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2nd International Conference on Sustainable Engineering and Creative Computing, ICSECC 2020

作者： Hidayat, Eka Wahyu Giriantari, Ida Ayu Dwi Sudarma, Made Widyantara, I. Made Oka Department of Informatics Siliwangi University Tasikmalaya Indonesia Engineering Study Program Udayana University Denpasar Indonesia

ISBN: (纸本)9781728175881

The purpose of this paper is to gift a visualization of three-dimensional (3D) trees using L-System that has been researched before. In this research, he succeeded in making a two-dimensional (2D) tree visualization and stated that when the iteration value or iteration value is larger than five, the 2D tree model results from associate iteration, it lost detail from the branch. This research is to develop the research results, namely the transformation from a 2D tree to a 3D tree. This research is intended to see what is needed in the transformation process from a two-dimensional tree to a three-dimensional tree using the L-System approach. The experiments carried out in three steps, the first step performing a two-dimensional visualization of the grammar origin from the previous research, the second step carrying out a three-dimensional transformation, and the third step making grammar modifications so that the 3D tree becomes realistic. The test results show that mathematically there are differences in the depiction of geometry in the cartesian coordinate with three axes, namely the x, y, and z axes, causing the transformation process from two-dimensional to three-dimensional trees to expand the use of symbols in the L-System. The extended production rules give more complex and more refined geometric shapes. © 2020 IEEE.

关键词： Visualization

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5kW BLDC Motor Characterization for Plugging Brake Application in Electric Vehicle

5kW BLDC Motor Characterization for Plugging Brake Applicati...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Faiza Latifah Muhamad Fajar Imanul Haq Mulia Pratama Dewi Indriati Hadi Putri Muhammad Rizalul Wahid Estiko Rijanto Bambang Wahono Arifin Nur Yanuandri Putrasari Muhammad Khristamto Aditya Wardana Achmad Praptijanto Suherman Ahmad Dimyani Study Program of Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Purwakarta Indonesia Research Center For Smart Mechatronics Research Organization of Electronics and Informatics National Research and Innovation Agency Indonesia Bandung Indonesia Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Purwakarta Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

In advancing electric vehicle technology, the braking system is a vital component with significant impacts on driver safety features. Numerous factors, such as high speeds, adverse weather conditions, human mistakes, and system malfunctions, play a role in the large number of vehicle accidents that happen each year. This has prompted vehicle manufacturers to develop advanced braking systems with the objective of reducing the likelihood of such incidents. The objective of this research is to implement a plugging braking system in electric vehicles, given the importance of the combination of electric and mechanical braking torque in ensuring the safe stopping of a vehicle. The methodology employed involved plugging brake modeling of a BLDC motor, the experiments of plugging brake, and the utilization of PWM as a regulator of plugging brake. The findings demonstrate that an increase in the PWM duty cycle of 58% (150), 78% (200), 98% (250) and 100% (255 full) can reduce the time required to stop the motor up to 2 seconds from the initial speed of 500 rpm, thereby underscoring the significance of PWM duty cycle variation in altering the braking current and thus the braking force.

关键词： Torque Wheels Pulse width modulation Motors Electric vehicles Safety Brakes Electromagnetics Stress Vehicles

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Application of K-Medoids Cluster Result with Particle Swarm Optimization (PSO) in Toddler Measles Immunization Cases 1

Application of K-Medoids Cluster Result with Particle Swarm ...

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1st Virtual Conference on Engineering, Science and Technology, ViCEST 2020

作者： Cynthia, Eka Pandu Rahadjeng, Indra Riyana Karyadiputra, Erfan Rahman, Fauzi Yusa Windarto, Agus Perdana Limbong, Martalina Hermanto, Teguh Iman Rusiadi, E. Yarmani, Y. Informatics Engineering Study Program Faculty of Science and Technology UIN Sultan Syarif Kasim Riau Indonesia Universitas Bina Sarana Informatika Jakarta Indonesia Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin Indonesia STIKOM Tunas Bangsa Pematangsiantar Indonesia Akademi Keperawatan Surya Nusantara Pematangsiantar Indonesia Informatics Engineering Study Program Sekolah Tinggi Teknologi Wastukancana Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Universitas Bengkulu Bengkulu Indonesia

The objective of the research was to analyze the clustering method by optimizing Particle Swarm Optimization (PSO) in the case of measles immunization for children under the age of 5. The research data source used is the North Sumatra Province Central Bureau of Statistics (https://***/). The data used in 2019 included 33 records with variables BCG, DPT-HB3/DPT-HB/Hib3, CAMPAK (MEASLES + RUBELLA), POLIO 4 and HEPATITIS B. The methods used were k-medoids and PSOs. This method is used to determine the value of the Davies Bouldin Index (DBI) before the cluster value is determined (k). The resulting k values were compared to k-medoids without PSO. The best results of k-medoid and PSO will be tested by classification to see the accuracy value of the cluster formed. The results showed that the optimization of k-medoids and PSO was better with the number of clusters (k = 5) than 0.078. (DBI). The results also show that the accuracy of the cluster formed is 95% with a correlation of 0.98. © Published under licence by IOP Publishing Ltd.

关键词： Immunization

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Twitter Data Sentiment Analysis of COVID-19 Vaccination using Machine Learning 5

Twitter Data Sentiment Analysis of COVID-19 Vaccination usin...

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5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022

作者： Maulana, Fairuz Iqbal Adi, Puput Dani Prasetyo Lestari, Dian Purnomo, Agung Prihatin, Sukeipah Yuli School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia Informatics Study Program Politeknik Kota Malang Malang Indonesia

ISBN: (纸本)9781665455121

The expansion of the web is accelerating, which helps encourage the creation of fresh ideas. In today's internet era, we must suggest techniques to filter out various information. Social media sentiment analysis based on Twitter data can monitor the real-Time monitoring of the COVID-19 vaccine. In this way, relevant organizations or governments can take proactive steps to address misinformation and inappropriate behaviour around the COVID-19 vaccine, which threatens the success of the national vaccination campaign. The purpose of this research is to determine if there is a link between how people feel about the COVID-19 vaccine on Twitter and how many people actually get vaccinated against it. This study uses the COVID-19 All Vaccines Tweet dataset sourced from Kaggle. This research Identifies public sentiment, emotion, word usage, and trend of all filtered tweets. The results show that there are 31% positive tweets, 10% negative tweets, and 58% neutral tweets. Tweets with neutral subjective valence tend to cluster in the middle of the polarity scale (between-1 and +1), whereas tweets with strong subjective valence are spread across the scale. © 2022 IEEE.

关键词： COVID-19

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A Design for Three Phase Electronic Controller for Electric Motor Cycle Equivalent to 100-125 Cc Engine Power with Regenerative Braking System 1

A Design for Three Phase Electronic Controller for Electric ...

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1st Paris Van Java International Seminar on Computer, Science, Engineering, and Technology, PVJ ISComSET 2020

作者： Tsani, Umar Saepudin, Asep Sukamto, Pria Informatics Engineering Study Program Sekolah Tinggi Teknologi Muhammadiyah Cileungsi Jl. Anggrek No. 25 Perum PT. Semen Cibinong Cileungsi Bogor Indonesia Mechanical Engineering Study Program Sekolah Tinggi Teknologi Muhammadiyah Cileungsi Jl. Anggrek No. 25 Perum PT. Semen Cibinong Cileungsi Bogor Indonesia

Technology always have the potential to disruptive the society, especially electronics since this technology follows Moore Laws. Electric vehicle is predicted to change how individuals are going to do their daily commute. Electric motor cycle is an answer to eco-friendly transportation, economical in the operation and will be more affordable in the future for the people. One of the main component for this vehicle is the 3 phase motor controller. Three phase electric motor has an advantage of being light weight, low cost and more compact compare with dc motors with a comparable power. The design is featuring a regenerative braking system which brings back the mechanical energy back to the system on braking time hence a significant advantage to increase energy efficiency, since a major power lost is happening during braking on conventional vehicle. The design on purpose is using 100-125 cc equivalent of gasoline engine since this engine has the most market in Indonesia. Which is about 10 to 15 KW 3 phase AC motor. © Published under licence by IOP Publishing Ltd.

关键词： Energy efficiency

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Application of online science practicum by using Microsoft Teams and Learning Management System (LMS) during the Covid 19 pandemic 10

Application of online science practicum by using Microsoft T...

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10th National Physics Seminar, SNF 2021

作者： Pertiwi, W.A. Sanjaya, L.A. Nadiyah Hasirah Haramen, M. Budi, A.S. Zarvianti, E. Puspa, R.W.D. Sianipar, L.K. Qoiriyah, W. Sitompul, H. Islamic Education Management Study Program Faculty Islamic of Education and Teacher Training Muhammad Azim Institute Jambi Indonesia Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Jakarta Indonesia Sharia Economics Study Program Faculty of Sharia and Law Muhammad Azim Islamic Institute Jambi Indonesia Physics Education Study Program STKIP Muhammadiyah Sungai Penuh Indonesia Kartika VIII-1 Senior High School Jakarta Indonesia Department of Physics Education Universitas Pelita Harapan Tangerang15811 Indonesia Informatics Engineering Study Program Faculty of Engineering Sheikh Yusuf Islamic University Tangerang Indonesia

The research objective of this is to see how to apply science practicum online using Microsoft Teams and Learning Management System (LMS). The form of this research is classroom action research which aims to apply the online science practicum during the Covid 19 pandemic. Therefore, it is carried out using two cycles in the application of online science practicum. The subjects of this study were students of the seventh semester in the Natural Science practicum course. Through observation and evaluation, it is shown that in the cycle I the percentage of practicum implementation which includes aspects of preparation, process and data and practicum results is 87.5%, in cycle II it has increased to 92.5%. In the assessment aspect of the practicum report, the average practicum assessment obtained in the first cycle was 3.09 from the highest score of 4 and in the second cycle was 3.7, while the aspect of student knowledge about the use of the Microsoft team which was taken using google form was 93%. In the aspect of student knowledge about the use of Learning Management System (LMS) by 75% and aspects of student understanding in the implementation of online science practicum using Microsoft Teams by 75%. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

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Social Network Extraction Unsupervised

arXiv

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arXiv 2022年

作者： Nasution, Mahyuddin K.M. Syah, Rahmad Information Technology Study Program FakultasIlmuKomputer dan TeknologiInformasi Universitas Sumatera Utara Medan20155 Indonesia Informatics Department Universitas Medan Area Medan Indonesia

In the era of information technology, the two developing sides are data science and artificial intelligence. In terms of scientific data, one of the tasks is the extraction of social networks from information sources that have the nature of big data. Meanwhile, in terms of artificial intelligence, the presence of contradictory methods has an impact on knowledge. This article describes an unsupervised as a stream of methods for extracting social networks from information sources. There are a variety of possible approaches and strategies to superficial methods as a starting concept. Each method has its advantages, but in general, it contributes to the integration of each other, namely simplifying, enriching, and emphasizing the *** Codes 1.2.7 © 2022, CC0.

关键词： Big data

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Benchmarking A New Dataset for Coffee Bean Defects Classification Based on SNI 01-2907-2008

Benchmarking A New Dataset for Coffee Bean Defects Classific...

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Information Technology Research and Innovation (ICITRI), International Conference on

作者： Made Windu Antara Kesiman Ismail Sulaiman I Made Dendi Maysanjaya Kadek Teguh Dermawan Dept. of Informatics Engineering Virtual Vision Image and Pattern Research Group Universitas Pendidikan Ganesha Bali Indonesia Program Study Teknologi Hasil Pertanian Faculty of Agriculture Universitas Syiah Kuala Banda Aceh Indonesia

To develop a device which can determine automatically the quality of coffee beans, the module to identify and classify coffee bean defects based on digital images processing is needed. For this reason, a new dataset of coffee bean defect images is built in this research. 3 classes were defined and obtained from the image sample of coffee beans, namely good coffee beans, defective coffee beans, and non-valid coffee beans. Moreover, specifically for the class of defective coffee beans, the new dataset also provides ground truth image samples for 17 classes of coffee bean with defects which was defined by SNI 01-2907-2008. Two Convolutional Neural Network (CNN) architecture models, InceptionResnetV2 and MobileNet, were tested to do an initial benchmarking process to classify coffee beans and their types of defects. Both architectures show very promising results to classify coffee bean images in 3-classes. With 92.52% of accuracy, MobileNet outperforms slightly InceptionResnetV2. Both architectures are fairly easy to classify the 3-classes of coffee bean images. But the experimental results indicate that the task of classifying more specifically the 17 classes of different types of defects in coffee beans is still quite difficult. Although the accuracy of InceptionResnetV2 of 53.35% seems much higher than the accuracy of MobileNet, the two architectures still seem to be struggling to identify each type of coffee bean defect. This benchmarking results will serve as the initial basis that helps to analyze the level of complexity of problems in the coffee bean new dataset, as well as the basis for further investigations and research processes to improve the performance of the future coffee bean classifier machine.

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Biomedical Image Quality Improvement with Spatial Domains 2

Biomedical Image Quality Improvement with Spatial Domains

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2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Fernando, Erick Siagian, Pandapotan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia

ISBN: (纸本)9781728197463

Digital image processing aims to improve the quality of an original image so that it can display an image that is relatively better than the original image, so as to obtain the detailed information needed for an analysis need. Quality degradation Biomedical images in computerization usually experience changes in brightness, blur, and contrast stretching. Because of the deterioration in the image quality, doctors and patients cannot obtain the information needed for analysis, therefore the need for biomedical image processing techniques with spatial domain methods to improve the quality and details of information in the image so that it helps doctors in diagnosing. Data analysis is biomedical images like X-ray images, CT-Scan (Computer Tomographic Scan) images, and USG (Ultrasound Graphic) images. A focused study on improving image quality can be done with digital spatial domain image processing techniques. Digital domain image processing is digital image processing based on the manipulation of pixel values in the image directly, in the form of point processing and mask processing. Process testing for each image for Blur level is CT-scan images with a value of 0.98436, ultrasound images with a value of 0.9875, X-ray images with a value of 0.9836. This value is blur level value get near to 1 which means the image becomes clearer. The analysis results prove that the spatial domain method can clarify the object image in this study. The biomedical image quality processing model is proven to be able to improve the quality of the image that is declining due to the digitization process and assist the user in analyzing the biomedical image. © 2021 IEEE.

关键词： Image quality

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm

Image Processing Implementation to Classify Coffee Fruit Rip...

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International Conference on Information Management and Technology (ICIMTech)

作者： M. Farhan Hussaini Dermawan Deden Witarsyah Dedy Syamsuar Hanif Fakhrurroja Ahmad Luthfi Muhammad Izman Herdiansyah Faculty of Industrial Engineering Telkom University Bandung Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Industrial Technology Islamic University of Indonesia Jogjakarta Indonesia Informatics Study Program Faculty of Science and Technology Universitas Bina Darma Palembang Indonesia

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level.

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