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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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Comparison heuristics method for solving two echelon vehicle routing problem

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AIP Conference Proceedings 2024年第1期3029卷

作者： Muhammad Khahfi Zuhanda Saib Suwilo Opim Salim Sitompul Mardiningsih Informatics Engineering Study Program Faculty Engineering Universitas Medan Area Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Today, almost everyone has done online shopping activities. The presence of e-commerce makes it easier for humans to do shopping. E-commerce companies compete to provide the best service to the community. One of them is in the delivery within the city. In terms of city delivery, the 2E-VRP model has been discussed a lot lately in terms of consolidating shipments. This study aims to present the 2E-VRP mathematical model and work in two stages to find a solution. In this article, the author also compares solutions with several heuristic models including 2-opt, repetitive nearest neighbor, nearest neighbor, farthest insertion, cheapest insertion, arbitrary insertion, and nearest insertion. From the results of research conducted by the 2-opt method, farthest insertion, cheapest insertion, and nearest insertion, the total distance is the best, all three get the same distance, then followed by the nearest insertion, arbitrary insertion, and nearest insertion methods.

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Development of coronary heart disease diagnosis system based on facial imagery

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AIP Conference Proceedings 2024年第1期2920卷

作者： Yudha Andriano Rismawan Agung Adi Firdaus Indah Novi Yarman Anisa Dwi Lutfi Yanti Anan Nugroho Rachelia Intan Merdina Andreas Arie Setiawan Informatics and Computer Engineering Education Study Program Universitas Negeri Semarang Semarang Indonesia Public Health Study Program Universitas Negeri Semarang Semarang Indonesia Faculty of Medicine Diponegoro University Semarang Indonesia

The effort of the community in early checkups for coronary heart disease is still very lacking. That is due to the less awareness and cost constraints so that heart disease is handled too late which causes the heart condition to get worse and even complications. A diagnosis of coronary heart risk based on facial texture has been done lately by researchers in China and produces pretty good output, but no similar study has been found in Indonesia. Therefore, this study aims to design several machine learning models and find out the performance of algorithms in diagnosing the risk of coronary heart disease with facial imagery. The research dataset was extracted using the Gray Level Co-occurrence Matrix on specific areas of the face. The areas taken are right crow’s feet, right canthus, bridge nose, forehead, left canthus and left crow’s feet. The main focus of this study was on the performance of the Support Vector Machine, Decision Tree, and Neural Network models. Dataset processing procedures are divided into two, namely model making (training) and performance testing (testing). The findings showed that the best performing model was NN with an AUC score of 92.8%, followed by SVM with 85.6%, and the lowest was DT with 68% AUC. NN became the model with the best performance with 76.9% accuracy, 81.7% precision, 76.9% recall, and an F1 score of 77.5%.

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Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds

Materials Today Quantum

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Materials Today Quantum 2024年 2卷

作者： Muhamad Akrom Supriadi Rustad Hermawan Kresno Dipojono Study Program in Informatics Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung 40132 Indonesia

This work used a variational quantum circuit (VQC) in conjunction with a quantitative structure-property relationship (QSPR) model to completely investigate the corrosion inhibition efficiency (CIE) displayed by pyridine-quinoline compounds acting as corrosion inhibitors. Compared to conventional methods like multilayer perceptron neural networks (MLPNN), the VQC model predicts the CIE more accurately. With a coefficient of determination (R 2 ), root mean square error (RMSE), mean absolute error (MAE), and mean absolute deviation (MAD) values of 0.989, 0.027, 0.024, and 0.019, respectively, VQC performs better. The established VQC model predicts the CIE with outstanding predictive accuracy for four newly synthesized pyrimidine derivative compounds: 1-(4-fluorophenyl)- 3-(4-(pyridin-4-ylmethyl)phenyl)urea (P1) , 1-phenyl-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P2) , 1-(4-methylphenyl)-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P3) , and quaternary ammonium salt dimer (P4) . It generates remarkably high CIE values of 92.87, 94.05, 94.96, and 96.93 for P1, P2, P3, and P4, respectively. With its ability to streamline the testing and production processes for novel anti-corrosion materials, this innovative approach holds the potential to revolutionize the market.

关键词： Variational quantum circuit QSPR Corrosion inhibition Pyridine-quinoline

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The gap values in the profile matching method by fuzzy logic

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

作者： S A Sitepu S Efendi Z Situmorang Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Master Program of Informatics Engineering Faculty of Computer Science and Information Technology Universitas of Sumatera Utara Medan Indonesia. Department of Computer Science Faculty of Computer Science and Information Technology Universitas St. Thomas Medan Indonesia.

In this research, the determination of the appropriate values of Gap for the assessment of promotion criteria of position in an institution / company. In this study the authors use Fuzzy Sugeno logic on the determination of Gap values used in Profile Matching method. Test results of 5 employees obtained the eligibility of promotion with the position of Z* values between in 3.20 to 4.11.

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Deep Learning Methods for Calibrated Photometric Stereo and Beyond

arXiv

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arXiv 2022年

作者： Ju, Yakun Lam, Kin-Man Xie, Wuyuan Zhou, Huiyu Dong, Junyu Shi, Boxin School of Electrical and Electronic Engineering Nanyang Technological University Singapore The Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong The Research Institute for Future Media Computing Shenzhen University Shenzhen China The Department of Informatics University of Leicester Leicester United Kingdom The Faculty of Information Science and Engineering The Institute for Advanced Ocean Study Ocean University of China Qingdao China The National Key Laboratory for Multimedia Information Processing National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing China

Photometric stereo recovers the surface normals of an object from multiple images with varying shading cues, i.e., modeling the relationship between surface orientation and intensity at each pixel. Photometric stereo prevails in superior per-pixel resolution and fine reconstruction details. However, it is a complicated problem because of the non-linear relationship caused by non-Lambertian surface reflectance. Recently, various deep learning methods have shown a powerful ability in the context of photometric stereo against non-Lambertian surfaces. This paper provides a comprehensive review of existing deep learning-based calibrated photometric stereo methods utilizing orthographic cameras and directional light sources. We first analyze these methods from different perspectives, including input processing, supervision, and network architecture. We summarize the performance of deep learning photometric stereo models on the most widely-used benchmark data set. This demonstrates the advanced performance of deep learning-based photometric stereo methods. Finally, we give suggestions and propose future research trends based on the limitations of existing models. Copyright © 2022, The Authors. All rights reserved.

关键词： Light sources

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Optimization of institutional incentives for cooperation in structured populations

arXiv

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arXiv 2023年

作者： Wang, Shengxian Chen, Xiaojie Xiao, Zhilong Szolnoki, Attila Vasconcelos, Vítor V. School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu611731 China Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Institute of Technical Physics and Materials Science Centre for Energy Research P.O. Box 49 BudapestH-1525 Hungary Computational Science Lab Informatics Institute University of Amsterdam Amsterdam1098XH Netherlands Institute for Advanced Study University of Amsterdam Amsterdam1012 GC Netherlands

The application of incentives, such as reward and punishment, is a frequently applied way for promoting cooperation among interacting individuals in structured populations. However, how to properly use the incentives is still a challenging problem for incentive-providing institutions. In particular, since the implementation of incentive is costly, to explore the optimal incentive protocol, which ensures the desired collective goal at a minimal cost, is worthy of study. In this work, we consider the positive and negative incentives respectively for a structured population of individuals whose conflicting interactions are characterized by a prisoner’s dilemma game. We establish an index function for quantifying the cumulative cost during the process of incentive implementation, and theoretically derive the optimal positive and negative incentive protocols for cooperation on regular networks. We find that both types of optimal incentive protocols are identical and time-invariant. Moreover, we compare the optimal rewarding and punishing schemes concerning implementation cost and provide a rigorous basis for the usage of incentives in the game-theoretical framework. We further perform computer simulations to support our theoretical results and explore their robustness for different types of population structures, including regular, random, small-world, and scale-free networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Game theory

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Pool Water Acidity Gauge Using Fuzzy Mamdani Method

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Journal of Physics: Conference Series 2019年第1期1361卷

作者： Abdul Jabbar Lubis Ummul Khair Arnes Sembiring Ade Zulkarnain Dodi Siregar Student Doctor of Philosophy Computer Engineering Universitiy Malaysia Perlis Study Program of Informatics Faculty of Engineering and Computer Science Universitas Harapan Medan Jl. H.M. Jhoni No. 70 C Medan 20217 Indonesia

Swimming pool is one of the means of sports and play that is fun. Swimming pools must also be considered clean. In order to be replaced with new water. The goal is so that pool users are not infected with infectious diseases due to the dirty water inside the pool. The Mamdani method is the most common method when discussing fuzzy methodology. It was Ebrahim Mamdani who first proposed this method in 1975 when building a steam engine and boiler control system. Mamdani uses a collection of IF-THEN rules obtained from experienced operators / experts. Mamdani's work is actually based on the article 'The Father of Fuzzy, Lotfi A. Zadeh: fuzzy algorithms for complex systems and decision processes.

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia computer science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) computer-aided diagnosis (CAD)

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Prototype of Learning Applications for Modern Cryptographic Techniques Using RC4 Algorithms to Support computer Security Courses 1

Prototype of Learning Applications for Modern Cryptographic ...

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1st Workshop on Environmental science, Society, and Technology, WESTECH 2018

作者： Iqbal, Muhammad Nazar, Nasrul Erliana, Cut Ita Irwansyah, Defi Kurniasih, Nuning Susilo, Edi Iskandar, Akbar Suryani, Rini Supriyono Sudarmaji Permana, Erwin Putera Erwinsyah, Alfian Sujinah Haimah Sudarsana, I Ketut Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Departement of Agrotechnology University of Ratu Samban Bengkulu Indonesia Department of Informatics Universitas Malikussaleh Lhokseumawe Indonesia Departement of Agrotechnology Sekolah Tinggi Ilmu Pertanian Rejang Lebong Bengkulu Indonesia Department of Geography Education Universitas Prof. Dr. Hazairin SH. Bengkulu Bengkulu Indonesia Faculty of Computer Sciences Universitas Muhammadiyah Metro Indonesia Department of Elementary School Teacher Education Universitas Nusantara PGRI Kediri Indonesia Faculty of Education and Teacher Training IAIN Sultan Amai Gorontalo Indonesia Faculty of Education University Muhammadiyah of Surabaya Surabaya Indonesia Department of Education Management Universitas Prof. Dr. Hazairin SH.Bengkulu Bengkulu Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Indonesia

The security of information in this global era is increasingly becoming a vital need in various aspects of life. An information will have a higher value when it comes to aspects of business decisions. This study presents a learning application to explain how to secure data using cryptographic techniques. This study aims to design a prototype learning application of cryptographic techniques using algorithm RC4 method. Based on the results of data analysis and after completing the design of RC4 algorithm cryptographic learning software, the authors found this software shows every step and stages of the processes (data input process (Plaintext or Ciphertext string), Key padding process (U), formation process in S-Box table, the Key-Flow formation process (K-keystream), encryption process and decryption process) contained in RC4 algorithm cryptography, so it can help understanding or learning work procedures of algorithms in the cryptographic method. Microsoft Visual Basic 2008 is an IDE (Integrated Development Environment) application that is used to create and develop software. In this application there were various features that facilitate programming such as compilation, debugging, project settings, designing and editing visual interfaces, and so on. © Published under licence by IOP Publishing Ltd.

关键词： Cryptography

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