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Widi Aribowo
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vubeta@unesa.ac.id
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Jl. Prof. Moch Yamin, Ketintang, Kec. Gayungan, Surabaya, Jawa Timur 60231
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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 16 Documents
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Search results for , issue "Vol. 3 No. 1 (2026)" : 16 Documents clear
A Novel Evolutionary-Swarm Hybrid Algorithm for Optimizing Power Transfer Efficiency in Wireless Power Transfer Systems David E. Aku; Idris I. Araga; Isah M. Danjuma; Abel E. Airoboman
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.44795

Abstract

Achieving high stable Power Transfer Efficiency (PTE) in Wireless Power Transfer (WPT) systems remains challenging due to the nonlinear, multimodal nature of the optimization space. Conventional algorithms such as Genetic Algorithms (GA), Differential Evolution (DE), and Simulated Annealing (SA) often face premature convergence, sensitivity to parameter settings, and inconsistent performance across runs. To overcome these issues, this study introduces the Evolutionary-Swarm Hybrid Algorithm (ESHA), which integrates DE for directional exploration, GA crossover for population diversity, SA for adaptive convergence, and Lévy Flights for stochastic global search. ESHA was implemented on a WPT system with a fixed 20 cm transmission distance and compared with GA, DE, and SA using three performance indicators: PTE, convergence speed, and computational efficiency. Results show that ESHA achieved a maximum PTE of 97.18%, surpassing GA (96.81%), DE (96.65%), and SA (96.19%), while maintaining zero variance across independent runs. It converged in an average of 31.2 iterations, slightly faster than GA (33.15) and SA (32.1), and comparable to DE (31.3). Execution time was 0.4738 s, close to GA (0.4654 s) and only marginally higher than DE (0.4262 s) and SA (0.4329 s). Statistical validation confirmed significant improvements in PTE (p < 0.05).
Absorptive Materials -Based Cooling Technologies for Solar Thermal: A Review of Thermal Management Strategies and Performance Enhancements Sajad W. Noori; Duaa Alaa Lafta; Alaa M. Lafta; Mustafa M. Mansour
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.44867

Abstract

The growing need for utility-scale photovoltaic (PV) systems to advance environmental goals has heightened concerns about the costs of scaling and thermal control. Among all the technical problems linked to PV panels, increased temperatures are the key issue, causing reduced efficiency and module damage. When solar energy is not absorbed by the photocells, the PV module's surface temperature can rise much higher, especially in hot climates. This is especially problematic at air temperatures above 50 °C, as traditional natural convection is unable to efficiently cool the PV modules; hence, the Spanish solar PV harnessing system traps 30% of the energy in the PV modules compared to the original efficiency. Moreover, high surface temperature cause material degradation, resulting in earlier thermal failure, replacement, or the expense of disposing of the latter. This is why methods for enhancing thermal management within PV panels are among the most important aspects, and, combined with several technological advances, PV readily available and could potentially reduce the cost of solar energy in the near future.
Stock Price Forecasting Using LSTM with Cross-Validation Rifki Ainul Yaqin; Muhammad Iqbal Anshori; Reddis Angel; Ignatius Wiseto Prasetyo Agung; Toni Arifin; Erfian Junianto
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.45130

Abstract

Stock price forecasting is highly challenging due to the market’s nonlinear, volatile nature, which is influenced by complex economic and behavioral factors. Traditional statistical models and many machine learning approaches often suffer from overfitting and limited generalizability. This study examines the effectiveness of Long Short-Term Memory (LSTM) networks combined with k-Fold Cross-Validation as a lightweight yet robust alternative. Unlike Transformer-based models, which require extensive computational resources,LSTM offers a more resource-efficient solution while effectively capturing temporal dependencies in financial time series. Experiments were conducted on six U.S. stocks (LW, LKQ, IPG, MGM, RL, and CAG) across 1,000 training epochs, using one to two LSTM layers (64–128 hidden units) with the Adam optimizer. Model performance was evaluated using RMSE, MAE, and R² under k-Fold Cross-Validation and compared against Split Validation from prior studies. Results show that k-Fold consistently produced lower error values, confirming its reliability for stable performance estimation. Notably, models using Close-only input achieved lower RMSE and MAE than those with additional indicators (MA200, stochastic), which primarily improved R². This indicates that feature simplicity, combined with robust preprocessing and validation, can outperform more complex inputs in short-term forecasting. In conclusion, integrating LSTM with k-Fold Cross-Validation provides a practical and efficient framework for stock prediction, particularly in resource-constrained settings. However, the findings are limited to specific stocks and indicators. Future work should extend the approach to broader markets, incorporate macroeconomic or sentiment-based features, and explore hybrid architectures to enhance predictive performance further.
The Conceptual Understanding of Metaheuristic Algorithms: A Brief Reviews Widi Aribowo
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.46163

Abstract

Metaheuristic algorithms have garnered significant attention in the field of optimization due to their ability to address complex, nonlinear, and combinatorial problems where conventional exact methods are often impractical. Inspired by natural phenomena, social behaviors, and physical processes, these algorithms provide near-optimal solutions within reasonable computational time by balancing exploration and exploitation. This paper presents a comprehensive review of metaheuristic algorithms, categorizing them into single-solution-based and population-based approaches. It further discusses hybrid and adaptive variants designed to overcome limitations such as premature convergence and parameter sensitivity. The study highlights the advantages, disadvantages, and practical applications of various metaheuristics across diverse domains including engineering, logistics, artificial intelligence, energy systems, and bioinformatics offering researchers a structured guide for selecting appropriate algorithms based on problem characteristics.
Investigating Soliton-Wave Dynamics Using the Focusing Nonlinear Schr¨odinger Equation Jibrin Sale Yusuf
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.43039

Abstract

This research undertakes a comprehensive investigation of the optical soliton solutions of the Focusing Non- linear Schr¨odinger Equation (NLSE), a fundamental model describing the propagation of optical solitons in nonlinear media. We employ two versatile and efficient methods: the Ricatti-Bernoulli Sub Ordinary Differential Equation (RBSODE) method and the Bernoulli Sub Ordinary Differential Equation (BSODE) method. These methods enable us to derive a wide range of optical soliton solutions. We examine two distinct nonlinearities: the Kerr law nonlinearity and the quadratic-cubic nonlinearity. These nonlinearities are crucial in determining the behavior of optical solitons in various nonlinear optical media. Our analysis reveals that the derived soliton solutions exhibit distinct characteristics. Kerr nonlinearity supports sharper, narrower solitons, whereas quadratic-cubic nonlinearity yields broader profiles with enhanced stability. This study obtains soliton solutions of the NLSE with Kerr and QC nonlinearities using the RBSODE and BSODE methods, analyzes the qualitative differences in the obtained profiles, and examines the conservation laws characterizing the dynamics. The RBSODE and BSODE methods are chosen for their algebraic flexibility and their ability to handle the nonlinearODEs derived from the traveling-wave reduction of the NLSE. Furthermore, we use the multiplier method to derive the conservation laws of the NLSE. These conservation laws provide valuable insights into the underlying dynamics of the optical solitons and have significant implications for the design and optimization of nonlinear optical systems. Our research contributes to the understanding of soliton behavior in nonlinear media, with potential applications in optical signal transmission and ultrafast laser propagation.
The Cassava Wastewater Treatment System with and without Recirculation – Challenge and Prospect Eganoosi Atojunere
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.43872

Abstract

The volume of wastewater produced during the secondary processing of cassava into cassava products is significant. This growing concern is not intended to undermine the importance of cassava as a staple food in many countries; instead, it is linked to the way wastewater is handled, which is considered deficient. This review is based on secondary data gathered from over 50 studies published between 2005 and 2025 on different treatment methods for cassava wastewater. It compared the Removal Efficiency (RE) of two existing Cassava Wastewater Treatment Systems: one with Recirculation (CWTS-R) and the other without Recirculation (CWTS-WR). The REs were based on four studied physicochemical parameters: Suspended Solids (SS), COD, turbidity, and cyanide. The trend for the REs was: pH 56 > 33.4; SS 45 > 42.3; COD 47 > 43.2; Turbidity 56 > 25.2; and Cyanide 40 > 38.3 for CWTS-R and CWTS-WR. The data obtained revealed that the REs for the CWTS-R were higher across all studied physiochemical parameters than those for the CWTS-WR. The contaminants removal abilities of the CWTS-R and CWTS-WR were significantly different. The increase in the REs might not be unrelated to the addition of a pump that redirects cassava wastewater back to the starting treatment points when the set threshold limits for these parameters are exceeded. Optimizing the operations of the existing CWTS-R and CWTS-WR is recommended to improve efficiency.

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