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Deep Learning Method Based for Breast Cancer Classification 2

Deep Learning Method Based for Breast Cancer Classification

引用

2nd International Conference on Information technology Research and Innovation, ICITRI 2023

作者： Irmawati Ernawan, Ferda Fakhreldin, Mohammad Saryoko, Andi Universitas Bina Sarana Informatika Fakultas Teknik dan Informatika Indonesia Universiti Malaysia Pahang Faculty of Computing Malaysia Jazan University Faulty of Computer Science and Information Technology Saudi Arabia Universitas Nusa Mandiri Faculty of Information Technology Indonesia

ISBN: (纸本)9798350324945

The most prevalent cancer in women worldwide and one of the main factors in cancer-related mortality is breast cancer. Extensive research efforts have been dedicated to early detection, diagnosis, and treatment of breast cancer to reduce mortality rates. This research aims to achieve accurate diagnosis of breast cancer and classify breast cancer using deep learning method. The study proposes deep learning techniques with Adam's optimization and two hidden layers for breast cancer classification. Addressing challenges such as data instability and overfitting during deep learning training, the research focuses on updating network weights. The experiments examine two hidden layers and varying learning rates to enhance classification accuracy. The datasets utilized in the experiments include the WBCD dataset (Original), the WDBC dataset (Diagnostics), and the Coimbra dataset. Additionally, the proposed scheme's accuracy is compared against existing benchmarks for breast cancer detection. The experimental findings show that the suggested scheme outperforms other benchmarks, achieving an impressive 96% accuracy in breast cancer classification. © 2023 IEEE.

关键词： Diseases

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Comparison of Machine Learning Methods Using Feature Extraction Optimization PCA Method for Identification of Pineapple Maturity Level

Comparison of Machine Learning Methods Using Feature Extract...

引用

2023 International Conference on Information technology and Computing, ICITCOM 2023

作者： Manik, Fuzy Yustika Efendi, Syahril Ginting, Dewi Sartika Harumy, T.H.F. Kana Sahputra, S. Nurhayati Universitas Sumatera Utara Faculty of Computer Science and Information Technology Sumatera Utara Medan Indonesia Universitas Negeri Medan Faculty of Mathematics and Natural Sciences Sumatera Utara Medan Indonesia Universitas Mikroskil Faculty of Informatika Sumatera Utara Medan Indonesia

ISBN: (纸本)9798350359633

Many features are implemented in computer vision and machine learning applications. Because no one knows how a feature affects the classification results of machine learning methods. Therefore, there is a tendency to increase the number of features. However, features may need to be more relevant than some extracted components. In addition, high feature dimensions can reduce performance in classification. In classifying pineapple maturity levels, 12 characteristics were obtained from extracting color, texture, and color characteristics. Utilizing dimensionality reduction, original data information can be preserved while reducing the number of variables. Feature dimension reduction is done using the feature reduction method and the PCA feature selection method. These important dimensional variables are condensed into fewer without sacrificing information in previous data. The five dominant components have been able to cover 94%• So, for this research, five main components were used, which will then be used in the SVM, KNN, and ANN machine learning models. There is an increase in the percentage of accuracy for each machine-learning method used. The increase in accuracy in the SVM and ANN methods is not very significant, only 1% and 2%. However, an increase in accuracy can be seen in the KNN method of 5%. With an increase in accuracy percentage, the PCA method can produce the best features for understanding the data, reducing processing requirements, and improving prediction performance. © 2023 IEEE.

关键词： Classification (of information)

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IoT in Smart Chromodynamic Plants Gardening 1

引用

32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Juric, Željko Keser, Tomislav Plander, Ivor Levanić, Mario Informatika Fortuno Ltd. Dragutina Žanića-Karle 27a Vinkovci32100 Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

The present economy of food production follows the trends of constant increase of its production. From year to year, better yields in crop production and efficient management of nutrient supply in flowers are expected. The environmental aspects that affect the well-being of flowers are well known, but the dynamics in the efficiency of nutrient ingestion efficiency and photocatalytic sugar production is something that has only been known relatively recently and has now become manageable. The efficiency of photocatalysis of floral nutrients is highly dependent on the photon-based energy source, or light, and its plant-specific conformal light spectrum. Generally, bluish and reddish tinted visible light sources are suitable for efficient plant growth, making the system more efficient overall (lower energy consumption and other requirements). Such systems are often referred to as chromodynamic plant growth systems. This paper presents an IoT-based system that leverages knowledge of chromodynamic plant growth control. The development and validation challenges are presented and explained. Proposals to solve the challenges are also presented to make the whole system Internet-enabled, chromodynamically controlled, and energy efficient. The systems presented show that chromodynamics validates the horticultural premise of nutrient uptake efficiency, in addition to energy efficiency and the trend toward networking everything based on IoT principles. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Nutrients

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The Essence of Perceived Compatibility and Behavioral Intention in Mobile Money Use

The Essence of Perceived Compatibility and Behavioral Intent...

引用

2024 International Conference on Advanced Information Scientific Development, ICAISD 2024

作者： Susanti, Leni Mohamad, Siti Hajar Savitri, Mila Andria Saputra, Karen Etania Alamsyah, Doni Purnama Setiadi, Ahmad Bina Nusantara University Binus Business School Entrepreneurship Department Jakarta Indonesia Management and Science University Department of Business Management and Law Selangor Malaysia Bina Nusantara University School of Design Interior Design Department Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Universitas Bina Sarana Informatika Faculty of Information Technology Software Engineering Department Jakarta Indonesia

ISBN: (纸本)9798350392036

Today, financial technology is a part of consumer needs. Mobile payments are used to support daily transactions, so a study of factors that can support behavioral intention and mobile money use is conducted. This study examines the support of digital literacy, perceived security, and perceived compatibility of mobile payments in increasing behavioral intention and mobile money use. The research was conducted on mobile payment users in Bandung City (Indonesia), and 416 research participants were asked using a questionnaire. The research was conducted using a quantitative survey and was processed using the SmartPLS tool. Two tests, namely, the PLS Algorithm and Bootstrapping, were used to test the research model. Next, the research hypothesis testing was used to explain the results. The research results found positive support from digital literacy, perceived security, and perceived compatibility on mobile payment behavioral intention. However, only perceived compatibility can directly increase the use of mobile money. In line with the hypothesis test, behavioral intention can support increased mobile money use by digital payment users. The research findings explain the ability of behavioral intention to mediate support for digital literacy, perceived security, and perceived compatibility in mobile money use. © 2024 IEEE.

关键词： Mobile commerce

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Deep Learning Method Based for Breast Cancer Classification

Deep Learning Method Based for Breast Cancer Classification

引用

Information technology Research and Innovation (ICITRI), International Conference on

作者： Irmawati Ferda Ernawan Mohammad Fakhreldin Andi Saryoko Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Faculty of Computing Universiti Malaysia Pahang Malaysia Faulty of Computer Science & Information Technology Jazan University Saudi Arabia Faculty of Information Technology Universitas Nusa Mandiri Indonesia

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Dynamic Programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

引用

5th International Conference on Cybernetics and Intelligent Systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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Unveiling the Power of ChatGPT: Transforming Face Detection with AI and AR 10

Unveiling the Power of ChatGPT: Transforming Face Detection ...

引用

10th International Conference on ICT for Smart Society, ICISS 2023

作者： Hermanus, Davy Ronald Sasmoko Kerta, Johan Muliadi Supangat, Suhono Harso Hidayat, Fadhil Hermanus, Danny Robert Indrianti, Yasinta Research Interest Group in Educational Technology Bina Nusantara University Computer Science Department Bandung Indonesia School of Electric and Informatic Institut Teknologi Bandung Bandung Indonesia Research Interest Group in Educational Technology Bina Nusantara University Faculty of Humanities Education Department Bandung Indonesia Bina Nusantara University Department Computer Science Bandung Indonesia Institut Teknologi Bandung Sekolah Tinggi Elektro Dan Informatika Bandung Indonesia Minneapolis United States Universitas Agung Podomoro Entrepreneurship Department Jakarta Indonesia

ISBN: (纸本)9798350339543

The goal of the current research is to develop a novel face identification system utilizing the Streamlit Python Library, with a particular emphasis on identifying and modifying human faces. The suggested solution makes use of ChatGPT, a powerful advanced communication model, to construct the fundamental program structure and assist in debugging potential coding problems. The method replaces the recognized human faces with other images by using a photo layer, delivering a distinctive and engaging experience. This prototype's main objective is to explore ChatGPT's potential and improve learning while the program is being developed. To identify and calculate the number of human faces in a given image or video stream, the system uses face identification algorithms. A configurable image layer is then used to replace each recognized face. © 2023 IEEE.

关键词： Python

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Analysis of Application of the SAW, WP and TOPSIS Methods in Decision Support System Determining Scholarship Recipients at University 3

Analysis of Application of the SAW, WP and TOPSIS Methods in...

引用

3rd International Conference on Computational science and Information Management, ICoCSIM 2019

作者： Marbun, Murni Zarlis, Muhammad Nasution, Zulkifli Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Teknik Informatika STMIK Pelita Nusantara Medan Indonesia

This research is an analysis of the application of the SAW, WP and TOPSIS methods to the support system for decision making at university. The types of scholarships provided are PPA education scholarships given by the Kementerian Riset, Teknologi dan Pendidikan Tinggi. The research variables are the attributes or criteria specified by the Directorate General of Learning and Student Affairs as contained in the 2018 Academic Achievement Improvement (PPA) guidebook. Decision Support Systems apply the classic FMADM method SAW, WP and TOPSIS. The results of this study are the application of the both methods of SAW and WP produce the same ranking and TOPSIS giving different rankings. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Exploring ERP User Behaviour in Developing Countries: Integrating Self-efficacy and UTAUT Perspectives 5

Exploring ERP User Behaviour in Developing Countries: Integr...

引用

5th International Conference on Advancement in Data science, E-Learning and Information Systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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Comparison of Machine Learning Methods Using Feature Extraction Optimization PCA Method for Identification of Pineapple Maturity Level

Comparison of Machine Learning Methods Using Feature Extract...

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Information technology and Computing (ICITCOM), International Conference on

作者： Fuzy Yustika Manik Syahril Efendi Dewi Sartika Ginting T.H.F Harumy Kana Sahputra S Nurhayati Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Sumatera Utara Indonesia Faculty of Mathematics and Natural Sciences Universitas Negeri Medan Medan Sumatera Utara Indonesia Faculty of Informatika Universitas Mikroskil Medan Sumatera Utara Indonesia

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