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Design of big data technology prototype for classification of village status based on village development index involves k-means algorithm to support village ministry Pdtt work programs 2

Design of big data technology prototype for classification o...

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2nd International Conference on sciences and Technology Applications, ICOSTA 2020

作者： Hasugian, Paska Marto Hutahaean, Harvei Desmon Sinaga, Bosker Sriadhi Silaban, Saronom Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan20221 Indonesia Departement of Chemistry Universitas Negeri Medan Medan20221 Indonesia

Big data technology is the overall technology that can handle the processing associated with analyzing the data to explore the potential that is in it. Some of the uses of big data are based on the biggest data traffic sources, such as social media, financial transactions, public data, censorship data, and company data. The problem found in the accumulation of village status data that has not been utilized in the decision-making process to determine the status of the next village and the absence of an application to process the data stored in the data database so that a tool is developed to analyze the buildup. The results of this study are to produce a prototype design that is Unified Modeling Language (UML) design, Form Design, and Database Design that will be used to develop Big Data Technology in determining the classification of village status based on the Village Build index. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Review the Utilization of Big Data and K-Means Algorithm in Supporting the Determination of Village Status As Support to the Ministry of Village PDTT 2

Review the Utilization of Big Data and K-Means Algorithm in ...

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2nd International Conference on sciences and Technology Applications, ICOSTA 2020

Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sectors. Big data technology is the whole technology that can handle Big Data. Some of the uses of big data are based on the largest significant data traffic sources such as social media, financial transactions, public data, sensor data, and corporate data. The same is the case with the status of so many villages in Indonesia, so it is better to use big data for the classification of village status based on the village index build by involving an algorithm process. This research aims to produce a description of the role of big data in supporting activities in a grouping. The method used is a qualitative approach related to data collection based on scientific work with the source of data information needed to study literature techniques from various studies that have been published in national and international journals. A decision is made that big data has been widely used in different circles to facilitate performance and speed up the decision-making process. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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Selectivity of CO_(2)reduction reaction to CO on the graphitic edge active sites of Fe-single-atom and dual-atom catalysts:A combined DFT and microkinetic modeling

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Carbon Resources Conversion 2024年第1期7卷 21-31页

作者： Ahmad Nuruddin Adhitya Gandaryus Saputro Arifin Luthfi Maulana Febdian Rusydi Fiki Taufik Akbar Hadi Teguh Yudistira Hermawan Kresno Dipojono Advanced Functional Materials Research Group Faculty of Industrial TechnologyInstitut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Research Center for Nanosciences and Nanotechnology Institut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Research Center for Quantum Engineering Design Department of PhysicsFaculty of Science and TechnologyUniversitas AirlanggaSurabaya 60115Indonesia Theoretical High Energy Physics Research Division Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Mechanical Engineering Study Program Institut Teknologi Sumatera(ITERA)South LampungLampungIndonesia Department of Materials Science and Engineering University of CaliforniaBerkeleyBerkeleyCA 94720United States

We study the carbon dioxide reduction reaction(CO_(2)RR)activity and selectivity of Fe single-atom catalyst(Fe-SAC)and Fe dual-atom catalyst(Fe-DAC)active sites at the interior of graphene and the edges of graphitic nanopore by using a combination of DFT calculations and microkinetic *** trend of limiting potentials for CO_(2)RR to produce CO can be described by using either the adsorption energy of COOH,CO,or their ***_(2)RR process with reasonable reaction rates can be achieved only on the active site configurations with weak tendencies toward CO *** efficiency of CO_(2)RR on a catalyst depends on its ability to suppress the parasitic hydrogen evolution reaction(HER),which is directly related to the behavior of H adsorption on the catalyst’s active *** find that the edges of the graphitic nanopore can act as potential adsorption sites for an H atom,and in some cases,the edge site can bind the H atom much stronger than the main Fe *** linear scaling between CO and H adsorptions is broken if this condition is *** condition also allows some edge active site configurations to have their CO_(2)RR limiting potential lower than the HER process favoring CO production over H2 production.

关键词： CO_(2)RR FexNy active site Fe-SAC Fe-DAC Graphitic edges DFT Microkinetic

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Jasmine Iswarini Dyah Prabandari Christy Atika Sari Eko Hari Rachmawanto Candra Irawan Bilal R. Altamer Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems University of Dian Nuswantoro Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq Department of Computer Science National University of Science and Technology DhiQar Iraq

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant.

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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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Challenges on Cloud Computing Migration Strategy for Music Industry: A Systematic Literature Review

Challenges on Cloud Computing Migration Strategy for Music I...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Hijir Della Wirasti Henki Seta Deden Witarsyah Hamonagan K Prabu Ayu Azzahro Bayu Hananto Faculty of Engineering Industry Telkom University Bandung Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Veteran Jakarta

Cloud computing has emerged as a transformative technology that offers numerous benefits to various industries, including the music industry. Cloud computing has revolutionized the way businesses operate and has had a significant impact on various industries, including the music industry Cloud computing, with its scalability, flexibility, and cost-effectiveness, presents an opportunity for the music industry to leverage technology to enhance its operations and meet the evolving demands of the digital era. This paper presents a systematic literature review on cloud computing migration strategies specifically tailored for the music industry. The review aims to identify existing research, frameworks, and best practices related to cloud migration in the music industry, as well as highlight the challenges and opportunities associated with such migrations. Through an analysis of relevant literature, this study provides valuable insights to assist music industry stakeholders in developing effective cloud migration strategies.

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An ultra thin,bright,and sensitive interactive tactile display based on organic mechanoluminescence for dual-mode handwriting identification

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InfoMat 2024年第6期6卷 76-87页

作者： Tingting Hou Wenlang Li Haoyu Wang Yuantian Zheng Chaojie Chen Haoran Zhang Kai Chen Huilin Xie Xin Li Shaoshuai He Siwei Zhang Dengfeng Peng Cheng Yang Jacky W.Y.Lam Ben Zhong Tang Yunlong Zi Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kongthe People's Republic of China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong Kongthe People's Republic of China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenthe People's Republic of China Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)Guangzhouthe People's Republic of China The Hong Kong University of Science and Technology Interdisciplinary Program Office Hong Kong SARthe People's Republic of China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenthe People's Republic of China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenthe People's Republic of China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhenthe People's Republic of China Guangzhou HKUST Fok Ying Tung Research Institute Guangzhouthe People's Republic of China

Visible light-based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users ***,many inorganic mechanoluminescent(ML)materials-based interactive media,typically ZnS-loaded phosphors(ZLPs),have been successfully ***,organic ML materials-based solutions were rarely exploited despite their huge merits of strong structural modification,abundant luminescence property,low cost,easy preparation,and so ***,we propose a novel interactive tactile display(ITD)based on organic ML materials(Cz-A6-dye)and triboelectric nanogenerator,with ultra-brightness(130%enhancement)and ultra-low threshold pressure(57%reduction)as compared to *** proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously,without extra power ***,the relationship between the luminous performance of organic ML materials and mechanical force is quantified,benefiting from the uniform ML layer *** by convolutional neural networks,the high-accuracy recognition(97.1%)for handwriting and identity of users is realized at the same ***,the ITD has great potential for intelligent wearable electronics and classified military applications.

关键词： interactive media organic mechanoluminescence triboelectric nanogenerators

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Enhanced Dye Adsorption and Bacterial Removal of Magnetic Nanoparticle-Functionalized Bacterial Cellulose Acetate Membranes

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Journal of Renewable Materials 2024年第9期12卷 1605-1624页

作者： Heru Suryanto Daimon Syukri Fredy Kurniawan Uun Yanuhar Joseph Selvi Binoj Sahrul Efendi Fajar Nusantara Jibril Maulana Nico Rahman Caesar Komarudin Komarudin Centre of Advanced Material for Renewable Energy(CAMRY) Universitas Negeri MalangMalang65145Indonesia Department of Mechanical and Industrial Engineering Universitas Negeri MalangMalang65145Indonesia Department of Food and Agricultural Product Technology Faculty of Agricultural TechnologyAndalas UniversityPadang25163Indonesia Department of Chemistry Institut Teknologi Sepuluh NopemberSurabaya60111Indonesia Study Program of Aquatic Resources Management Faculty of Fisheries and Marine ScienceBrawijaya UniversityMalang65145Indonesia Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennai602105India Faculty of Vocational Universitas Negeri MalangMalang65145Indonesia

Utilizing biomass waste as a potential resource for cellulose production holds promise in mitigating environmental *** current study aims to utilize pineapple biowaste extract in producing bacterial cellulose acetate-based membranes with magnetic nanoparticles(Fe_(3)O_(4)nanoparticles)through the fermentation and esterification process and explore its *** bacterial cellulose fibrillation used a high-pressure homogenization procedure,and membranes were developed incorporating 0.25,0.50,0.75,and 1.0 wt.%of Fe3O4 nanoparticles as magnetic nanoparticle for *** membrane characteristics were measured in terms of Scanning Electron Microscope,X-ray diffraction,Fourier Transform Infrared,Vibrating Sample Magnetometer,antibacterial activity,bacterial adhesion and dye adsorption *** results indicated that the surface morphology of membrane changes where the bacterial cellulose acetate surface looks *** crystallinity index of membrane increased from 54.34%to 68.33%,and the functional groups analysis revealed that multiple peak shifts indicated alterations in membrane functional ***,adding Fe_(3)O_(4)-NPs into membrane exhibits paramagnetic behavior,increases tensile strength to 73%,enhances activity against *** and ***,and is successful in removing bacteria from wastewater of the river to 67.4%and increases adsorption for anionic dyes like Congo Red and Acid Orange.

关键词： Bacterial cellulose dye adsorption Fe_(3)O_(4)nanoparticles membrane pineapple waste

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White Bread Mold Detection using K-Means Clustering Based on Grey Level Co-Occurrence Matrix and Region of Interest

White Bread Mold Detection using K-Means Clustering Based on...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Qori Alfatah Putra Christy Atika Sari Eko Hari Rachmawanto Nur Ryan Dwi Cahyo Edy Mulyanto Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Computer Science National University of Science and Technology DhiQar Iraq

This research paper presents a bread mold identification system that utilizes digital image processing techniques, specifically K-means clustering and thresholding, to accurately detect and classify mold-infected areas on bread. The system aims to provide valuable information regarding the safety of consuming mold-contaminated bread, enabling consumers to make informed decisions and reduce the risk of health issues associated with consuming mold-infested bread. the K-means clustering algorithm for mold classification, considering factors such as the number of iterations and the distance metric within the feature space to determine its accuracy. The GLCM feature extraction technique is employed to extract texture information from bread images, encompassing features such as standard deviation (110.62), contrast (1.46), energy, and homogeneity (0.96 and 0.77, respectively). Experimental results demonstrate that the Euclidean Distance yielded the highest result of 72.73, the Cosine Distance obtained the highest result of 8.25, and the City Block Distance obtained the highest result of 92.11. These findings showcase the effectiveness of the system in accurately detecting and classifying mold-infected areas on bread, thereby aiding in ensuring food safety and reducing health risks for consumers.

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Diabetes Prediction Model for Better Clarification by using Machine Learning 6

Diabetes Prediction Model for Better Clarification by using ...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Eben, J. Lysa Jayasudha, R. Ramya, S. Kaliappan, S. Aswal, Shobha Al-Salehi, Khalid Ali Salem Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Tamilnadu Chennai India Department of Mathematics Dr.N.G.P.Institute of Technology Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Tamilnadu Erode India Division of Research and Development Lovely Professional University Punjab Phagwara144411 India School of Computing Graphic Era Hill University Dehradun India Biomedical Engineering Study Program Faculty of Science and Technology Airlangga University Surabaya Indonesia

ISBN: (纸本)9798350398496

Diabetes mellitus is one of the most pressing health concerns because so many people are afflicted by its disabling symptoms. Factors such as age, excess body fat, insufficient physical activity, a history of diabetes in one's family, a sedentary lifestyle, an unhealthy diet, hypertension, etc., all increase the likelihood of developing diabetes mellitus. Health complications are more common in people with diabetes, including cardiovascular disease, renal failure, stroke, blindness, and nerve injury. To validate a diagnosis of diabetes, hospitals typically perform a battery of procedures on the patient. Big data analytics has many vital applications in the healthcare sector. Numerous large computer systems are used in the healthcare sector. With the help of big data analytics, researchers can sift through mountains of data in search of previously unseen patterns and insights. Current techniques have a poor degree of precision in classification and forecast. While previous research has focused on factors such as glucose, body mass index, age, insulin, etc., the proposed model takes these into account and also the other factors that may be more relevant to the development of diabetes. The newer sample is superior to the older one based on categorization accuracy. A workflow algorithm for diabetes prognosis is also required to improve the accuracy. © 2023 IEEE.

关键词： Forecasting

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