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Widi Aribowo
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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 83 Documents
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Effect Of Traditional and Modern Cooking Methods on the Microbial and Physicochemical Quality of Jollof Rice Omorodion, Nnenna Jennifer; Olubukola E, Olanrewaju
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (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.v2i2.36998

Abstract

Jollof rice is a popular West African dish, but its microbiological and physicochemical quality can be compromised by cooking methods. This study investigated the effect of traditional and modern cooking methods on the microbiological and physicochemical quality of Jollof rice sold around University of Port Harcourt. 20 samples of Jollof rice were collected from vendors, cooked using with firewood and gas cooker. Microbiological analysis and physicochemical analysis were conducted using standard methods. Microbiological analysis revealed that firewood cooked Jollof rice had higher total heterotrophic bacteria count (3.7×104 CFU/g to 4.5×104 CFU/g), exceeding stipulated standards. It was also observed that gas cooked Jollof rice had higher fungal count (1.4×103 CFU/g to 8×103 CFU/g) was within stipulated microbiological standard. Firewood-cooked Jollof rice had higher microbial counts compared to gas cooked Jollof rice. Five bacteria species: Bacillus subtilis, (18.75%); Klebsiella sp, (12.5%); Bacillus cereus, (18.75%); Staphylococcus aureus, (43.75%); and Proteus mirabilis, (6.25%) and three fungi species: Aspergillus niger, (57.1%); Fusarium sp, (14.3%) and Penicillum sp, (28.6%) were isolated. Physicochemical analysis showed that firewood cooked Jollof rice had higher values in; Ash, fibre, lipid and moisture content compared to gas-cooked Jollof rice. Gas-cooked Jollof rice had better physicochemical properties, including lower pH and higher protein content. This study concludes that Traditional cooking methods (firewood) may compromise the microbiological and physicochemical quality of Jollof rice, while modern methods (gas) produce safer and more nutritious products. This study highlights the importance of adopting safe cooking practices to ensure food safety and quality.
A Review on Battery Life and Energy Management in HWSNs using Adaptive Energy Harvesting Techniques Iyobhebhe, Matthew; Momodou. S. Tekanyi, Abdoulie; Abubilal, K. A.; D. Usman, Aliyu.; H. A. Abdulkareem; Yau Isiaka; E. E. Agbon; Elvis Obi; Chukwudi Ezugwu; Botson Ishaya Chollom; Ajayi Ore-Ofe; Umar, Abubakar; O. Eleshin, Ridwan.; Ashafa, Fatima; Thomas Muge, Paul
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (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.v2i2.37897

Abstract

This review article scrutinizes the limitations and improvements in battery life and energy management models within HSWNs that employ adaptive energy harvesting techniques. As Wireless Sensor Networks (WSNs) advance into various implementations, including monitoring environmental parameters and smart cities, effective energy management is vital. This review paper examines the responsibility of communication protocols, precisely routing and Medium Access Control (MAC) protocols, in optimizing energy efficiency. We scrutinize existing energy-efficient schemes and their comparative performance, thereby, concentrating on their adaptability to changing energy sources. Examining these protocols, we accentuate the best techniques and potential areas for development. Furthermore, the review highlights the necessity for advanced approaches integrating energy harvesting with resilience communication frameworks to maximize network lifespan. The discoveries are targeted to lead future research and advancement in the field of WSNs, hence, providing more reliable and efficient energy management schemes for WSNs.
Exploring the Impact of AI and IoT on Production Efficiency, Quality Precision, and Environmental Sustainability in Manufacturing M.Mansour, mustafa; lafta, Alaa M.; Salman, Azhar Mansoor; Salman, Haider Sami
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (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.v2i2.38200

Abstract

The findings obtained through these research objectives will pave new agendas towards the medium-range economy renaissance, resilient digital ecosystems, and human-centered integrated intelligence. More in-depth exploration of the goal-specific research objectives awaits the research report. The main research gap and questions – and concomitant research approach, paradigm, and methodologies – framing the subsequent sections of the paper are substantiated by these objectives' delineation from the research questions. Practical implications and directions for prospective areas of techno-social innovation studies building upon the findings are outlined to conclude the paper. The aims, once accomplished, offer a symbiotic relationship with the research questions that catalyze interest in a domain that has hitherto been largely neglected in Industry 4.0 literature. These aims become the guiding lights surmounting the destination of AIoT in being a subversive innovation in developing and deploying discrete, reconfigurable, and near-continuous Industry 4.0 auxiliary open smart manufacturing.
Password Authentication Using Modify Multi-Connect Architecture Associative Memory Hussein, Rusul; Inaam Salman Aboud; Rasha Majid Hassoon
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (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.v2i2.38218

Abstract

Abstract: Password authentication is one of the mechanisms that are widely used to authenticate an authorized user. In this research proposed password authentication for both graphical and textual password by using new technique is Modify Multi-connect architecture (MMCA) algorithm for more efficient in speed and accuracy. Among 100 test the accuracy result is 100% for graphical and textual password to authenticate a user, and the process time to authenticate each user is 0.5 and 1 seconds for textual password and graphical password respectively.
Design Lighting System Based on PID Control and Node-RED Fikrul Ma’arif, Muhammad
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 3 (2024): (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.v1i3.35454

Abstract

In general, lighting systems use the on/off principle, by turning on the lights in a dark room and turning off the lights in a bright room. This has drawbacks in terms of effectiveness, because it does not pay attention to external influences and lighting, namely sunlight. To overcome this problem, automatic light intensity control is needed which still refers to the surrounding lighting. The aim of this research is to understand the performance of light intensity control devices in lighting systems using the PID method. Comparing the measurements of the BH1750 sensor with a lux meter measuring instrument, an average error value of 6.61% was obtained. Searching for PID parameters uses the trial and errors method with 5 attempts on each parameter. In testing each parameter, optimal results were obtained for the PID parameters, namely Kp = 0.10 Ki = 0.18 Kd = 0.10 with a system response value of 7.91, settling time of 14.63 and overshoot of 0.97
Energy Monitoring in Wave Power Plant Based on Node-Red and ESP 8266 Dzakiyya Rosalin, Berliana
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 3 (2024): (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.v1i3.35456

Abstract

Renewable energy in Indonesia includes solar, water or hydro, bioenergy, wind, geothermal, and ocean waves. The large availability of renewable energy, especially ocean waves, is supported by the geographical conditions of Indonesia, which is the largest archipelagic country. Indonesia has 17,499 islands from Sabang to Merauke, while the area of ​​Indonesia is 7.81 km2 and 3.25 million km2 is ocean. This is related to the world's electricity needs which are estimated to reach 1000 EJ (EJ = 1018J) and will continue to increase every day. Depletion of reserves and greenhouse gas emissions do not allow fossil fuel energy to dominate. Therefore, the Node Red and ESP 8266 Based Wave Power Plant is one of the profitable renewable alternative energies on a commercial scale. The design of this prototype uses a pendulum system. The up and down motion of the pendulum will be converted into a rotary motion by the crankshaft and distributed to the pulley and DC generator. Thus, it can distribute electrical energy that is controlled first by the charger controller before entering the battery. Then the INA 219 sensor will detect the amount of voltage and current generated and distributed to the internet (Node Red) via ESP 8266 so that the tool can be monitored remotely.
Design of Bidirectional DC-DC Converter for Photovoltaic Charging System Muhammad Farhan Rizky; Syahril Mubarok, Muhammad; Herlambang Setiadi; Nur Vidia Laksmi B.
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 3 (2024): (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.v1i3.35685

Abstract

This paper proposes a bidirectional DC-DC converter designed for photovoltaic charging systems. The converter aims to efficiently charge batteries while maintaining stable DC voltage and current output. It can convert DC power from solar panels to charge the battery and deliver DC power from the battery to the connected DC bus. The control method for the converter utilizes PI control to achieve a constant output current and voltage. The simulations were conducted using MATLAB/Simulink software, optimizing the converter’s topology, parameters, and controls according to the requirements of the PV charging system. Simulations validated the converter’s performance under various conditions, including input power fluctuations caused by changes in sunlight intensity. The results demonstrate that the bidirectional DC-DC converter effectively operates in charging and discharging modes, maintaining a stable 24V voltage in the DC bus and providing optimal charging performance for the battery.
Assessing the Strategic Impact of Artificial Intelligence - Robotic Process Automation on Enterprise Architecture in the Telecommunications Industry Umar, Abubakar; Abdulrazaq Imam, Isa; Ore-Ofe, Ajayi Ore-Ofe; Daniel Emmanuel, Dako; Sylvester Aondonenge, Dugguh; Abdulwahab Olugbenga , Lawal
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 3 (2024): (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.v1i3.36736

Abstract

This project explores the strategic impact of Artificial Intelligence (AI)-enhanced Robotic Process Automation (RPA) on Enterprise Architecture (EA) within the telecommunications industry. Traditionally, RPA has been applied to automate repetitive tasks without altering underlying IT infrastructure, focusing primarily on operational efficiency. However, the integration of AI introduces cognitive capabilities to RPA, enabling more dynamic interactions within complex organizational systems. This project assesses how AI-driven RPA can influence EA by enhancing system efficiency, supporting business-IT alignment and promoting digital transformation. Through case studies and analyses of various telecommunications operations, the project investigates the dual role of AI-enhanced RPA in both streamlining enterprise-wide processes and maintaining adaptability to meet industry demands. The findings indicate that, while AI-RPA integration holds significant promise for accelerating operational improvements, it also presents unique challenges related to governance, scalability and long-term sustainability. This work contributes insights into the adoption of AI-driven RPA as a transformative tool for telecommunications, offering guidance on best practices for aligning automated systems with enterprise strategic goals.
An emission and weight of vehicles-based road traffic congestion pricing system and control with consideration of investment worthiness Obari, Johnson Adeiza; Tijani A, Salawudeen; Monday A, Idakwo; Busayo H, Adebiyi
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 indicate the qualitative robustness of this approach in handling the inherent nonlinear nature of road pricing problems. Investors and traffic management systems can rely on the simplicity, reduced computation cost, reduced health hazards and the justified investment worthiness on road and toll facilities.
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

The co-digestion of cassava peels (CP) and chicken manure (CM) offers a sustainable approach to biogas production, but optimizing process conditions and kinetic modeling remains crucial for efficiency. This 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 2 L working volume. Results showed that the 1:3 CP:CM ratio produced the highest cumulative biogas yield (0.25 m³) from 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, while Excel Solver provided is a user-friendly tool for nonlinear regression, eliminating the need for specialized statistical software. This study reinforces the potential of kinetic modeling and computational optimization in enhancing AD processes, paving the way for improved waste-to-energy conversion.

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