawudeen T. Ahmed; Idakwo A. Monday; Adebiyi H. Busayo
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.38528

Abstract

This work presents a knowledge-based approach to traffic congestion pricing system and control. The road traffic congestion has attracted different intelligent contributions which have addressed many real-time traffic scenarios at a toll point unlike the flat toll system that renders parallel toll for every traffic condition. However, existing works on dynamic traffic congestion pricing systems focus entirely on the traffic parameters without taking cognizance of the impacts of the weight of vehicles on the road. More so, despite the numerous health hazards associated with air pollution from vehicle exhaust during traffic peak hour, effects of emission have not been conceived as pivotal input to be circumvented in road toll design. Therefore, a fuzzy logic-based approach to dynamic traffic congestion pricing problems in a 1*2 traffic scenario comprising of a fast lane and a slow lane, is presented. The inputs to the fuzzy inference system are the weights of vehicles, the rate of carbon dioxide emission, and the traffic density on the toll lane; while the output is the congestion price. Simulations results on the MATLAB fuzzy logic toolbox for a case of Lekki Admiralty Toll Gate reveal that a traffic scenario with traffic density of 57.2 V/mile, carbon dioxide emission rate of 339 Kg/m and weight of approaching vehicle of 8860 Kg, the congestion price gives N1130; this value of congestion price for this example scenario indicates an approximate value of 70% return on investment (RoI) when compared to the flat toll.
Excel Solver Aided Biogas Kinetics Computation for Varied Ratio Co-digestion of Cassava Peels with Chicken Manure Luka, Yusufu; Saddiq, Hassan Ahmed; Abubakar, Abdulhalim Musa; Naandeti, Nathan Akucha
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.38630

Abstract

Existing biogas kinetic models require computational expertise. This study presents an Excel Solver-based approach to improve accessibility and accuracy. The co-digestion of cassava peels (CP) and chicken manure (CM) represents a sustainable approach to biogas production; however, optimizing process conditions and kinetic modeling remain crucial for efficiency. The study employed Excel Solver to estimate kinetic parameters in the modified Gompertz and Cone models for three different CP:CM ratios (1:1, 1:3, and 3:1) under mesophilic conditions (ambient temperature) and a retention time of 40 days. Anaerobic digestion (AD) was conducted in 4-L batch digesters with a working volume of 2 L. Results showed that the 1:3 CP:CM ratio produced the highest cumulative biogas yield (0.25 m³) from the experiment, outperforming the other ratios (1:1 = 0.2384 m³ & 3:1 = 0.1576 m³). At the optimal ratio, the modified-Gompertz model exhibited a superior fit (R² = 0.9684) compared to the Cone model (R² = 0.7586), with lower SSE values (2.157 vs. 16.503, respectively), confirming its reliability in capturing microbial adaptation and substrate degradation dynamics. The estimated parameters—biogas production potential (BP = 0.2076 m³), maximum production rate (k = 0.0226 m³/day), and lag phase (λ = 3.4 days)—highlighted the significance of nitrogen balance in optimizing biogas yield. The kinetic study is essential for predicting biogas production trends, optimizing digester performance, and designing efficient biogas systems. The Excel Solver, provided, is a user-friendly tool for nonlinear regression, eliminating the need for specialized statistical software.
Revisiting Parasitic Computing: Ethical and Technical Dimensions in Resource Optimization Godfrey Oise; Clement Nwabuokei; Richard Igbunu; Prosper Ejenarhome
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.38786

Abstract

Parasitic computing is a provocative concept enabling one system to offload computational tasks to remote hosts without explicit consent by exploiting communication protocols such as TCP/IP. While initially demonstrated as a conceptual hack, its implications for distributed computing, ethics, and resource optimization remain underexplored in modern contexts. This study revisits the original parasitic computing model, focusing on operational feasibility, technical efficiency, and ethical boundaries. We implement a Python-based simulation that encodes logical operations (AND, OR) into TCP packets by manipulating checksum fields—a core mechanism of the parasitic approach. We conducted over 6,000 packet transmissions across various network latency conditions using loopback and LAN environments to measure success rates, response times, and failure thresholds. Results show that logical operations can succeed under low-latency conditions with over 94% accuracy, but performance degrades sharply under higher round-trip times, dropping below 70%. These findings suggest parasitic computing may be technically viable within tightly controlled environments but face significant limitations in broader network applications. The researchers critically examine ethical considerations, emphasizing the risks of unauthorized computation, resource exploitation, and potential security breaches. This study contributes a reproducible methodology and empirical data, offering a renewed perspective on parasitic computing’s technical boundaries and future potential. It further calls for responsible experimentation and proposes hybrid models combining parasitic techniques with legitimate distributed computing frameworks and new safeguards to detect and mitigate unintended abuses. The paper proposes directions for improving protocol resilience and computational fairness in open networks.
Optimal Placement of Phasor Measurement Units on Shiroro 330kv Grid Network Using Binary Grey Wolf Optimization Algorithm Kabiru Abubakar Tureta; Sabo Aliyu; Yakubu Abdulrazak
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.38936

Abstract

Phasor Measurement Units (PMUs) are crucial for improving the control, monitoring, and observability of modern power systems. This research presents an optimal PMU placement strategy for the Shiroro 330 kV grid network using the Binary Grey Wolf Optimization (BGWO) algorithm. The objective is to minimize the number of PMUs required while ensuring full system observability under both normal and contingency conditions. The BGWO algorithm, inspired by the hunting behavior of grey wolves, is a powerful metaheuristic for solving binary optimization problems. Applied to the Shiroro grid, this method demonstrates enhanced observability and systemreliability. Compared to other optimization techniques, BGWO achieves higher accuracy and reduced computational time. The simulation results validate the effectiveness of the proposed approach in achieving cost-effective and reliable PMU deployment for the 330 kV network.
Design of an Enterprise Network Terminal Security Solution Muhammad Idris Abubakar; Ajayi Ore-Ofe; Abubakar Umar; Ibrahim Ibrahim; Lawal Abdulwahab Olugbenga; Ajikanle Abdulbasit Abiola
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39105

Abstract

This paper presents a secure enterprise network terminal security solution designed to protect the confidentiality, integrity, and availability of critical data and network resources. It presents a logical approach to creating an enterprise network security architecture with a primary focus on optimizing and enhancing the performance of as data center servers and storage. Traditionally, network infrastructure has primarily focused security measures on core components, such as firewalls and intrusion detection/prevention systems (IDS/IPS). However, the exponential growth of Internet of Things (IoT) devices, Bring Your Device (BYOD) policies, and remote workforce trends has shifted the threat landscape, making network terminals key vectors for malicious access, with critical end devices often being the ultimate targets. This study presents a comprehensive framework that prioritizes terminal-level security by integrating existing encryption techniques, specifically a double layer VPN tunnel architecture, to enhance data transmission confidentiality. A significant contribution of the paper lies in its structured classification of network terminals into thoughtful, intelligent, and dumb categories based on capability and memory—an approach that supports tailored securityimplementations. The framework also outlines contingency measures for securing data center endpoints in the event of a breach scenario. The novelty of this work lies in its focused protection strategy for terminals within enterprise environments, bridging the security gap between endpoints and core infrastructure. The proposed solution demonstrates the potential to reduce exposure to ransomware and targeted attacks through layered defenses and a proactive disaster recovery and business continuity (DR&B) strategy, despite limitations in real-world simulation due to resource constraints.
Spatial Pattern and Distribution of Adansonia Species in the Sahel Savanna Ecosystem of Yobe State, Nigeria Ishaya Yahaya Kuku; Edicha Jibril Abdullahi; Bitrus Eniyekenimi Daukere; Jedidiah Precious Oru-Bo
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39262

Abstract

Adansonia species, particularly baobab, are ecologically and socioeconomically significant in the Sahel Savanna, yet their spatialdistribution patterns remain underexplored in Nigeria. This study employed a reconnaissance survey to delineate the study area and inform the establishment of purposively selected quadrats ranging from 100 x 100 m to 500 x 500 m, based on local Adansonia density and distribution. All individual trees were identified and measured for structural attributes, with their geographic coordinates collected using calibrated GPS devices and validated through multiple readings and inter-observer checks. Nearest Neighbour Analysis (NNA) in ArcGIS 10.8 was used to analyze the spatial patterns by comparing observed mean distances to expected values under random distribution. Results revealed that Adansonia species, predominantly A. digitata and A. kilima, exhibited a dispersed distribution pattern across 19 of 20 quadrats, with only one quadrat showing randomness. This pattern suggests influences from resource competition, seed dispersal strategies, environmental heterogeneity, and human management. The study provides critical insights for conservation planning and sustainable management of baobab in arid environments.
A Novel Modified Tornado Optimizer with Coriolis Force Based on Levy Flight to Optimize Proportional Integral Derivative Parameters of DC Motor Diego Oliva; Farhad Soleimanian Gharehchopogh; Vugar Hacimahmud Abdullayev; Widi aribowo; Asmunin Asmunin; Andi Iwan Nurhidayat
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39269

Abstract

One kind of electric motor that runs on direct current (DC) is called a DC (Direct Current) motor.  This motor uses the interaction of electric current and magnetic fields to transform electrical energy into mechanical energy, or motion.  Applications requiring exact speed and torque control frequently use DC motors.  By minimizing errors (differences between setpoints and actual values), proportional-integral-derivative (PID) control is a control technique used to govern dynamic systems to reach desired conditions (setpoints).  PID creates an ideal control signal by combining three elements. The Modified Tornado optimizer-based Coriolis force (TOC) method for DC motor control is presented in this article.   The paradigm for the TOC approach is the Tornado Optimizer-Based Coriolis Force Algorithm, a metaheuristic that leverages tornado dynamics and the effect of the Coriolis force to address difficult optimization problems.   According to this study, the TOC method can be improved by implementing the Levy Flight methodology.   According to the results of tests employing optimal functions, the LTOC technique may broaden exploration and exploitation.   Meanwhile, when the LTOC technique is applied as a DC motor controller, the optimal overshoot response value is achieved. The LTOC approach outperforms the TOC method by 0.014% and 0.037%, respectively, in terms of ITSE and ITAE values.
The Reconfiguration of Kaduna Municipal Area Distribution Network for Power Loss Reduction and Voltage Profile Improvement Using Static Var Compensators (SVC) Abel Ehinem Airoboman; Bukar Alhaji Bukar; I.A Araga
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39272

Abstract

The increase in global and Nigerian demand for electricity due to technological advancements has brought about numerous challenges, including voltage instability, power factor problems, and high-power losses in electrical power distribution networks. This paper presents the placement of a Static Var Compensator (SVC) in the power distribution network of Town One Station, Kaduna, Nigeria, to investigate its impact on improving and addressing the network’s poor voltage profile and reducing the active powerloss experienced by the network. For analysis, the bus voltage, power, and the current passing through the chosen feeders were measured and noted appropriately. The network parameters, including route length, transformer parameters, and maximum power flow, were obtained from the Kaduna Electricity Distribution Company in Kaduna, Nigeria. The distribution network was modelled and simulated in the ETAP software environment, both with and without Static Var Compensator (SVCs). The results obtained fromthe simulation indicated that buses 5, 7, 8, and 47, among others, have a voltage magnitude of 0.743– 0.932 pu, which is clearly outside the acceptable limit of 0.95– 1.05 pu. Further results showed that the network experienced real and reactive power losses of 8,527 kW and 23,535 kVAr, respectively. After the placement of the SVC with a 5.75MVAR rating, the active power loss decreased from 8527 kW to 6751 kW, indicating a 20.82% reduction in total active power loss experienced by the network. Additionally, the minimum network’s bus voltage improved from 0.743 to 1.02 p.u. 
Internet of Things (IoT) based Electrical Power Monitoring System for Solar Power Plants using the Telegram Application Rezi Delfianti; Venny Aminda Tazayul; Bima Mustaqim; Fauzan Nusyura; Catur Harsito
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39405

Abstract

Indonesia, with its tropical climate, possesses substantial solar energy potential. However, traditional monitoring of solar power systems in Indonesia still relies on manual observation, making the process inefficient, time-consuming, and prone to error. To address these limitations, this study proposes the design and implementation of a real-time Internet of Things (IoT)-based monitoring system for solar power plants using the Telegram application as the user interface. The system integrates the ESP32 microcontroller and the Pzem-004 T sensor to measure AC electrical parameters, including voltage, current, power, energy, frequency, and powerfactor. Unlike previous studies that used platforms such as Blynk or ThingSpeak, this research introduces Telegram as an innovative messagingbased monitoring platform, offering greater accessibility, simplicity, and user familiarity. The monitoring system was tested on a single-phase off-grid solar power setup, utilizing five types of household electrical loads, to validate its accuracy and reliability. The ESP32 communicates with the Telegram bot through Wi-Fi, and users can retrieve real-time data via predefined commands. Experimental results demonstrate high measurement accuracy, with average errors of 0.07% for voltage, 0.1% for current, and 0.08% for power. These results confirm that the system provides reliable data transmission and sensor readings. This work contributes a low-cost, efficient, and user-friendly alternative to conventional monitoring systems, particularly for decentralized renewable energy systems in remote or off-grid areas. The integration of Telegram as a communication medium for energy monitoring adds a novel dimension to IoT-based power system applications.
Enhancing Indoor Positioning Accuracy with Ant Colony Optimization and Dual Clustering Oise Godfrey Perfectson; Nwabuokei Onyemaechi Clement; Ozobialu Chukwuma Emmanuel; Ejenarhome Otega Prosper; Atake Onoriode Michael; Unuigbokhai Nkem Belinda; Akilo Babalola Eyitemi
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39452

Abstract

Indoor positioning systems are crucial for public safety, healthcare, and IoT, but Wi-Fi fingerprinting faces challenges such as signal interference, multipath effects, and high computational costs. These issues reduce positioning accuracy and make real-time localization difficult.This paper introduces an Ant Colony Optimization (ACO)-based dual clustering method to enhance Wi-Fi fingerprinting accuracy and efficiency. ACO performs coarse clustering by optimizing initial data groupings, while K-means refines clusters for improved precision. The Weighted K-Nearest Neighbor (WKNN) algorithm is then applied for real-time positioning by selecting the most similar signal sub-bases.Experiments show that the proposed method achieves 100% accuracy in building classification and 91% accuracy in floor classification. For latitude and longitude prediction, Random Forest and SVC outperform XGBoost, achieving MSE values of 0.0048 (latitude) and 0.0055 (longitude). The approach also reduces computational overhead by 93.51%, improving efficiency.The study presents a robust, scalable solution for indoor positioning and introduces the Dual Clustering Wi-Fi Localization Dataset (DCWiLD) for future research. Future work will focus on dataset balancing, BLE/UWB integration, and energy optimization for IoT applications.

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