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Backpropagation Network Optimization Using One Step Secant (OSS) Algorithm

IOP Conference Series: Materials Science and Engineering 2020年第1期769卷

作者： Solikhun Mochamad Wahyudi M. Safii Muhammad Zarlis Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia. Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

Education is one of the main indicators in national development efforts. The government in its efforts to realize national goals to educate the nation's life has made a policy for compulsory 9-year schools, namely elementary and junior high schools. To find out how many residents use the education facilities provided by the government can be seen through school enrollment rates (SPR). A high School Participation Rate (SPR) means showing greater opportunities to access education in general. This study aims to optimize artificial neural networks with the One Step Secant (OSS) algorithm. Artificial Neural Network (ANN) is part of the artificial intelligence system (Artificial Intelligence, AI) which is one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. The sample data used for optimization is SPR Indonesia data by province. Using 4 architectural models with 5 input variables, 1 shadow layer and 1 output. The best results obtained between architectures 5-4-1, 5-8-1, 5-16-1 and 5-32-1 are architectures 5-16-1. Obtained prediction accuracy comparisons using the One Step Secant (OSS) algorithm and standard algorithms namely 96.97% and 100%. The standard algorithm is superior in accuracy, the One Step Secant (OSS) algorithm is superior in terms of iterations.

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Resilient Algorithm In Predicting Fertilizer Imports by Major Countries

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IOP Conference Series: Materials Science and Engineering 2020年第1期769卷

作者： Solikhun Mochamad Wahyudi M Safii Muhammad Zarlis Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia. Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

In the last five years (2013-2017) Indonesia's fertilizer production experienced volatile growth, but overall tended to increase at a rate of 1.7% per year. The research aims to optimize artificial neural networks with a resilient backpropagation algorithm (Rprop), artificial neural networks are one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. Sample data used for optimization is fertilizer import data according to the main country of origin and uses 4 architectures, the best results are obtained between architectures 6-8-1, 6-12-1, 6-16-1, and 6-32-1 is architecture 6-32-1 with 100% accuracy.

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Perceptron Partition Model to Minimize Input Matrix

Perceptron Partition Model to Minimize Input Matrix

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International Conference on Science and Innovated Engineering 2018, i-COSINE 2018

作者： Azmi, Zulfian Nasution, Mahyuddin K.M. Zarlis, Muhammad. Mawengkang, Herman Efendi, Syahril Postgraduate Doctoral of Computer Science Universitas Sumatera Utara Padang Bulan USU Medan20155 Indonesia Information Technology Department Universitas Sumatera Utara Padang Bulan USU Medan20155 Indonesia Program Pasca Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Indonesia Department of Mathematics Universitas Sumatera Utara Padang BulanUSU Medan20155 Indonesia

Implementation of Neuron Network model using Perceptron has not given optimal result in real time learning. The large number of inputs expressed in matrix form makes the process slower in pattern recognition. So, it takes characteristic to represent all the input matrices by using the partition method. By partitioning each input and with the best weight and using the activation function will produce an output value. And learning is valid in recognizing patterns only 1 iteration only. Further validation is done on the water mill control module with dissolved oxygen input, water pH, salinity and water temperature. With Perceptron Partition learning algorithm more real-time than perceptron model. Testing on the waterwheel input whether rotating or stopping by Matrix Laboratory software simulation. © Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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Dynamic Model for Determining Disaster Evacuation Locations with Game Theory

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： M. Safii Syahril Efendi Muhammad Zarlis Herman Mawengkang Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Faculty of Computer Science and Information Technology Universitas Sumatera Utara Faculty of Math and Science Universitas Sumatera Utara

Disaster management can be grouped into three stages with several activities that can be carried out starting from pre-disaster, during emergency response and post-disaster. In the pre-disaster stage one of which is mitigation, which is a series of efforts to reduce disaster risk, both through physical development and awareness raising and capacity to face the threat of disaster. In mitigation one important factor is about evacuation. Evacuation locations in disaster transportation management are urgently needed for an effective evacuation process. Evacuation location determination is a benchmark in handling evacuation that can minimize the impact of losses from the disaster. To determine the evacuation location dynamically using game theory can solve the problem by providing several alternative locations by showing the dominant factor in the variables in the selection of the evacuation site. Game theory will use pure and mixed strategies to provide the most optimum choice of criteria. With this method will produce a decision support system to determine the optimal evacuation location or safe area in disaster mitigation

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Preventing bad behavior in academia

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四川生理科学杂志 2024年第7期46卷 1615-1615页

作者： Rayane da Cruz Albino Faculty of Pharmacy Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil. Department of Host-Microbe Interactions St. Jude Children’s Research Hospital Memphis TN USA. School of the Environment The University of Queensland Whiterock QLD Australia. KU Leuven Ghent Belgium. Laboratory for Computational Social Systems Indraprastha Institute of Information Technology Delhi New Delhi India. University Medical College Shantou Guangdong China. Department of Ecoscience Aarhus Universitet Aarhus Denmark. Institute of Environment and Sustainable Development Banaras Hindu University Varanasi Uttar Pradesh India. Department of Medical Parasitology Faculty of Medicine and Health Sciences Sana’a University Sana’a Yemen and Tropical Disease Research Center Faculty of Medicine and Health Sciences University of Science and Technology Sana’a Yemen. Department of Medicine University of Montreal Montreal QC Canada. Electricity Infrastructure and Buildings Division Pacific Northwest National Laboratory Portland OR USA. Department of Biological Sciences University of New Brunswick Saint John Saint John NB Canada. Department of Biomedical Engineering The University of Melbourne Melbourne VIC Australia. Vagelos Molecular Life Sciences Program University of Pennsylvania Philadelphia PA USA. Doctoral Program in Neurobiology and Behavior Columbia University New York NY USA. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA. Department of Engineering University of Cambridge Cambridge Cambridgeshire UK. Department of Geography Liverpool John Moores University Liverpool UK. Department of Biology Stanford University Stanford CA USA. Department of Psychology University of Nicosia Nicosia Cyprus. Department of Global Ecology Carnegie Institution for Science Stanford CA USA. Research and Support Division Stellenbosch University Cape Town South Africa.

We gave young scientists this prompt:Describe one change to scientific policy or culture that would substantially decrease incidents of scientific misconduct or other unethical behavior.

关键词： behavior. prompt culture

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Cropping Method on Grayscale Images for Periapical Radiographs of Human Teeth

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IOP Conference Series: Materials Science and Engineering 2020年第1期879卷

作者： Linda Wahyu Widianti Sunny Arief Sudiro Sarifuddin Madenda Johan Harlan Doctoral Student in Information Technology Post Graduate Program Gunadarma University Departement of Information system of STMIK Jakarta STI&K Jl. BRI No. 17 Radio DalamKebayoranBaru Jakarta Selatan Gunadarma University Jakarta Indonesia

This study explains the comparison of techniques for cropping existing in Matlab for graylevel images on periapical radiographs of human teeth. Some cropping techniques in Matlab are rectangular crop, square crop, circular crop, ellipse crop, polygon crop. This research will explain how each existing cropping technique will give different results based on their respective shapes. So that eventually will produce the most appropriate cropping techniques among several existing cropping techniques in mathlab. The five cropping techniques that have been mentioned here where the four existing cropping techniques namely rectangular crop, square crop, circular crop, ellipse crop still carry other objects that are not needed in research, so it is not appropriate to be used for research objects that have irregular shapes. Appropriate cropping technique is polygon cropping because it is able to identify research objects that have irregular shapes.

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Classification of Land Cover from Sentinel-2 Imagery Using Supervised Classification Technique (Preliminary Study)

Classification of Land Cover from Sentinel-2 Imagery Using S...

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International Conference on information Management and technology (ICIMTech)

作者： Eka Miranda Achmad Benny Mutiara Ernastuti Wahvu Catur Wibowo Information Systems Department Doctoral Program in Information Technology Gunadarma University Jakarta Indonesia Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Computer Science Faculty Universitas Jakarta Indonesia

This paper intended to classify land cover of high-resolution satellite image using supervised classification method. The object of this research was the land cover image of the central java area in Indonesia which chosen as an area observed with the cloud cover consideration. The Satellite image was obtained from Sentinel-2 through https://***. Supervised Classification and ArcMap 10.5 was used to classified image object. This research classified the land cover into four classifications class namely Water, Forest, Urban and Bare Land due to show the main classes in the Land Cover Classification of RSNI-l National Standardization Body of Indonesia, RSNI-l was used as reference for classification process. The confusion matrix used to calculate classification accuracy value. Subsequently, confusion matrix results compared to the truth information. The truth information was derived from the actual value of RASTERVALUE obtained from Google Earth. This research shown supervised classification maximum-likelihood classification has been classified land cover into four class (forest, water body, urban and bare land) with overall accuracy = 1 and kappa value = 0.4896. This result showed this research got moderate kappa accuracy value but high overall accuracy value. High accuracy value reached due to fully supervised experiment during classification process.

关键词： Satellites Forestry Training Java Probability Standardization Vegetation mapping

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Author Correction: Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis

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Nature communications 2023年第1期14卷 6540页

作者： Hitomi Takada Yohei Sasagawa Mika Yoshimura Kaori Tanaka Yoshimi Iwayama Tetsutaro Hayashi Ayako Isomura-Matoba Itoshi Nikaido Akira Kurisaki Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan. Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan. Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan. Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan. itoshi.nikaido@riken.jp. Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan. itoshi.nikaido@riken.jp. Master's/Doctoral Program in Life Science Innovation (Bioinformatics) Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan. itoshi.nikaido@riken.jp. Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan. akikuri@bs.naist.jp.

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Food Self-sufficiency Decision Support Model Based on Provinces in Indonesia Using the Clustering Method

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

作者： M. Safii Mochamad Wahyudi Solikhun Muhammad Zarlis Syahril Effendi Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

In Indonesia rice is a staple food as a major source of carbohydrates. Rice is also a staple food of the people of most countries in Asia and even most of the population in the world. Food security for Indonesia is closely linked to the adequacy of rice provision. The indicators of national food security are (1) the availability of food every time; (2) the ability or purchasing power of the people towards food; (3) guarantee of distribution and supply of food; and (4) the ability to import in urgent conditions. Rice as a rice-producing crop is a very important commodity for Indonesia, besides being the main food producer, rice commodity is also the main source of income from millions of farmers. The availability of rice at affordable prices to communities is an important factor for national security, security and stability. Indonesia has a large population, the fourth largest in the world after China, America and India. Dependence on rice imports has a high risk not only of food dependency on other countries, but also limited availability of rice in the international market. In 1977 Indonesia imported 2 million tons of rice and accounted for one third of the rice available on the international market, affecting the price of rice. Increased rice production can be achieved through increased productivity with the application of technology varieties and better cultivation and expansion of planting areas with increased intensity of planting and printing or opening of new rice cultivation area. Based on the above explanation, the researcher uses Data Mining Clustering with K-Means to get the assessment result of all rice production provinces. With this method the results of the research can be used as a model of decision makers for the government to give priority attention to areas that have the potential to increase rice production.

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Evaluation of Maturity Level of information and Communication technology (ICT) Governance with CobIT 5.0 Case Study: STMIK Pelita Nusantara Medan

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Journal of Physics: Conference Series 2019年第1期1255卷 012046-012046页

作者： Sihotang, Hengki Tamando Efendi, Syahril Jollyta, Deny Husain Zarlis, M Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia

In entering competition the quality and predicate best the national and the quality of graduates, college trying to use information technology as an instrument for might win this competition. That IT can be used to fulfill and support the system in college, it needs assessment from information technology regularly. One method of conducting evaluation of the performance of the department of information technology is to use the framework Cobit 5 as yardstick efficiency in the use of information technology currently consisting of 5 (five) domain namely: EDM, APO, DSS, MEA A measuring instrument his as. With this method, researchers trying to make it a blueprint as the end result of utilization of information technology in college, so the management can plan exactly how of development of information technologies company to the next few years. An evaluation, known level capabilities inside the area mea and APO is entirely located at the level of 1 (performed) with the level of the target to be achieved is the level of 3 (established). Weakness governance information technology in STMIK Pelita Nusantara Medan is the lack of formalization rules and procedures management information technology. To reduce the gap between capability the current level was level and capability to be achieved, so STMIK Pelita Nusantara Medan must meet PA2.1, PA2.2, PA3.1 and PA3.2, that capability the current level was that is at the level of 1 could rise to the level of 3. Along with that, STMIK Pelita Nusantara Medan moved closer to the purpose..

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