cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Widi Aribowo
Contact Email
widiaribowo@unesa.ac.id
Phone
+62811307761
Journal Mail Official
vubeta@unesa.ac.id
Editorial Address
Jl. Prof. Moch Yamin, Ketintang, Kec. Gayungan, Surabaya, Jawa Timur 60231
Location
Kota surabaya,
Jawa timur
INDONESIA
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 20 Documents
 1   2 
Search results for , issue "Vol. 2 No. 2 (2025)" : 20 Documents clear
A Modelling and Simulation of Damping Controller In DFIG AND PMSG Integrated With A Convectional Grid: A Review Sabo, Aliyu; Dahiru, Dauda; Noor Izzri, Abdul Wahab
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.v2i2.34749

Abstract

One of nature's most plentiful energy sources is a wind energy conversion system, which also has higher sustainability and no pollution. Damping controllers are designed to enhance hybrid robustness and adaptability when using permanent magnet and double-fed induction synchronous generators. The generators are integrated with convectional sources, which requires careful consideration of grid stability (rotor angle stability), which helps prevent mechanical oscillation and grid disruptions due to the instability. Power system stabilizers with excitation are designed and optimized to assure power system stabilizer settings for ideal damping performance and ignore energy losses; damping controllers are essential.
A review on Energy Consumption Model on Hierarchical clustering techniques for IoT- based multilevel heterogeneous WSNs using Energy Aware Node Selection. Iyobhebhe, Matthew; Tekanyi, Abdooulie Momodou. S.; Abubilal, K. A; Usman, Aliyu. D; Isiaku, Yau; Agbon, E. E; obi, Elvis; Chollom, Botson Ishaya; Ezugwu, Chukwudi; Eleshin, Ridwan. O.; Abdulkareem, H. A.; Ashafa, Fatima; Abubakar, Saba; Umar, Abubakar; Ajayi Ore-Ofe; 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.v2i2.34882

Abstract

This review article scrutinizes the energy consumption model related to hierarchical clustering methods in IoT-based multi-tier heterogeneous networks (WSNs). Since energy efficiency is vital to prolong the operational activities of sensor nodes, this review article concentrated on energy-aware node selection as a significant technique for improving energy consumption. The review article deliberates on the challenges posed by dynamic wireless sensor network conditions, node heterogeneity like energy-based, and scalability challenges that affect energy management. This review article scrutinizes the energy consumption model related to hierarchical clustering methods in IoT-based multi-tier heterogeneous networks (WSNs). Since energy efficiency is vital to prolong the operational activities of sensor nodes, this review article concentrated on energy-aware node selection as a significant technique for improving energy consumption. We scrutinize different factors affecting efficient node selection, comprising residual energy, transmission distance, and sensor node reliability while juxtaposing these techniques with traditional node selection schemes. Furthermore, the importance of developed modeling techniques was highlighted. Finally, future research directions were outlined, by accentuating the incorporation of energy harvesting and collective models to improve the stability and operation of Wireless Sensor Networks. This holistic overview aims to offer appreciated insights for authors and practitioners in WSNs.
Mathematical Modelling of Truck Platoon Formation Based on a Dynamic String Stability Ajayi, Ore-Ofe; Umar, Abubakar; Ibrahim, Ibrahim; Olugbenga, Lawal Abdulwahab; Abiola , Ajikanle Abdulbasit
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.v2i2.34941

Abstract

In this research, the development of a fuzzy logic-based cooperative adaptive cruise control scheme for truck platooning string stability was developed. String stability, which is critical to the operation of truck platooning in the area of enhancing traffic flow and reducing fuel consumption can be affected by unknown uncertainties such as truck incapacitation, delay of platoons and inability to maintain a constant inter-vehicular gap. A commonly reported approach in addressing truck platooning string stability is the Cooperative Adaptive Cruise Control (CACC) scheme. The CACC scheme consists of Adaptive Cruise Control (ACC) and vehicle-to-vehicle (V2V) communication. However, the CACC lacks the requisite flexibility in dealing with unexpected disturbances that can result in the inability to maintain a constant speed and inter-vehicular gap.
Impact of Grid-Scale Solar Photovoltaic Integration on Power System Performance Sunday Ugwuanyi, Nnaemeka; Ugwuoke, Nestor Chima; Obi, Patrick Ifeanyi
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.v2i2.35474

Abstract

The impact of SPV integration on grid performance is a topic of ongoing debate, with conflicting reports on its effects. This study employs modal analysis, Newton-Raphson power flow, and time-domain simulations to assess the effects of SPV integration on voltage profiles, active power loss, and system stability in the IEEE 4-machine and Nigerian 50-bus power systems. The findings reveal that SPV integration impacts power systems differently, emphasizing the need for a comprehensive approach that considers voltage stability, power losses, and stability constraints. While SPV integration can improve voltage levels and reduce power losses, it may also compromise transient stability, highlighting the importance of careful planning and grid reinforcement. For the IEEE 4-machine system, SPV integration is feasible up to 25% based on power loss, but transient stability constraints limit it to 0%. For the Nigerian grid, optimal SPV integration is achieved at 10% based on power loss and voltage profile, while transient stability constraints limit integration to 5%. This study underscores the necessity of a multi-metric approach to defining SPV penetration limits, considering the trade-offs between voltage performance, power loss, and system stability.
Solar-Powered IoT-Based Home Fire Early Warning and Protection System Muhammad Arief Wicaksono; Amirullah, Amirullah; Plangklang, Boonyang
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.v2i2.35773

Abstract

This paper presents the implementation of a prototype of a fire early warning system in a residential house using temperature and smoke sensors supplied by an Internet of Things (IoT) based solar module. The 10 Wp solar module is the energy source connected to a 12V battery via a solar charge controller (SSC). Data retrieval is carried out through testing by the MQ-2 Sensor and LM35 Sensor, respectively, to detect smoke (gas) and heat. The system then activates the buzzer, sends data from the detection of the status and level of smoke (gas) and heat to the smartphone screen and liquid crystal displays (LCD) in the form of an alarm, and orders the PLN switch to work to cut off the electricity. The results of the tool test show that the proposed prototype is able to provide early warning notifications regarding the status and level of smoke (gas) and heat - both from the LCD and remotely from the smartphone, and is able to activate the relay dan order the switch cuts off the electricity to prevent fire. The prototype system's source is supplied by solar modules independently, making it applicable in remote areas with limited electricity access-compared to the previous model which was supplied solely by the electricity grid.
Microbiological and Physiochemical Assessment of Corn Meal (Agidi) Omorodion, Nnenna Jennifer; Victoria OlaIokungbaye , Modebola
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.v2i2.35907

Abstract

Corn meal (Agidi) is a gel-like traditional fermented starchy food item produced from maize, although millet and sorghum can also serve as raw materials. It is known by different names in different localities. A total of 30 corn meal (Agidi) comprising of 15 white and 15 jollof agidi samples were bought from Choba market in Port Harcourt Rivers State were examined and analyzed using standard microbial techniques. The Total Bacteria count for white (plain) Agidi ranged from 6.30 logcfu/g - 8.06 logcfu/g. The Staphylococci count for White Agidi samples ranged from 6.0 logcfu/g – 8.2 logcfu/g. The Coliform count ranged from 6.00- 7.96 cfu/g. The results generated from this study exceeded the acceptable limit for bacteria in food. Bacteria isolated from White agidi includes Staphylococcus spp, (31.58%), Enterococcus sp (21.05%). Bacillus sp, (18.42%), Escherichia coli (15.75%) and Klebsiella sp (10.53%). Pseudomonas sp (2.63%). For jollof agidi the bacterial isolated Staphylococcus spp, (30.8%) Bacillus spp, (24.6%). Enterococcus sp (20.0%), Escherichia coli (12.3%), Klebsiella sp 7(10.8%) and Pseudomonas sp (1.5%). pH of corn meal ranged from 4 – 6, the moisture content ranged from 80% – 90%, while the titratable acidity ranged from ranged from 0.20 – 0.40. Proper handling of agidi during production must be taken. This is to prevent contamination from environmental and human sources. Control measures to prevent cross-contamination of agidi require procedures for maintaining the hygienic quality of the processing environment and equipment. High level of hygiene be maintained in the preparatory processes and production of this cornmeal (Aidi) to enhance health safety.
A Survey On Categorization Of Threat Intelligence And Trust-Based Sharing Strategies On Cyber Attack Tajudeen, Abdulquadri; Nureni, Azeez
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.v2i2.36031

Abstract

Given the development of information technology both at the national and global level, security threats of organizations’ information systems are worth considering. With threats becoming more and more frequent, it’s important to have proper measures to detect, prevent, and counter threats. However, these cyber threats are not a one-time occurrence but are constantly evolving making the stratification and categorization of TI a challenge for organizations in terms of building trust with other counterparts in sharing TI. This research seeks to address these challenges by using survey on TI categorization as well as trust-based sharing mechanisms. The research is an expository research. Specifically, the research adopts a quantitative research methodology with a systematic literature review coupled with case studies to determine the TI classification, methodologies, and effectiveness of TI against cyber security vulnerability. To achieve the above objective, the study integrates the existing literature, industry research, and practical experience hence offering a comprehensive understanding of TI management practices. Findings reveal the types and sources of TI, the classification of Threat Intelligence, and methodologies and practices associated with Threat intelligence. This survey concludes that the role of TI and trust-based sharing mechanisms in fortifying organizational cyber security defenses is important. The survey recommended strategies that organizations could adopt to enhance their resilience against evolving cyber threats
Comparison Feed Forward Back Propagation Networks (FFBPNs) with Support Vector Machine (SVM) for Diagnosis Skin Cancer Based on Images Jawad, Rawaa; Jawad, Raheel
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.v2i2.36117

Abstract

Skin cancer is a type of malignancy responsible for 70 percent of overall skin cancer-related death worldwide. The purpose of the research is to use AI to detect skin cancer of all types more quickly and improve the efficiency of diagnostic radiology.The method used in this paper is an artificial neural network implemented for the detection of skin cancer and the watershed segmentation method for segmentation. The features extracted are shape and Gray-Level Co-Occurrence Matrix. The extracted feature is used for classification. The classifiers are Support Vector Machine and Feedforward Back Propagation applied in a Matlab environment and an image processing technique on a set of photographs that were collected from several websites, including the Kaggle web. The implementation of code for the detection of skin cancer by using data as 100 images 50 no cancer and 50 is cancer, the result shows a successful implementation for the detection of cancer in FFBP classifier a 45 and 2 is bad detection, as well as in SVM classifier 49 with 1 is bad diagnostic. The Conclusion shows SVM classifier provided results for the skin lesions classification produced 98% accuracy and the accuracy of the FFBP of 96 %. The conclusion of this study is helping people with skin cancer undergo a CT scan. The scan is tested using a computer trained to analyze CT scan data.
Early Heart Disease Prediction Using Data Mining Techniques Sylvester Aondonenge, Dugguh; Ore-Ofe, Ajayi; Hassan Taiwo , Kamorudeen; Umar, Abubakar; Abdulrazaq Imam , Isa; Daniel Emmanuel , Dako; Ibrahim , Ibrahim
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.v2i2.36735

Abstract

This study develops a predictive model for early heart disease detection using data mining techniques to enhance timely and accurate diagnosis. Heart disease prediction is complex due to the need to analyze various risk factors, such as age, cholesterol, and blood pressure. The model integrates multiple machines learning algorithms, including Random Forest, Support Vector Machine, and a hybrid ensemble approach, aiming to achieve higher prediction accuracy and reliability. The methodology follows five phases which include data collection, data pre-processing, feature extraction, model construction, and model evaluation. Data was gathered from publicly available health repositories, preprocessed to remove missing values and irrelevant information, and subjected to feature extraction techniques to identify influential predictors. The data was split into an 80:20 ratio for model training and testing to assess model performance across various classification algorithms. The hybrid model achieved an accuracy of 97.56%, precision of 98.04%, and recall of 97.09%, surpassing the individual algorithms tested. These findings indicate that the hybrid approach effectively supports early intervention for heart disease, particularly in healthcare settings with limited diagnostic resources. The study demonstrates that advanced data mining techniques offer a viable solution for improving patient outcomes through early detection of heart disease.
Simulation and Experimental Evaluation of a 5-Level Cascaded H-Bridge Inverter Abdulwahab, Ibrahim; Ismaila, Mahmud; H. Sulaiman, Sulaiman; Abdullahi Shehu, Ibrahim; Mohammed, Musa
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.v2i2.37172

Abstract

Multilevel inverters (MIs) are designed in such a way that different DC sources could be used to achieve the desired output voltage. This includes high quality output voltage, reduction of voltage stress on the switches, low common mode voltages, better harmonic content and reduction in total harmonic distortion compared to the conventional voltage source inverter. As there will be reduction in THD the size of the filter will also get minimized which decreases complexity of the system. Sinusoidal pulse width modulation technique is commonly employed in MIs in order to obtain undistorted output voltage by eliminating lower order harmonics. Cascaded H-bridge MIs are the most preferable for this purpose due to their modularity, reliability, less usage of clamping diodes and ease of control of circuitry and it also reduces the switching and conduction losses of the system. In this study, 5-level cascaded H-bridge inverter was simulated in MATLAB/Simulink software environment. A prototype of the simulated 5-level inverter was also constructed and the result was compared with that obtained from simulation. The results of both the simulation and experimental measurement have the similar output voltage waveform and the THD value of 33.12% and 33% for the simulation and experiment respectively.

Page 1 of 2 | Total Record : 20

 1   2 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 2 No. 3 (2025) Vol. 2 No. 2 (2025) Vol. 2 No. 1 (2025) Vol. 1 No. 3 (2024): (In Progress) Vol. 1 No. 2 (2024) Vol. 1 No. 1 (2024)