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Analysis of Decision Tree and Smooth Support Vector Machine Methods on Data Mining

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

作者： Natalina Br Sitepu Sawaluddin M Zarlis Syahril Efendi Hanna Willa Dhany Informatic Engineering Study Program Magister Faculty of Computer Science and Information Technology Universitas Sumatra Utara Medan - Indonesia

This research is about smooth support vector machine (SSVM) and Decision Tree in data mining. Many researchers conduct and develop methods to improve the accuracy and classification of data on good results. This research was conducted by conducting an experiment on STMIK Neumann Medan student data. In this study, it was concluded that Decision Tree performance is better than SSVM, Decision Tree gets very good results that promise to help find the best students to get scholarships. This study is better than SSVM. The training process has a difference of 11.04% and the testing process is 10.08% with each Accuracy.

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Analysis backpropagation methods with neural network for prediction of children's ability in psychomotoric

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Journal of Physics: Conference Series 2018年第1期978卷

作者： F Izhari H W Dhany M Zarlis Sutarman Informatics Engineering Study Program Master Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

A good age in optimizing aspects of development is at the age of 4-6 years, namely with psychomotor development. Psychomotor is broader, more difficult to monitor but has a meaningful value for the child's life because it directly affects his behavior and deeds. Therefore, there is a problem to predict the child's ability level based on psychomotor. This analysis uses backpropagation method analysis with artificial neural network to predict the ability of the child on the psychomotor aspect by generating predictions of the child's ability on psychomotor and testing there is a mean squared error (MSE) value at the end of the training of 0.001. There are 30% of children aged 4-6 years have a good level of psychomotor ability, excellent, less good, and good enough.

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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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Trackable Agent-based Evolution Models at Wafer Scale

arXiv

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arXiv 2024年

作者： Moreno, Matthew Andres Yang, Connor Dolson, Emily Zaman, Luis Department of Ecology and Evolutionary Biology University of Michigan Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data Science University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Department of Computer Science and Engineering Michigan State University East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

Continuing improvements in computing hardware are poised to transform capabilities for in silico modeling of cross-scale phenomena underlying major open questions in evolutionary biology and artificial life, such as transitions in individuality, eco-evolutionary dynamics, and rare evolutionary events. Emerging ML/AI-oriented hardware accelerators, like the 850,000 processor Cerebras Wafer Scale Engine (WSE), hold particular promise. However, many practical challenges remain in conducting informative evolution experiments that efficiently utilize these platforms’ large processor counts. Here, we focus on the problem of extracting phylogenetic information from agent-based evolution on the WSE platform. This goal drove significant refinements to decentralized in silico phylogenetic tracking, reported here. These improvements yield order-of-magnitude performance improvements. We also present an asynchronous island-based genetic algorithm (GA) framework for WSE hardware. Emulated and on-hardware GA benchmarks with a simple tracking-enabled agent model clock upwards of 1 million generations a minute for population sizes reaching 16 million agents. This pace enables quadrillions of agent replication events a day. We validate phylogenetic reconstructions from these trials and demonstrate their suitability for inference of underlying evolutionary conditions. In particular, we demonstrate extraction, from wafer-scale simulation, of clear phylometric signals that differentiate runs with adaptive dynamics enabled versus disabled. Together, these benchmark and validation trials reflect strong potential for highly scalable agent-based evolution simulation that is both efficient and observable. Developed capabilities will bring entirely new classes of previously intractable research questions within reach, benefiting further explorations within the evolutionary biology and artificial life communities across a variety of emerging high-performance computing platforms. Copyright © 20

关键词： Genetic algorithms

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The Comparative Hybrid Approach to Investigate Cognition across Substrates

The Comparative Hybrid Approach to Investigate Cognition acr...

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2021 Conference on Artificial Life, ALIFE 2021

作者： Albani, Sarah Ackles, Acacia L. Ofria, Charles Bohm, Clifford Department of Neuroscience Michigan State University East LansingMI48823 United States Lyman Briggs College Michigan State University East LansingMI48823 United States Department of Integrative Biology Michigan State University East LansingMI48823 United States Department of Computer Science Michigan State University East LansingMI48823 United States Program in Ecology Evolution and Biology Michigan State University East LansingMI48823 United States BEACON Center for the Study of Evolution in Action Michigan State University East LansingMI48823 United States

Understanding the structure and evolution of cognition is a topic of broad scientific interest. Computational substrates are ideal for conducting investigations into this topic because they can be incorporated in rapidly evolving Artificial Life systems and are easy to manipulate. However, design differences between currently existing digital systems make it difficult to identify which manipulations are responsible for broad patterns in evolved behavior. This is further confounded if we are trying to disentangle how multiple features interact. Here we systematically analyze components from two evolvable digital neural substrates (Recurrent Artificial Neural Networks (RNNs) and Markov brains) to develop a proof-of-concept for a comparative hybrid approach. We identified elements of the logic and memory storage architectures in each substrate, then altered and recombined properties of the original substrates to create hybrid substrates. In particular, we chose to investigate the differences between RNNs and Markov Brains relating to network sparsity, whether memory is discrete or continuous, and the basic logic operator in each substrate. We then tested the original substrates and the hybrids across a suite of distinct environments with different logic and memory requirements. While we observed trends across all three of the axes that we investigated, we identified discreteness of memory as an especially important determinant of performance across our test conditions. However, the specific effect of discretization varied by environment and whether the associated task relied on information integration. Our results demonstrate that the comparative hybrid approach can identify structural components that enable cognition and facilitate task performance across multiple computational structures. © 2021 ALIFE. All Rights Reserved.

关键词： Markov processes

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A Review in E-Learning Context: Gamification Elements for Language Learning

A Review in E-Learning Context: Gamification Elements for La...

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Technology, Engineering, and Computing Applications (ICTECA), International Conference on

作者： Gamal Kusuma Zamahsari Sahrul Romadhon Mufidah Nur Amalia Lailatul Rifah Arti Prihatini Ardi Wina Saputra Digital Language Learning Center Communication Science Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia Indonesian Language Education Study Program Institute of Islamic Religion Madura Pamekasan Indonesia Digital Language Learning Center Computer Science Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia Digital Language Learning Center Visual Communication Design Faculty of Humanities Bina Nusantara University Jakarta Indonesia Indonesian Language Education Faculty of Teacher Training and Education Unversity of Muhammadiyah Malang Malang Indonesia Indonesian Language Education Study Program Widya Mandala Catholic University Surabaya Indonesia

Recent advancements in e-learning have highlighted the significance of incorporating gamification into language acquisition processes. It is essential to examine the application of learning game features within classroom settings. The foremost goal of this systematic review of literature is to ascertain and thoroughly delineate the elements of gamification considered suitable for incorporation into environments for language learning. This investigation focuses on two main objectives: firstly, to examine the influence of diverse elements of gamification on the enhancement of language abilities, and secondly, to comprehend how these elements shape the educational approaches and experiences of students in a gamified learning environment. The review methodology employed in this study is a systematic literature review of the current literature to comprehensively analyze and map out the effective utilization of gamification in the context of language teaching. The results of our study demonstrate that the deliberate integration of game features can have a substantial impact on student motivation and engagement. Nevertheless, the efficacy of these components is contingent upon the individual attributes of students and the educational goals in question. The paper finishes by providing advice for customizing gamification tactics to accommodate the varying learner profiles in language teaching. Additionally, it suggests potential areas of future research that can contribute to the ongoing development and enhancement of this pedagogical approach.

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Classification Of Aedes Mosquito Larva Using Convolutional Neural Networks And Extreme Learning Machine

Classification Of Aedes Mosquito Larva Using Convolutional N...

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International Conference on Electrical, Telecommunication and computer Engineering (ELTICOM)

作者： Pauzi Ibrahim Nainggolan Syahril Efendi Mohammad Andri Budiman Maya Silvi Lydia Ivan Joshua Dhani Syahputra Bukit Romi Fadillah Rahmat Ledy Afrida Sinaga Edi Subroto Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Information Technology Universitas Sumatera Utara Medan Indonesia Department of Public Health Universitas Sumatera Utara Medan Indonesia Environmental health and diseases control Ministry of Health Medan Indonesia Department of midwifery study program STIKes Mitra Husada Medan Sumatera Utara Indonesia

The spread of diseases transmitted by Aedes mosquitoes, such as Dengue fever, Chikungunya (CHIKV), and Zika, poses a severe health problem in many countries. Aedes mosquitoes can be found in tropical and subtropical areas. One method to control the diseases is by controlling the population of Aedes mosquitoes, and one way to control the population of Aedes mosquito is by exterminating Aedes mosquito larvae. Identifying mosquito larvae, however, demands a considerable amount of effort, time, and specialized knowledge about the morphology and anatomy of mosquito larvae to accurately classify the various types. Therefore, a system is needed to classify Aedes and non-Aedes mosquito larvae. In this study, classification was carried out using larvae images taken using a digital microscope. The methods used to classify mosquito larvae images are Convolutional Neural Networks (CNN) to extract features from the larvae image and Extreme Learning Machine (ELM) to classify the larvae image. The result obtained from evaluating the CNN-ELM model is an accuracy of 98%, f1-score of 99% for Aedes larvae, and fl-score of 96% for non-Aedes larvae.

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A Systematic Review in Educational Settings: Numerous Challenges to the Adoption of Augmented Reality

A Systematic Review in Educational Settings: Numerous Challe...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Gamal Kusuma Zamahsari Mufidah Nur Amalia Lailatul Rifah Frihandhika Permana Sahrul Romadhon Arti Prihatini CommunicationScience Department Faculty of Humanities Digital Language Learning Center Bina Nusantara University Jakarta Indonesia Faculty of Humanities Digital Language Learning Center Visual Communication Design Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Indonesian Language Education Study Program Institute of Islamic Religion Madura Pamekasan Indonesia Indonesian Language Education Faculty of Teacher Training and Education University of Muhammadiyah Malang Malang Indonesia

The integration of augmented reality has shown to be a successful implementation within the fields of education. The resultant positive impact is highly beneficial and introduces a novel dimension to the realm of education. Nevertheless, the advancement of technology and the evolving demands of education present inherent challenges that must be confronted. This study's main goal is to provide a thorough examination of the difficulties faced when implementing augmented reality (AR) technology in educational settings. This study involves an extensive review of literature focusing on the integration of augmented reality (AR) into educational contexts. Nevertheless, the availability of literature source databases remains constrained. Another researcher has asserted that this study aims to address the limitations previously discussed. The objective of this study is to adequately rectify the limitations. The bibliometric review was carried out utilizing analytical techniques offered by Scopus, while the viewing of bibliometric data was performed employing the Vos viewer application. The findings indicate that there exist multiple factors that stakeholders ought to consider while employing augmented reality within educational contexts. The field of augmented reality (AR) encompasses four separate challenges, namely technological complexities, user-related considerations, AR content creation, and the need for curriculum adjustments to meet the learning demands associated with AR integration.

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Development of e-tracer study at faculty of mathematics and natural science, State University of Jakarta, Indonesia

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AIP Conference Proceedings 2024年第1期2982卷

作者： Ellis Salsabila Fariani Hermin Agus Agung Permana Mathematics Education Study Program Faculty of Mathematics and Natural Sciences Universitas Negeri Jakarta Jakarta Indonesia Computer Science Study Program Faculty of Mathematics and Natural Sciences Universitas Negeri Jakarta Jakarta Indonesia

Alumni or college graduates have an essential role in their respective universities in establishing cooperation with various agencies. Therefore, the role of alumni can be optimized if the university has alumni data on an ongoing basis. Alumni data tracing is a Tracer study conducted in the Faculty of Mathematics and Natural sciences, State University of Jakarta, Indonesia, which provides information on an alumnus data. Data collecting has been done using the online form method, namely Microsoft Forms. However, in reality, it is less effective because the data cannot be updated and the data management cannot be appropriately managed. This research is an innovation in searching and managing the alumni data in the form of a Tracer study information system. The system development model uses the Spiral Model since it is flexible and possible to make changes throughout the software development life cycle to accommodate any needed alterations.

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Ecology, Spatial Structure, and Selection Pressure Induce Strong Signatures in Phylogenetic Structure

arXiv

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arXiv 2024年

作者： Moreno, Matthew Andres Rodriguez-Papa, Santiago Dolson, Emily Department of Ecology and Evolutionary Biology University of Michigan Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data Science University of Michigan Ann Arbor United States Department of Computer Science and Engineering Michigan State University East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution, and have been hypothesized to influence phylogenetic structure. For instance, they can help explain natural history, steer behavior of contemporary evolving populations, and influence efficacy of application-oriented evolutionary optimization. Likewise, in inquiry-oriented artificial life systems, these drivers constitute key building blocks for open-ended evolution. Here, we set out to assess (1) if spatial structure, ecology, and selection pressure leave detectable signatures in phylogenetic structure, (2) the extent, in particular, to which ecology can be detected and discerned in the presence of spatial structure, and (3) the extent to which these phylogenetic signatures generalize across evolutionary systems. To this end, we analyze phylogenies generated by manipulating spatial structure, ecology, and selection pressure within three computational models of varied scope and sophistication. We find that selection pressure, spatial structure, and ecology have characteristic effects on phylogenetic metrics, although these effects are complex and not always intuitive. Signatures have some consistency across systems when using equivalent taxonomic unit definitions (e.g., individual, genotype, species). Further, we find that sufficiently strong ecology can be detected in the presence of spatial structure. We also find that, while low-resolution phylogenetic reconstructions can bias some phylogenetic metrics, high-resolution reconstructions recapitulate them faithfully. Although our results suggest potential for evolutionary inference of spatial structure, ecology, and selection pressure through phylogenetic analysis, further methods development is needed to distinguish these drivers' phylometric signatures from each other and to appropriately normalize phylogenetic metrics. With s

关键词： Abiotic

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