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Machine Learning-Based Prediction of Corrosion Inhibition Efficiency of Expired Pharmaceuticals: Model Development and Application

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Journal of Bio- and Tribo-Corrosion 2025年第1期11卷 1-12页

作者： Putra, Dzaki Asari Surya Ardyansyah, Nibras Bahy Putranto, Nicholaus Verdhy Trisnapradika, Gustina Alfa Akrom, Muhamad Rustad, Supriadi Dipojono, Hermawan Kresno Maezono, Ryo Faculty of Computer Science Study Program in Informatics Engineering Universitas Dian Nuswantoro Semarang50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia School of Information Science Japan Advanced Institute of Science and Technology Ishikawa923-1292 Japan

Corrosion poses a significant challenge in industries due to material degradation and high maintenance costs, making effective inhibitors essential. Recent studies suggest expired pharmaceuticals as alternative corrosion inhibitors, but identifying the most efficient compounds can be time-consuming. This study applies machine learning models, particularly Gradient Boosting Regressor (GBR), to predict corrosion inhibition efficiency (CIE). The developed model is integrated into a web-based application, enabling real-time, accurate CIE predictions. Results show GBR as the more precise model for predicting CIE, with low error rates. The streamlit-based web application offers a user-friendly platform, facilitating quick identification of suitable inhibitors. It is flexible, supporting analysis beyond corrosion inhibitors, and significantly enhances the efficiency of the evaluation process. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Innovative web-based microteaching model: To improve the teaching skills of prospective informatics teachers in vocational high schools

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Social Sciences and Humanities Open 2025年 11卷

作者： Sugihartini, Nyoman Elmunsyah, Hakkun Nurhadi, Didik Rahmawati, Yuni Vocational Education Doctoral Program Post Graduate School Universitas Negeri Malang Malang Indonesia Informatics Education Study Program Department of Informatics Faculty of Engineering and Vocational Universitas Pendidikan Ganesha Bali Indonesia

Prospective informatics teachers in vocational schools (VS) must master content knowledge, pedagogical skills, and technology integration to achieve learning goals. Therefore, informatics teachers in VS need to innovate to increase students' creativity. However, many prospective informatics teachers experience difficulties in this regard. This research aims to develop and implement the Web-Based Microteaching (WBM) model to improve the teaching skills of prospective informatics teachers at VS. This study uses research and development methods with the ADDIE model approach. The research results show that the WBM model effectively improves prospective informatics teachers' teaching skills, especially in planning lessons and practising basic teaching skills. This innovation is a relevant learning solution in the digital era and positively contributes to the professional development of informatics teachers. The WBM model is an innovation to provide a more intensive and structured practical experience by utilizing web technology as the main media. Through web-based learning, prospective teachers can access material, exercises and feedback independently, which is expected to accelerate pedagogical mastery. © 2025 The Authors

关键词： Microteaching model Prospective informatics teacher Teaching skills vocational high schools Web-based

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

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Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Development of Automatic Plant Irrigation System using Soil Moisture Sensors for Precision Agriculture of Chili

Development of Automatic Plant Irrigation System using Soil ...

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2020 International Conference on Smart Technology and Applications, ICoSTA 2020

作者： Priandana, Karlisa Wahyu, Ramadina Al-Fatihah Computer Science Department Bogor Indonesia Computer Engineering Study Program Vocational School Bogor Indonesia

ISBN: (纸本)9781728130835

In agriculture, water management is crucial to reduce the amount of water used for irrigation. This study aims to develop an automatic plant irrigation system to be implemented in the Greenhouse of the Department of computer Science, IPB University. The system is made of solenoid valves and soil moisture sensors whose amount is adjusted to the number of plants. This automatic plant irrigation system was created to support the development of smart and precision farming in Indonesia. Irrigation is done automatically and precisely for each plant by using a solenoid valve and a relay. The system prototype has been tested with different soil moisture values. Experiment results show that the prototype has successfully read the soil moisture value and can do the irrigation properly according to the specified functional requirements. © 2020 IEEE.

关键词： Soil moisture

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Methodology for optimizing electrical grounding grids in stratified soils using advanced calculation techniques and evolutionary algorithms

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Swarm and Evolutionary Computation 2025年 95卷

作者： Silva, Carlos Leandro Borges da Pires, Thyago Gumeratto Silva Filho, Antonio Marcelino Bulhões, Junio Santos Belo, Orlando M. Oliveira Rodrigues, Clóves Gonçalves Coimbra, Antonio Paulo Calixto, Wesley Pacheco Electrical Mechanical & Computer Engineering School Federal University of Goias Goiania Goias PC 74.605-220 Brazil Institute of Systems and Robotics Coimbra University CoimbraPC 3030-290 Portugal Department of Informatics School of Engineering University of Minho BragaPC 4710-057 Portugal Electrical Power Systems Study Group Federal Institute of Tocantins Palmas TocantinsPC 77.021-090 Brazil Graduate Program in Production and Systems Engineering Pontifical Catholic University of Goias Goiania Goias PC 74605-010 Brazil Mato Grosso Brazil Technology Research and Development Center Federal Institute of Goias Goiania Goias PC 74.055-110 Brazil

This paper presents a practical methodology for optimizing the geometry of electrical grounding grids at industrial frequencies of 50Hz and 60Hz, integrating advanced calculation techniques and evolutionary algorithms to improve the safety and operational performance of electrical grounding systems. The proposed approach is particularly beneficial for industrial automation and control systems, where effective grounding is necessary to maintain system reliability and prevent downtime. This methodology employs mathematical modeling and computational tools to optimize grid parameters, ensuring compliance with safety standards while reducing operational costs, thus contributing to the overall efficiency of automated systems in industrial environments. The study reports a reduction of up to 66% in the number of vertical rods and 40% in horizontal conductors compared to traditional methods. These results indicate that the proposed methodology can significantly reduce material usage and costs while maintaining electrical safety in accordance with regulatory standards, making it applicable to a wide range of industrial settings, including substations and automated facilities. © 2025 The Authors

关键词： Electric grounding

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An Effort to Increase the Potential of Virgin Coconut Oil with Pendawa Technique 6

An Effort to Increase the Potential of Virgin Coconut Oil wi...

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Joint Conference of the 6th Annual Conference of Industrial and System engineering 2019, ACISE 2019 and 1st International Conference on Risk Management as an Interdisciplinary Approach 2019, ICRMIA 2019

作者： Sapatra, E.F. Yuniarti, I. Imamsyah, R.A.S. Industrial Chemical Engineering Technology Study Program Faculty of Vocational School Diponegoro University Indonesia

In order to overcome the disadvantages of conventional method, innovations on how to produce coconut oil were applied with the technique of PENDAWA (Pendayagunaan Asam Jawa). Coconut oil comes from coconut milk which is the substance between oil and water (emulsion). So to get coconut oil, acid is needed as an emulgator to break down emulsifying substances. In this case, Tamarind is used because it is cheap, available, contains a lot of antioxidants, and is efficacious. Coconut oil contains medium chain saturated fatty acids, namely MCT (Medium-chain triglycerides) where MCT provides extraordinary health enhancing properties. We compared three types of coconut oil, namely coconut oil in the traditional way, coconut oil with the addition of tamarind, and packaging oil on the market. The result was coconut oil with the Pendawa method very good in quality and quality with FFA 0.0067% and peroxide number of 1.5 mg ek/kg. In conclusion, this oil production with the PENDAWA method is very effective, efficient, high in quality, and provides high profit for the industry that wants to produce it. © Published under licence by IOP Publishing Ltd.

关键词： Emulsification

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Heat transfer performance of serpentine mini-channel cold plate in various Reynolds numbers

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AIP Conference Proceedings 2025年第1期3120卷

作者： Muhammad Aulia Rahman Yusuf Yunus Indro Pranoto Khasani Djati Wibowo Djamari Department of Mechanical and Industrial Engineering Faculty of Engineering Gadjah Mada University Jl. Grafika No. 2 Kampus UGM Yogyakarta 55281 Indonesia Mechanical Engineering State Vocational High School 2 Ternate Ternate 97727 Indonesia Mechanical Engineering Study Program Faculty of Engineering and Technology Sampoerna University Jakarta 12780 Indonesia

The electric vehicle showcases a promising development in the future. Recently, the most reliable power storage for such a system is a Li-ion battery. The performance of this battery, however, relies on the thermal management system implemented on the vehicle. Albeit having a sufficient performance for the current state of an electric vehicle, enhancement is necessary to make sure that the future requirement is within the remit of the cooling system. One of the simple but powerful enhancements is by employing a mini-channel cold plate. In this study, the performance of a serpentine mini-channel cold plate in various Reynolds numbers (Re) was investigated experimentally. The results illustrate a better mean of cooling of high Re flow, indicated by the lower surface temperature and higher heat transfer coefficient up to 2.1 W/m2·K. Additionally, the performance was then compared to the pressure drop to represent the efficiency of the pumping power requirement of such a system. The highest h/ΔP is observed at Re = 2130.33 which correspond to the mass flow rate of 0.5 LPM. It was found that although having a higher heat transfer coefficient, the efficiency is much lower due to pressure drop rise as the mass flow rate increases.

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Batik Industrial Waste Monitoring and Control System Based on the Internet of Things 5

Batik Industrial Waste Monitoring and Control System Based o...

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5th International Conference on Electrical, Electronics, Informatics, and vocational Education, ICEELINVO 2022

作者： Ali, M. Firdaus, M.F. Electrical Engineering Education Department Faculty of Engineering Universitas Negeri Yogyakarta Indonesia Electrical Study Program Vocational School Universitas Negeri Yogyakarta Indonesia

The aims of this research are to (1) Design and build a Batik Industrial Waste Monitoring and Control System Based on the Internet of Things (BIWMCS -IoT);(2) Test the performance of the BIWMCS-IoT system. The design and implementation of the BIWMCS-IoT system consist of five stages, namely: (1) Needs analysis, (2) Design, consisting of electronic planning, hardware, and software;(3) Development, including hardware and software development;(4) Testing, and (5) implementation. The BIWMCS-IoT system consists of a sensor unit to measure the parameters of water turbidity, temperature, Power of Hydrogen (pH), and the flow velocity of the wastewater then obtained by the microcontroller and the results are sent to the Wi-Fi module to adjust the solenoid valve opening and closing. Based on the testing of the system, has been shown that the BIWMCS-IoT system can work well according to the standards in the Minister of Indonesian Environment Regulation Number 05 of 2014. The reading accuracy of the batik waste monitoring system reaches 96.6% with the delivery time to the smartphone less than 30 seconds. This shows that this system can work well to monitor and control the liquid waste produced by the batik industry. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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Developing indicators of green initiation and green design of green supply chain management in construction industry 2

Developing indicators of green initiation and green design o...

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2nd International Conference on Electrical engineering and Green Energy, CEEGE 2019

作者： Wibowo, Mochamad Agung Handayani, Naniek Utami Farida, Nur Nurdiana, Asri Department of Civil Engineering Faculty of Engineering Diponegoro University Indonesia Department of Industrial Engineering Faculty of Engineering Diponegoro University Indonesia Study Program of Civil Engineering Vocational School Diponegoro University Indonesia

Project is a set of interrelated activities and requires skills from different professions, and also project is involved the various of stakeholders in each phase of the Project Life Cycle. Implementation of Green Supply Chain in construction projects meant to bring the concept of eco-friendly in every process from the initiation phase, planning phase, the construction phase, and the operation and maintenance phase. It is necessary to identify indicators of green initiation and green design and how to explain the relationship between the role of initiation by the owner and the design process by a design consultant. This study aims to identify the indicators of green initiation and green design concept as part of Green Supply Chain. The method used for this study is a descriptive research that identifies and develop a framework for implementing green initiation and green design in construction industry that consists of concept, dimensions, elements, and indicators. GSCM in construction projects was determined by 9 indicators in the green initiation phase and 40 indicators in the green design phase. The success of green concept in construction project is very determined from these two phases as the beginning of the process, and the most important parties are the owners and design consultants. © 2019 The Authors, published by EDP Sciences.

关键词： Construction industry

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