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6th International Conference on Information Technology, Information Systems and Electrical engineering, ICITISEE 2022

作者： Hasan, Mhd Arief Sarno, Riyanarto Ardani, M. Syauqi Hanif Intitut Teknologi Sepuluh Nopember Informatics Department Surabaya Indonesia Universitas Lancang Kuning Informatic Engineering Study Program Pekanbaru Indonesia

ISBN: (纸本)9798350399615

In this study, we built an Electronic Nose to detect pineapple ripeness. We designed a prototype E-Nose using a wooden crate. Inside the box, we built the E-Nose using 9 MQ sensor circuits connected to the Arduino Microcontroller. In the crate, we put an object, namely a pineapple with three levels of ripeness (ripe, half ripe, and unripe), each weighing 1kg placed in three different positions (5cm, 20cm, and 35cm) from the position of the sensor array (E-nose). We converted the signal output results into ppm units. We compared the value of each fruit signal based on the level of ripeness and distance using E-Nose. We used several signal processing methods (wavelets) for signal processing. Then, we improved the signal generated using wavelet. The wavelet methods used are Moving Average, Fast Fourier Transform (FFT), and Discrete Wavelet Transform (DWT). The contribution of this research is to see the influence of the signal valuegenerated from the sensor (MQ Sensor) to the position (distance) of the object (fruit) and its influence on the level of maturity (fruit). Then signalgenerated from the sensor we make improvements with the mva, fft, and dwt methods. © 2022 IEEE.

关键词： DWT E-Nose FFT MVA Pineapple

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Deep Learning for Cyber Security: Deephoax Detection 2

Deep Learning for Cyber Security: Deephoax Detection

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Yakub, Sy. Yuliani Wowor, Rivo Juicer Agustriawan, David Irmawati Kristiyanti, Dinar Ajeng Winarno, P.M. Hassan, Rosilah Mohamad, Roshayu Razzaq, Randy Zahran Universitas Multimedia Nusantara Department of Informatics Tangerang Indonesia Information System Study Program Universitas Multimedia Nusantara Tangerang Indonesia Universiti Kebangsaan Malaysia Selangor Malaysia College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Uin Sultan Maulana Hasanuddin Department of Informatics Banten Indonesia

ISBN: (纸本)9798331506995

The increasing prevalence of deep hoaxes, such as fake news and phishing schemes, poses a significant threat to cybersecurity, undermining trust and spreading misinformation. In Indonesia, surveys indicate that more than 60% of people exposed to hoax news believe that it is true, emphasizing the urgent need for robust detection methods. Traditional cybersecurity approaches often struggle to keep pace with the growing scale and sophistication of these attacks. To address this challenge, this research investigates the use of deep learning techniques, specifically focusing on text-based hoax detection in the Indonesian language. The study fine-tunes IndoBERT, a pretrained deep learning model optimized for Indonesian text, to enhance the accuracy and scalability of hoax detection. The IndoBERT model was trained on a balanced dataset of 29,552 articles, comprising both hoax and real news content, collected from the Mafindo API and Kaggle's Indonesia News Dataset. The model was fine-tuned using supervised learning and evaluated using several key metrics, including accuracy, F1-score, precision, and recall. The results demonstrate that IndoBERT outperforms existing state-of-the-art approaches, achieving an accuracy of 98.51%, an F1-score of 98.44%, and a precision of 98.23% on the test set. These results highlight the effectiveness of IndoBERT for hoax detection, which offers a scalable solution to improve cybersecurity defenses against deceptive content. This research contributes to the integration of advanced deep learning models into cybersecurity systems, addressing the evolving landscape of cyber threats. © 2025 IEEE.

关键词： Cyber attacks

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Development of STEM project-based learning student worksheet for Physics learning on renewable energy topic 12

Development of STEM project-based learning student worksheet...

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12th International Physics Seminar, IPS 2023

作者： Muliyati, D. Prastiawan, F. Mutoharoh, M. Department of Physics Education Faculty of Mathematics and Natural Sciences Universitas Negeri Jakarta East Jakarta13220 Indonesia Industry Engineering Study Program Universitas Krisnadwipayana Jatiwaringin Bekasi13077 Indonesia

This research is motivated by the development of education in the 21st-century, which demands students to master the 4C skills (creative thinking, critical thinking, collaboration, and communication), particularly in the field of physics. The nature of physics learning requires active and interactive teaching methods that can be implemented through project-based activities for students. One effective instructional media is the student worksheet designed based on STEM-PjBL (science, technology, engineering, and mathematics project-based learning) principles. This research aims to assess the suitability of STEM-PjBL student worksheets as a learning media, which can serve as a recommendation to assist teachers in teaching renewable energy topics. This study uses the ADDIE model to adopt the Research and Development (R&D) method. This research results in a STEM-PjBL student worksheet as a physics learning media to understand renewable energy topics. The STEM-PjBL student worksheet is expected to assist students in mastering 21st-century skills effectively. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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Magnetic and Optical Properties of a-Fe2O3/TiO2 Nanocomposite Derived from Logas Natural Sand for Environmental Application

Magnetic and Optical Properties of a-Fe2O3/TiO2 Nanocomposit...

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2024 International Conference on Applied Sciences and Material Applications, ICASMA 2024

作者： Amiruddin, Erwin Awaluddin, Amir Rini, Ari S. Umar, Lazuardi Rianna, Martha Hadilala, Teguh P. Putri, Novalin Department of Physics Faculty of Mathematics Natural Sciences Riau University Pekanbaru28293 Indonesia Department of Chemistry Faculty of Mathematics Natural Sciences Riau University Pekanbaru28293 Indonesia Department of Physics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan20155 Indonesia Magnetic Laboratory Faculty of Mathematics and Natural Sciences Riau University Pekanbaru28293 Indonesia Laboratorium Jalan Civil Engineering Magister Study Program Faculty of Civil Engineering Diponegoro University Central Java Semarang50275 Indonesia

In this study, the iron oxide/titanium dioxide (a-Fe2O3/TiO2) nanocomposites derived from Logas natural sand were prepared by ball milling method. The effects of milling time on the magnetic, optical properties and chemical composition of the nanocomposites were investigated using vibrating sample magnetometer (VSM), Uv-Vis spectroscopy and X-ray fluorescence (XRF) spectroscopy, respectively. The magnetization measurement results of all the samples showed the presence of ferromagnetic behaviour characterized by their low coercivity value ranged from 360.10 Oe to 86.50Oe. The optical properties of the samples strongly depend on milling time and showed that the band gaps of the iron oxide/titanium dioxide (a-Fe2O3/TiO2) nanocomposites decrease with increasing milling time. Some other elements such as silicon, aluminium and others were detected, which shows that the milled sample is not purely a-Fe2O3/TiO2 nanocomposites as confirmed by X-Ray Fluorescence. This study demonstrates the simple way of preparing the a-Fe2O3/TiO2 nanocomposites for environmental application. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Milling (machining)

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Design and fabrication of photovoltaics based on MFS (Ag/BaTiO3/silicon p-type) structure

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Materials Science for Energy Technologies 2024年第1期7卷 29-34页

作者： Irzaman Dahrul, M. Rahmani, M. Rukyati, A.M. Samsidar Nurhidayah Deswardani, F. Peslinof, M. Jenie, R.P. Iskandar, J. Wahyuni, Y. Priandana, K. Siskandar, R. Department of Physics Faculty of Mathematics and Natural Sciences IPB University Bogor16680 Indonesia Department of Physics Faculty of Sciences and Technology Jambi University Jambi36361 Indonesia Department of Nutrition Faculty of Health Science and Technology Binawan University East Jakarta13630 Indonesia Department of Computer Engineering Pakuan University Bogor16142 Indonesia Department of Computer Science IPB University Bogor16680 Indonesia Computer Engineering Technology Study Program College of Vocational Studies IPB University West Java Bogor16151 Indonesia

The experiment was carried out by growing BaTiO3 (Undoped or Li-doped) on p-type Si(1 0 0) substrates using the Chemical Solution Deposition (CSD) method and spin coating at a rotational speed of 3000 rpm for 60 s, followed by heating at 850 °C. The characterization results show that the bandgap energy value of the thin film due to lithium doping reduces the bandgap energy value. This is presumably because the donor atom added to a semiconductor causes the allowable energy level to be slightly below the conduction band. The presence of this new band causes the thin film bandgap energy to decrease with a five-valent tantalum dip. The morphological properties showed that the BaTiO3/Si(1 0 0) thin film particles in the deposited lithium had a fairly homogeneous grain. With the addition of lithium acetate as a binder into barium titanate, the grain size is getting smaller because it is suspected that the lithium-ion radius is smaller than the barium-ion radius. Measurement of I-V on the thin film shows that the output voltage value increases with more light intensity hitting the surface of the thin film. The greater the light intensity, the greater the energy of the photons, so the electrons are easier to jump. The three things above (both electrical and morphological properties) conclude that the thin films grown have the potential for photovoltaics. © 2023

关键词： Thin films

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Selection of Education Assistance Recipients Based on AHP and SAW 23

Selection of Education Assistance Recipients Based on AHP an...

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23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022

作者： Pranoto, Gatot Tri Pebrianti, Dwi Darwis, Muhammad Yaddarabullah Krishnasari, Erneza Dewi Pelita Bangsa University Informatics Engineering Study Program Bekasi Indonesia Budi Luhur University Computer Science Jakarta Indonesia Universitas Trilogi Department of Informatics Engineering Jakarta Indonesia Universitas Trilogi Department of Visual Communication Design Jakarta Indonesia

ISBN: (数字)9781665460811

ISBN: (纸本)9781665460811

The final decision of the educational assistance recipient in GNOTA Foundation, Jakarta is still processed manually. They usually only look at the father's occupation criteria without looking at other criteria such as the age of the child, the child's orphan status, the occupation of mother, the age of father, the age of mother and other scholarships received. GNOTA Foundation needs to implement a Decision Support System (DSS) for the selection process, so the results are fast and on target. This research applies the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods for the selection of education assistance recipients so the criteria can be weighted and the prospective recipient students can be ranked. This research determines the priority weight and importance of each criterion, namely the age of child age (0.18), the status of child (0.22), the occupation of father (0.08), the occupation of mother (0.06), the age of father (0.05), the age of mother (0.04) and other scholarship assistance (0.36). The results of the weighting of these criteria have been tested and declared consistent through the Consistency Ratio (CR) value of 0.070. This study also produces a list of the best ranking students who are prospective recipients of educational assistance. The ranking results have been tested based on compliance with the provisions of the GNOTA Foundation of 92.91%. The system in this study was developed using a prototyping system development model and utilizing the Unified Modeling Language (UML) tool. The prototype functionality in this study works well by using the Blackbox Testing (BBT) model based on Equivalence Partitioning. In addition, the level of user acceptance of the prototype in this study was 81.2% using the Technology Acceptance Method (TAM). © 2022 IEEE.

关键词： Decision support systems

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Observing Generator Performance by Finite Element Analysis Considering Coil Numbers 5

Observing Generator Performance by Finite Element Analysis C...

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5th International Conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2023

作者： Habibi, Muhammad Afnan Ali Irfani, Mochamad Farhan Gumilar, Langlang Kusumawardana, Arya Aripriharta Baskoro, Angger Universitas Negeri Malang Study Program of Power Plant Engineering Technology Malang Indonesia Universitas Negeri Malang Department of Electrical Engineering and Informatics Malang Indonesia National Yang Ming Chiao Tung University Dept. Electrical Engineering and Computer Sciences Hsinchu Taiwan

ISBN: (纸本)9798350369717

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies. © 2023 IEEE.

关键词： Finite element method

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Unraveling Game Addiction Behavior Among Digital Native Students: Leveraging Machine Learning for Insights

Unraveling Game Addiction Behavior Among Digital Native Stud...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Rona Nisa Sofia Amriza Cut Alna Fadhilla Department of Information System Telkom University Purwokerto Indonesia Informatics Study Program Faculty of Engineering Universitas Samudra Aceh Indonesia

ISBN: (数字)9798350368086

ISBN: (纸本)9798350368093

The allure of gaming often leads to excessive engagement, which can result in addictive and problematic behaviors, negatively impacting academic performance and school achievements. While gaming becomes increasingly prevalent, concerns about game addiction have grown, particularly among students. The excessive and obsessive usage of video games that characterizes game addiction can have detrimental effects like academic deterioration, social isolation, and mental health problems. This study seeks to elucidate the complex patterns of game addiction among digital-native students by utilizing advanced machine learning techniques. We employed Random Forest, SVM, Decision Tree, and Naïve Bayes algorithms to classify game addiction data from students. To address the class imbalance, we applied Borderline-SMOTE. Our results demonstrate that decision tree and random forest outperformed other machine learning approaches, achieving an accuracy of $\mathbf{9 5 \%}$ in classifying game addiction. These findings contribute to the expanding body of knowledge on game addiction. Furthermore, in order to provide real-time monitoring and intervention for students who are at risk of developing a game addiction, future research may investigate incorporating these findings into educational platforms or applications.

关键词： Support vector machines Video games Addiction Games Real-time systems Vectors Bayes methods Decision trees Older adults Random forests

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Affordable ESP32-based monitoring system for microbial fuel cells: real-time analysis and performance evaluation (ESP32-based data logger as a monitoring system for microbial fuel cell)

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International Journal of Energy and Water Resources 2024年第2期8卷 199-212页

作者： Indriyani, Y.A. Efendi, R. Rustami, E. Rusmana, I. Anwar, S. Djajakirana, G. Santosa, D.A. Study Program of Soil Sciences Graduate Schools IPB University Bogor Indonesia Department of Mechanical Engineering Faculty of Engineering Universitas Sulawesi Tenggara Kendari Indonesia Department of Physics Faculty of Mathematics and Natural Sciences IPB University Bogor Indonesia Department of Biology Faculty of Mathematics and Natural Sciences IPB University Bogor Indonesia Department of Soil Science and Land Resource Faculty of Agriculture IPB University Bogor Indonesia Biotechnology Center Research and Community Empowerment Institute IPB University Bogor Indonesia

Microbial fuel cells (MFCs) are bioelectrochemical instruments that exploit living microbes as biocatalysts for the conversion of chemical energy stored in the bonds of substrates into electrical energy. Monitoring of current or voltage generation in microbial fuel cells at rigid time intervals is noteworthy. Unfortunately, bioelectrochemical studies are often constrained due to the need for expensive and precise devices for electrochemical measurements. Utilization of low-cost microcontroller as monitoring system can be a considerable solution, compared with data logger that is a high-cost device, or compared with commercial multimeter that have to be used manually in collecting data. In this present work, microbial fuel cells electricity generation was successfully online monitored and the voltage data was also successfully collected using an ESP32 based-data logger. Statistically, there was no significant difference between ESP32 and multimeter in voltage reading, and the average of absolute and relative error values were 0.85 mV and 2.72%, respectively. It suggested that ESP32 could be a possible and low-cost monitoring system for microbial fuel cells bioelectricity generation. Additionally, ADS1115 (an external analogue to digital converter interface to ESP32) has up to four analogue channels, whereas multimeter has just one. In this research, microbial fuel cell powered by isolate KCf1 generated highest voltage value of 789 mV and power density of 541 mW m⁻². © The Author(s), under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2023.

关键词： Biofuel Electricity Electrochemistry Green technology Renewable energy

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