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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 8 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2025)" : 8 Documents clear
Exploring Supervised Learning Methods for Predicting Cuisines from Their Ingredients Hendrawan, Yonathan Ferry; Chekuri, Omkar
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

Various regions around the world use similar ingredients for food preparation, with exceptions of unique regional ingredients. However, the variation in the cuisines in the regions stems from the unique combinations of these ingredients. This aspect has been explored in Kaggle's competition, in which many submissions and solutions have been put forward. However, to the best of our knowledge, there is still no paper that compares Backpropagation, Support Vector Machine, Naïve Bayes, Decision Tree, Random Forest, and AdaBoost to predict cuisines based on their ingredients. We present our approach and measurement of those Supervised Learning Methods for tackling the problem. We use a combination of Machine Learning library and our own method implementations to conduct the experiment. Our results show that all the methods have more than 55% accuracy, and the best result achieved is 76.769% for Support Vector Machine. Given the small data size and high dimensionality of text data, SVM and Naive Bayes generalize well, compared to the more complex methods such as Neural Network. Our results also suggest that Random forest is robust and handles noise in the data well compared to AdaBoost.
Image Optimization Technique Using Local Binary Pattern And Multilayer Perceptron Classification To Identify Potassium Deficiency In Cacao Plants Through Leaf Images Hildayanti, Andi; Machrizzandi, Muhammad Sya’rani
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; Buba, Sadiq; Muhammed, Kabir; Kalau, Samuel ephraim; Olaniyi, Daramola paul; Veerapandiyan Veerasamy; Abdulmajid Muhammed Na'inna
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.
Design of Automatic Battery Charger Using Forward DC-DC Converter for Solar Home Energy Vidia Laksmi B, Nur; Muhammad Syahril Mubarok; Fithrotul Irda Amaliah; As’ad Shidqy Aziz; Daeng Rahmatullah; Dimas Herjuno; Habibi, Muhammad Afnan
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.v2i1.35817

Abstract

The utilization of solar energy as a renewable and environmentally friendly energy source, which is inexhaustible, is an ideal solution to meet the growing demand for electricity. Solar Home Energy refers to a house powered by solar energy. The solar energy is subsequently stored in batteries using a battery charger. In this paper, a forward DC-DC converter is used as a battery charger to supply power to a self-sufficient house from solar energy, stored in a 96 V 45 Ah battery. A fuzzy logic controller is employed to regulate the output of the forward DC-DC converter, ensuring a constant charging voltage according to the set point. The output of this project is designed for 110 V 4.5 A; however, in practice, the forward DC-DC converter only achieved a charging voltage of 100.5 V, resulting in an error of 8.63% from the planned value. Additionally, the charging current reached 1.4 A, leading to a significant error of 63.89% from the planned charging current.
Designing of An Integrated Port Development Planning Model: Application to The Three Main Cameroonian Ports NDZIE BITUNDU, Christian Alain Bienvenu; WOUNBA , Jean François; BWEMBA , Charles; FONDZENYUY, Stephen Kome
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.v2i1.35876

Abstract

The Chad and the Central African Republic countries threatened to find an alternative to Cameroon's ports because of the low accessibility and inefficiency of these ports. The objective of this study in its relevance is to characterize the current hinterland of Cameroonian maritime ports, to analyze the dynamics of the flow of goods in the port hinterland of Cameroon, and to make recommendations for improving the National Port Master Plan to guarantee the increased development of Cameroonian maritime ports. The Huff model integrated into the Spatial Interaction Model (SIM) is used to geographically delimit the economic hinterland of Cameroon's seaports. The results of the study highlight two key points: (1) the significance of integrating the development of Cameroon’s port hinterland into the national port planning strategy to enhance the growth of the country’s maritime ports. (2) Each port in Cameroon should pay more attention to the expansion of the hinterland. This study introduces methods integrating the SIM approach for practical hinterland exploration with the Bayesian model and mutual information for analyzing hinterland needs. Additionally, it offers recommendations for a seaport development planning model. This article broadens the use of the SIM Bayesian model with mutual information, which can easily be adapted to other scenarios.
Analysis of Microbial and Physio-Chemical Attributes in Fresh, Sun-Dried, and Oven-Dried Tomatoes (Solanum Iycopersium) Omorodion, Nnenna Jennifer; Richmas Obiobu, Euboniso
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.v2i1.35906

Abstract

This study accessed the microbial and physiochemical qualities of fresh, oven-dry, and sun-dry tomatoes to comprehensively understand the impact of drying methods on the quality and safety of this widely consumed fruit. Microbial and physiochemical analysis were done using standard methods. It revealed the variations in microbial population with the results showing the total viable bacterial count ranged from 1.3×106cfu/g to 2.7×106cfu/g with fresh tomato (FT) slices having the highest value (2.7×106cfu/g). Sun-dried tomatoes (SD) (2.3×106cfu/g), oven-dried at 40°C (1.6×106cfu/g) and oven-dried at 60°C (1.4×10-6cfu/g) respectively. The least count was obtained from sample oven-dried (OVD) at 80°C (1.3×106cfu/g). The total viable fungal count the fresh tomato (FT) slices had the highest counts (2.6 ×104cfu/g) and the least count was obtained from sample oven-dried at 40°C (6×103cfu/g), highlighting the dynamic microbial changes during different drying processes. Additionally, physiochemical assessments encompassed proximate compotion, pH and ascorbic acid levels. The pH range was between 4.1 (for fresh tomatoes) and 5.2 (for sun-dried tomatoes). Ascorbic acid levels also showed Fresh tomatoes (28.32mg/100g) were the highest but in this case, Oven-dried at 80°C had the least (9.21mg/100g). Notable differences emerged, shedding light on the consequences of drying techniques on key quality indicators. In conclusion, this study provides a comprehensive analysis of the microbial and physiochemical properties of fresh, oven-dry, and sun-dry tomatoes, elucidating the impact of various drying methods on the quality and safety of this widely consumed fruit. More so, the observed variations in physiochemical properties suggest the need for careful consideration of other drying methods such as vacuum drying and freeze-drying to preserve flavor, enhance shelf life, and maintain nutritional quality.
Modified FATA Morgana Algorithm Based on Levy Flight Prapanca, Aditya; Nasreddine Belhaouas; Imed Mahmoud
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.v2i1.37066

Abstract

Metaheuristics is an algorithmic approach used to solve complex optimization problems that are difficult to solve with conventional methods. The wide application of metaheuristics shows the flexibility and effectiveness of this method in solving various optimization problems in various fields. With the continuous development of technology and the need for more efficient solutions, the use of metaheuristics is expected to increase in the future. A novel group intelligence technique, called the modified mirage algorithm (FATA), is introduced to tackle continuous multi-type optimization problems.  FATA formulates the mirage light filtering principle (MLF) and light propagation strategy (LPS) by replicating the mechanism of mirage formation.  The MLF approach, together with the final integration concept, improves the algorithmic population's exploration capacity within FATA.This study presents the application of the levy flight method to the fata morgana algorithm. Validation in this study between the proposed method and the original fata morgana algorithm. From the simulation results, it is found that the proposed method has better performance on unimodal and multimodal functions.

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