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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 95 Documents
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Telegram Application to Monitor and Control of Automatic Railway Crossing Prototype Using Automatic Transfer Switch Wusandi Janu Ramadhan; Amirullah Amirullah; Asepta Surya Wardhana
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35391

Abstract

A railroad crossing is a device that functions to close and open roads that limit or stop public traffic lanes so that vehicles stop temporarily and give priority to trains. Failure of a railroad crossing will have fatal consequences because it will cause accidents and cause fatalities, injuries, or other material losses. The accident occurred because there was no equipment or failure of officers when operating the railroad crossing. To overcome these obstacles, the railroad crossing was made automatically. This paper proposes a prototype control of an automatic railroad crossing using an automatic transfer switch (ATS) monitored by the Telegram application. The main power source of the railroad crossing prototype is a photovoltaic generator system consisting of solar modules, inverters, and batteries. ATS is proposed so that the system is able to automatically transfer the power supply from the solar power generator to PLN electricity if the battery voltage is not enough to drive the railroad crossing or vice versa. The results of the study show that the combination of a 50 Wp solar module and a VRLA battery (12V and 12Ah) is able to store and generate electricity to drive the railroad crossing. The INA219 sensor is able to measure the current, voltage, and power of the PV module and battery. Arduino Uno is able to process voltage and current sensor data, send and receive UART data (RX TX), and communicate with ESP8266. Data from ESP8266 can then be sent and monitored remotely by the Telegram application via Arduino-Uno. The results of DC current and DC voltage tests using the INA219 sensor between the Telegram application and Multimeter are able to produce errors below 5%. The Telegram application is also able to monitor the DC voltage and DC current of PV modules and batteries, as well as the DC adapter voltage and DC adapter current from PLN remotely, and the status of opening and closing the railway crossing gate based on the power supply selection by ATS.
Monitoring of Public Street Lighting Equipment Using Passive Infrared Receiver (PIR) Sensors and Node-red Ismail Faruqi , Muhammad; Herjuno, Dimas
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35411

Abstract

The current public street lighting system (PJU) still uses manual panel control. With these problems to find out the condition of the lights from the public street lighting (PJU) is running well or not and to find out whether the lights are on or off. From this statement, the purpose of this study is to determine 1) the sensitivity distance of the PIR (Passive Infrared Receiver) sensor with Movement on a microcontroller-based PJU to save electrical energy. 2) comparison of Current When measured using an ampere clamp and Node-red. The method used is experimental, namely Referring to two sets of variables. The first set functions as a constant. The results of the study show that 1) Based on the test results, it was found that the PIR sensor works when the human object is at a distance of 1 to 8 meters and can be detected objects in bright or dark conditions. 2) Based on the test results, it was found that the PZEM-004T sensor When given a load, the greater the current load given to the device, the current value read on the Node-red.
Current and Voltage Monitoring in Wind Power Plants Using ESP8266 and Node-Red Rozihan Arief; Mohamad Irfan Faudi Maulana
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35429

Abstract

Fossil energy which is the main energy producer can be converted by utilizing wind power as an alternative renewable energy. The tool used as a wind power converter is a wind turbine, where wind power is kinetic energy that is converted into mechanical energy which is used to produce alternative energy is electrical energy. The working principle of this generator comes from the kinetic energy of the wind that rotates the propeller or windmill, then this mechanical energy runs the generator to create electrical energy. The design is carried out to find out and understand about operating Wind Power Plant Monitoring using Node-Red-based ESP8266 which is integrated with a smartphone or PC as a monitor for the tool. The design of the Wind Power Plant voltage and current monitor uses the ESP8266 microcontroller and the programmer uses the Arduino IDE software which will be applied to Node Red to create a display on the smartphone or PC screen. This study aims to produce a wind turbine prototype using the Savonius wind turbine model and monitor the output of the wind power plant using the ESP8266 which is displayed using the Node-Red dashboard.
Portable Pico Hydro Power Plant for Power Station Charger Muhammad Taufiqurrohman; Dita Octaviani
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35597

Abstract

The increasing need for energy will cause the depletion of energy reserves on earth and require energy reserves that can be renewed. Water flowing energy is the right choice to replace it by using it to generate electricity. And electrical energy can be stored in batteries that can be used at any time. In this study, converting the energy of the water into electricity is stored in batteries in the form of portable generators that can be taken anywhere. By requiring a component such as a turbine, generator, charger controller, auto buck bost converter, battery and other supporting components that are assembled into one in a portable form. With out a 12V battery that can increase and decrease the voltage as a charger for cellphones, laptops and other electronic equipment. By taking the results obtained, do a comparison by comparing the difference in the discharge of flowing water with the charging time on the power charger. The results obtained were river discharge 73.621 l/s charging time 42 hours, river discharge 73.621 l/s charging time 42 hours, pipe discharge 6.41 l/s charging time 84 hours, pipe discharge 8.064 l/s pipe charging time 38 hours, pipe discharge 9.868 l/s charging time 32 hours, pipe discharge 14.42 l/s pipe 27 hour. The greater the discharge,the faster the charging of the battery.
Internet of Educational Things (IoET): An Overview Zahid Zufar At Thaariq
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35886

Abstract

The internet has caused a paradigm shift in education towards digitalization, so that students who experience it are now referred to as digital natives. This technology has changed the orientation of learning and teaching from teacher-centered to student-centered. Specific discussion is needed regarding the use of the internet modified in such a way in learning. Internet of Educational Things (IoET) becomes an interesting discussion in this article to support the paradigm shift. This article discusses using a narrative review approach. This means that this preparation tends to be reflective and in accordance with the author's understanding. The discussion includes (1) the paradigm shift from conventional to internet-assisted digital, (2) IoET as a digital-based instructional system approach and (3) related findings. Future recommendations will be presented, especially regarding the use of IoET in the education system.
Factors Influencing Young Audience Preferences for Digital Platforms in Indonesia Mochammad Abdul Machfud; Arieviena Ayu Laksmi; Tangkin Hong
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 2 (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.v1i2.35989

Abstract

The rapid development of digital technology and the widespread adoption of the internet have significantly transformed media consumption patterns, especially among young audiences in Indonesia. This study uniquely explores the preferences and motivations of Indonesian youth (ages 15-30) in selecting digital platforms over traditional media, applying the Theory of Planned Behavior (TPB) as a framework. TPB posits that Attitude Toward Behavior(ATB), Subjective Norms(SN), and Perceived Behavioral Control (PBC) are keyfactors influencing behavioral intentions. The results reveal distinct differences from prior research: SN and PBCemerged as dominant influencers, whereas ATBhad minimal impact. These findings underline the critical roles of social validation and platform usability in shaping preferences. Implications of this study include guiding media providers to develop strategies that cater to the social and functional needs of young Indonesians, ensuring sustained engagement with digital platforms.
Exploring Supervised Learning Methods for Predicting Cuisines from Their Ingredients Yonathan Ferry Hendrawan; Omkar Chekuri
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 1 (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.v2i1.34153

Abstract

This study explores the use of multi-class classification to predict cuisines based on ingredient list using a Kaggle dataset derived from the Yummly recipe database. The goal was to identify the most effective machine-learning techniques for classifying recipes into different cuisine regions based on their ingredients. Six supervised learning methods were examined: Backpropagation Neural Network, Support Vector Machine (SVM), Naive Bayes, Decision Tree, Random Forest, and AdaBoost. The preprocessing pipeline involvedtokenizing ingredients into numerical features, ensuring compatibility with machine-learning algorithms, and facilitating model training and evaluation. Among the models tested, the SVM and Random Forest algorithms performed the best, achieving accuracies of 76.7% and 73.2%, respectively. These results were relatively close to the top competition leaderboard accuracy of 83%. Our custom implementations oftheBackpropagation Neural Network and Decision Tree demonstrated competitive performance, though hardware limitations during experimentation prevented the full optimization of these models. The findings emphasize the critical role of factors such as parameter tuning, dataset size, and feature preprocessing in determining classification accuracy. Additionally, the study highlights how a combiningof well-selected algorithms and data preprocessing can yield meaningful improvements in prediction quality. All codesand materials used in this research are publicly available, enabling further exploration by other researchers and practitioners
Image Optimization Technique Using Local Binary Pattern and Multilayer Perceptron Classification to Identify Potassium Deficiency in Cacao Plants Through Leaf Images Muhammad Sya’rani Machrizzandi; Andi Hildayanti
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 1 (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.v2i1.34587

Abstract

Cocoa plants (Theobroma cacao, L.) are the best plantation crops in Indonesia that play an important role in the economy. However, in cultivation, cocoa farmers often face problems that can cause a decrease in cocoa production, one of which is the lack of potassium nutrients. Therefore, how to implement digital image processing which can help analyze image objects in the form of normal leaf characteristics and potassium-deficient leaf characteristics using the Local Binary Pattern (LBP) method for image feature extraction and classified using the Multilayer Perceptron (MLP) method in identifying potassium deficiencies in cocoa plants based on their leaf characteristics. In the image object in the form of leaf characteristics, each will be identified with 250 in the background dataset and 100 in the non-background dataset. So that the feature extraction process by LBP can be analyzed using the MLP parameter approach in the form of variations in the Learning_rate network and several solvers. In the case study conducted as the methodology applied starting from data collection, algorithm development, to validation and measurement using ROC, it was found that the results of the study using the LBP method and MLP classification showed that the best accuracy results in testing the background dataset using the learning_rate network 10(-4) with Solver lbfgs were 86.66% and the best accuracy in testing the non-background dataset using the learning_rate network 10(-3) with Solver adam was 80.00%.
Microstructure and Hardness Study of Al6061 Resulting from Artificial Aging Izzatus Tsamroh, Dewi; Puspitasari, Dewi; Puspitasari, Poppy; Mustapha, Mazli
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 1 (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.v2i1.34984

Abstract

This research aimed to improve the mechanical properties of Al6061 alloy through artificial aging heat treatment. The method used in this research was a laboratory-based experimental method. The Al6061 alloy was heated in a muffle furnace at a temperature of 480°C and held for 30 minutes. Next, rapid cooling (quenching) was carried out using cooling media of dromus oil. Then, specimens were reheated at 190°C for 2 hours, 4 hours and 6 hours for artificial aging process. The heat-treated specimens were tested for microstructure and hardness numbers. The data obtained were compared and analysed using image-J software. The research results showed that the smallest grain diameter was obtained in specimens treated with artificial aging for 4 hours, which was 47.633 µm. In this specimen, the β-Mg2Si phase was found to be 19.752 %. The highest hardness number was obtained in specimens with the same variation, which was 110.8 HRE.
A Review on Techniques Used for Solving the Economic Load Dispatch Problems: Categorization, Advantages, and Limitations Sabo Aliyu; Sadiq N. Buba; Kabir Muhammed; Samuel Ephraim Kalau; Daramola P. Olaniyi; Abdulmajid Muhammed Na'inna; Veerapandiyan Veerasamy
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 1 (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.v2i1.35591

Abstract

The increasing global demand for electric power presents significant challenges for power utilities, as they must balance the need for reliable and sustainable power generation with the goal to minimize generation costs. This challenge has led to studying Economic Load Dispatch (ELD), which aims to optimize power generation at minimal fuel costs.  This paper presents a comprehensive review of several primary techniques used in solving ELD problems, including traditional methods such as the Lambda Iteration, Gradient, and Newton-Raphson techniques, as well as modern optimization methods like Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Sine Cosine Algorithm (SCA), and Gravitational Search Algorithm (GSA). The paper also provides a comparative analysis using tables and chart in section three outlining the advantages, disadvantages, and limitations of each technique discussed in section two. Additionally, this review examines the applications of these techniques on IEEE test systems in various studies, highlighting their effectiveness on practical utility making it easier for researchers to make a choice in selecting a technique for their ELD problem.

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