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Assessment of ripeness analysis of information technology supervision on DS and ME domains using COBIT 4.1 in the information engineering department of Musamus Merauke

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IOP Conference Series: Earth and Environmental Science 2019年第1期343卷

作者： A Prayitno T K Rahayu L Sumaryanti A Efendi Department of Informatics Universitas Musamus Merauke Indonesia Civil Engineering Study Program Universitas Muhammadiyah Buton Indonesia

Information technology plays an essential role in the business world because it may affect the operations of the organization within the organization that also uses information technology to provide information. One of the departments that use information technology is the Information engineering Department of Musamus Merauke University, which is used to provide information related to the Department of Information engineering. But in the use of information technology is still flawed. Therefore, it is necessary to have a standard in information technology management to measure overall standards and governance in information technology management, ie using COBIT. Based on this study, we will design an information technology management model for the Department of Information engineering. Control objectives for information and related technologies (COBIT) are 4 (4) primary domains, including domains, planning, and organization (PO), acquisition and implementation (AI), transmission and support (DS) and tracking. And evaluating (ME) in research. This will use two domains, namely the delivery domain and support (DS) and monitoring and evaluation (ME) by adjusting the problems and requirements of the information engineering department in the arrangement. Information technology support for information technology service processes and support for monitoring and evaluation of information technology, the results showed that the level of maturity of information technology supervision in the information engineering department is at level 2. Therefore, information technology in the engineering department Information must be updated to the expected level.

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Testing Real-Time Applications on Windows 10 IOT Using the Nyquist Theory

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： Zulfahmi Syahputa M. Zarlis Beny B. Nasution Informatics Engineering Study Program Magister Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia

Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT.

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Scientific discovery in the age of artificial intelligence

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NATURE 2023年第7978期621卷 E33-E33页

作者： Wang, Hanchen Fu, Tianfan Du, Yuanqi Gao, Wenhao Huang, Kexin Liu, Ziming Chandak, Payal Liu, Shengchao Van Katwyk, Peter Deac, Andreea Anandkumar, Anima Bergen, Karianne Gomes, Carla P. Ho, Shirley Kohli, Pushmeet Lasenby, Joan Leskovec, Jure Liu, Tie-Yan Manrai, Arjun Marks, Debora Ramsundar, Bharath Song, Le Sun, Jimeng Tang, Jian Velickovic, Petar Welling, Max Zhang, Linfeng Coley, Connor W. Bengio, Yoshua Zitnik, Marinka Department of Engineering University of Cambridge Cambridge UK Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA NVIDIA Santa Clara CA USA Department of Computational Science and Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Science Cornell University Ithaca NY USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Stanford University Stanford CA USA Department of Physics Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Mila – Quebec AI Institute Montreal Quebec Canada Université de Montréal Montreal Quebec Canada HEC Montréal Montreal Quebec Canada CIFAR AI Chair Toronto Ontario Canada Department of Earth Environmental and Planetary Sciences Brown University Providence RI USA Data Science Institute Brown University Providence RI USA Center for Computational Astrophysics Flatiron Institute New York NY USA Department of Astrophysical Sciences Princeton University Princeton NJ USA Department of Physics Carnegie Mellon University Pittsburgh PA USA Department of Physics and Center for Data Science New York University New York NY USA Google DeepMind London UK Department of Computer Science and Technology University of Cambridge Cambridge UK Microsoft Research Beijing China Department of Biomedical Informatics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Harvard Data Science Initiative Cambridge MA USA Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Cambridge MA USA Department of Systems Biology Harvard Medical School Boston MA USA Deep Forest Sciences Palo Alto CA USA BioMap Beijing China Mo

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The Implementation of Fuzzy Multiple Attribute Decision Making by Using Weighted Product Algorithm in Evaluating Employees' Performance

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： Herlina Latipa Sari Toibah Umi Kalsum Desi Mahdalena Informatics engineering study program of Dehasen University Bengkulu Meranti Raya street No. 32 Sawah Lebar Bengkulu city

Fuzzy Logic used as an act to describe problem from input into expected output. One part of Fuzzy logic is Fuzzy multiple attribute decision making in deciding weighted alternative Score and importance criteria rating meanwhile Weighted product method is to evaluate so in deciding employee performance by multiplying to correlate with attribute rating, rating for each attribute must be powered by number with related weighted attribute and that process is same with normalization process. The result of implementation of Multiple Attribute Decision Making (FMADM) by using Weighted Product (WP) Algorithm in valuating employee performance which conducted once a year which obtained from performance valuation of system valuation at CV. Mulya Karya Baru. By conducting sample from data which obtained from data. This research can create and develop an application which can help user to rank the employee performance.

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Classification of teak wood production in Central Java using the C5.0 algorithm

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AIP Conference Proceedings 2019年第1期2202卷

作者： Yuliana Susanti Respatiwulan Sri Sulistijowati Handajani Hasih Pratiwi Isnandar Slamet Hartatik Firstiana Istiqomah 1Program Study of Statistics Universitas Sebelas Maret Indonesia 2Diploma Program of Informatics Engineering Universitas Sebelas Maret Surakarta Indonesia

Central Java has the largest teak land area in Java Island. It is about two-thirds of teak land area on Java Island is located in Central Java. The purpose of this study is to determine the classification of factors that influence the production of teak trees in Central Java with the Commercial Version 5.0 (C5.0) algorithm. This algorithm is a refinement of the ID3 and C4.5 algorithms. The C5.0 algorithm works by separating samples based on attributes that have the highest information gain. The results of the study show that there are three classification rules produced with an 81.8% accuracy rate.

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Design of Hexapod Robot Movement Based on Arduino Mega 2560

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Journal of Physics: Conference Series 2019年第1期1165卷

作者： K U Ariawan G S Santyadiputra I W Sutaya Electronics Engineering Study Program Technical and Vocational Faculty Universitas Pendidikan Ganesha Informatics Engineering Education Departement Technical and Vocational Faculty Universitas Pendidikan Ganesha

This study aims to design the movement of the hexapod robot so that it can move straight forward, turn 90 degrees forward, and move forward 180 degrees by applying the tripod gait method to produce a maximum movement pattern. The robot control system uses Arduino Mega 2560 to control the motion of 18 servo motors through the I2C interface servo motor driver - PCA9685. In straight forward motion testing, an average velocity of 6 cm/s was obtained, 90 degree forward motion testing obtained an average speed of 18 degrees/s, while the 180 degree rotational forward motion test also obtained an average speed of 18 degrees/s.

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Remote Chlorophyll-a and SST to Determination of Fish Potential Area in Makassar Strait Waters Using MODIS Satellite Data

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IOP Conference Series: Earth and Environmental Science 2019年第1期270卷

作者： A Selao A A Malik F I Yani A Mallawa Safruddin Informatics Faculty of Engineering Muhammadiyah University of Parepare Study Program of Aquaculture Faculty of Agriculture Animal Husbandry and Fishery Muhammadiyah University of Parepare Study Program of Aquatic Resource Utilization Faculty of Marine Science and Fishery Hasanuddin University

The objective of this research was to analyze integrated geospatial data using MODIS Satellite data and field data observation to the determination of potential fish area. This study applied in Makassar Strait 118° 0' 0' E-119° 37' 0' E, 3°0'0' S – 4°45'0' S. The methods of this research was conducted using MODIS combine the depth of map waters survey direct interviews and people who participate in fishing activities monthly in January, February, March, April, May, and June. Data were analyzed by using software: Statistics, SeaDas, ENVI, and GIS. The result showed that the horizontal distribution of sea surface temperature (SST) spread evenly or divergent. The distribution of sea temperature in the coastal area was relatively warm in the sea around Barru and Pangkep was ranged 31 to 32 °C. Sea surface temperature dominates in the range of 30 - 31°C. SST correlation coefficient was 0.79 between MODIS and value of observation field data.

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Retracted: Sylabus and Matrials Design for Vocational Student and Its Dissemination Using Website

Retracted: Sylabus and Matrials Design for Vocational Studen...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Harahap, Astro Julida Ongko, Erianto Manurung, Hotler Kurnia, Dian Hartono, H. Abdullah, Dahlan Erliana, Cut Ita Djanggih, Hardianto Saddhono, Kundharu Rianita, Dian Setiawan, Muhammad Ikhsan Setiawan, Yuliyanto Budi Manurung, Rosida Tiurma Sriadhi, S. Sinurat, Mangasi Siregar, Aisyah Soni Hutauruk, Rapat Piter Sibarani, Nico Benjamain Department of Informatics Akademi Teknologi Industri Immanuel Medan Indonesia Department of Computer Systems Universitas Pancabudi Medan Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Law Universitas Tompotika Luwuk Banggai Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Administration University of Lancang Kuning Pekanbaru Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia Study Program of Communication Studies Universitas Semarang Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia STIE Bina Karya Tebing Tinggi Indonesia

The learners' needs are an important factor in designing syllabus and materials design, this research deals with the syllabus and material design based on the professional's needs. It is expected that the syllabus and materials designes are communicatively applicable to the professional academy. Descriptive method is applied in this research. The sample of this research is 30 students of ATII Immanuel Academy Medan. They were selected by random sampling to get the data, the questioners were administered to students. the questioners consisted of 54 items and the semi structured interview consisted of 5 questions, the finding indicated that learners' needs were focused on reading and speaking skills. With reference appropriately and proportionally derived for students of the Professional Academy. Further on the basis of the syllabus, materials are designed in which the skills of using language become a priority. The results of this research will be disseminated using the website. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Face recognition system using Viola Jones, histograms of oriented gradients and multi-class support vector machine

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Journal of Physics: Conference Series 2019年第4期1341卷

作者： M Arafah A Achmad Indrabayu I S Areni Doctoral Student of Electrical Engineering Department Hasanuddin University Makassar Indonesia Informatics Study Program STMIK AKBA Makassar Indonesia Department of Electrical Engineering Hasanuddin University Makassar Indonesia Department of Informatics Hasanuddin University Makassar Indonesia

This study aims to determine the best distance to install a CCTV camera in identifying a person's face in the passenger inspection area at the airport, which can be developed for suspect detection systems. The training data used is in the form of an image with five different angles per person, while the testing data is in the form of video. The initial stage conducted is face detection based on local features (a pair of eyes, nose, and mouth) in the input data using the Viola-Jones method. The face detection results process with pre-processing, feature extraction, and classification. In the pre-processing stage, the Brightness Enhancement (BE), Grayscale and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are used to improve the quality of the detected face. Furthermore, the feature extraction and classification stages use the Histogram of Oriented Gradient (HOG) and the Multi-class Support Vector Machine (MSVM) methods, respectively. The result shows that the best accuracy obtained is 86.76% for a CCTV camera distance of 300 cm and a height of 250 cm.

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