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Widi Aribowo
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vubeta@unesa.ac.id
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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 95 Documents
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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.
Exact Solitonic Solutions in New Hamiltonian Amplitude Equation using Riccati-Bernoulli Method Jibrin Sale Yusuf
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 3 (2024)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v1i3.35831

Abstract

The propagation of optical pulses in nonlinear media is a complex phenomenon that requires accurate modeling and analysis. The New Hamiltonian Amplitude Equation (HNLS) is a fundamental model that describes this phenomenon, but solving it exactly is a challenging task. We employ the Riccati-Bernoulli Sub ODE method to derive exact soliton solutions to the HNLS. This research contributes to the understanding of optical soliton dynamics in various nonlinear regimes, providing a foundation for the development of novel optical communication systems and devices. We use the Riccati-Bernoulli Sub ODE method to derive exact soliton solutions to the HNLS. The method is applied to various nonlinear regimes, including Kerr law, Quadratic Cubic, and Parabolic law nonlinearities. Additionally, we obtain particular solutions using the power series method. The resulting optical soliton solutions are expressed in terms of various mathematical functions, including trigonometric functions, hyperbolic functions, exponential functions, and rational functions. These solutions describe the oscillatory behavior, exponential growth or decay, rapid growth or decay, and algebraic decay or growth of optical pulses in various nonlinear regimes. The solutions obtained using the power series method provide further insight into the behavior of optical pulses in these regimes. Our results provide a comprehensive understanding of optical soliton dynamics in nonlinear media
Hybrid Deep Learning Approach for DDoS Attack Detection Based on Multidimensional Network Traffic Analysis Hammad, Atheer
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 2 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i2.39992

Abstract

DDoS attacks have become a significant threat to the Internet of Things (IoT) and contemporary network environments due to their large traffic volume, dynamic nature, and class imbalance. Conventional intrusion detection systems may not be able to provide reliable detection in such circumstances. The proposed study is a hybrid deep learning framework that combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to identify DDoS attacks through multidimensional network traffic analysis. The CNN part is employed to derive spatial properties from traffic information, whereas the LSTM part captures temporal relationships among traffic flows. Our experimental analysis of the proposed model used an elaborate experimental setup and conventional performance measures, including accuracy, precision, recall, F1-score, and AUC. The findings of the present research indicate that the hybrid CNNLSTM model outperforms the individual CNN and LSTM models, achieving an accuracy of 99.35% and an AUC of 0.995. The strength of the proposed method in the presence of class imbalance is further confirmed by analysis using ROC and Precision-Recall curves. The results show that the suggested hybrid framework can offer a powerful and viable solution towards DDoS attack identification in IoT and next-generation networks.
Analysis Of The Characteristic Of A Dual Chamber Microbial Fuel Cell Based On Copper Wire Mesh Azzahra, Shavira; Wardhana, Arya Kusuma; Mustika, Soraya Norma; Rizal, Royb Fatkhur
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 2 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i2.44757

Abstract

Sustainable alternative energy solutions are being investigated as a result of the growing demand for energy worldwide and the negative effects of fossil fuels on the environment. A promising method is provided by Microbial Fuel Cell (MFC) devices, which use microbial activity to turn organic materials into electrical power. However, system configuration specifically, the distance between electrodes has a major impact on MFC performance. This study uses wastewater from rice washing as a substrate to examine the effects of different copper plate electrode spacings (1 cm, 3 cm, and 5 cm) on a dual- chamber MFC. By verifying the viability of using household organic waste for the generation of renewable energy and determining the ideal design parameters, this study advances MFC development. Copper plate and copper wire mesh electrodes, separated by a gel membrane, were utilized to create a self-assembled dual-chamber MFC. To assess system performance, measurements of voltage, current, power, and power density were made at various electrode distances and external loads. According to the findings, the maximum power output (207.5 mW), maximum voltage (0.467 V), and ideal power density (0.001395 mW/mg) were all achieved at a distance of 3 cm. Faster voltage stabilization was possible with a 1 cm gap, but efficiency was reduced with a 5 cm distance. At an external resistance of 3 kΩ, the system reached its maximum power.
Soliton Dynamics in Combined KdV-mKdV and KdV-nKdV Models: A Riccati-Bernoulli Sub ODE Approach Sale Yusuf, Jibrin; Sani Muhammad , Umar
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 2 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i2.45053

Abstract

We investigate new soliton solutions of two coupled nonlinear systems: the combined KdV–nKdV and the KdV–mKdV equations. Using the Riccati–Bernoulli Sub-ODE (RBSODE) method with r = 0, the models are reduced to tractable algebraic forms that yield explicit trigonometric, hyperbolic, and exponential-type soliton families. The analytical procedure reveals parameter conditions under which compressive and oscillatory solitons emerge, such as δ/α2(α+δ)>0 for localized bright solitons. A systematic parameter study quantifies how amplitude, width, and velocity vary with the nonlinear coefficients α, δ, p, q. Comparison with existing results (Wazwaz 2017) shows that our solutions recover known families as special cases while extending them to additional parameter regimes. Physical implications are discussed in the context of nonlinear wave propagation in dispersive media, where the balance between quadratic and cubic nonlinearities governs soliton shape and robustness. The results demonstrate that the RBSODE approach provides a flexible symbolic framework for constructing diverse soliton families and analyzing their parameter dependence in coupled nonlinear systems.  
Application of Greedy Algorithm and Simulated Annealing Algorithm on the Asymmetric Capacitated Vehicle Routing Problem Model in Designing Optimal Garbage Transportation Routes Arisha, Bella; Puspita, Fitri Maya; Suprihatin, Bambang; Indrawati
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 2 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i2.45644

Abstract

Waste management remains a recurring issue, particularly in large urban areas. An optimal waste collection route is essential to prevent the problem from becoming more severe and persistent. This study aims to determine the minimum distance and route for waste collection in the Seberang Ulu 1 District, Palembang, using the Greedy and Simulated Annealing algorithms. The calculations were carried out by dividing the district into four work zones. The results show that, using the Greedy algorithm, the minimum distances and routes for work zones 1 through 4 were 24.655 km, 29.7 km, 22.7 km, and 24.705 km, respectively. Meanwhile, using the Simulated Annealing algorithm, the minimum distances and routes for each work zone were 24.325 km, 32.45 km, 22.5 km, and 22.385 km. On average, SA reduces the total distance traveled by 2.1% compared to Greedy, but it requires a longer computation time due to its iterative process of finding the global optimum. These indicate that both algorithms are equally effective in solving the ACVRP problem, with different advantages. SA's advantage in optimizing more complex routes and Greedy's advantage in computation speed for practical implementation. These findings indicate that the Simulated Annealing Algorithm and the Greedy Algorithm almost the same results in solving the Asymmetric Capacitated Vehicle Routing Problem in Seberang Ulu 1 District, Palembang.

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