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Easy Data Augmentation for Handling Imbalanced Data in Fake News Detection 1

Easy Data Augmentation for Handling Imbalanced Data in Fake ...

引用

1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Pradana, Rilo Chandra Joddy, Setiawan Girsang, Abba Suganda Binus Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350360554

Detecting fake news in the digital era is challenging due to the proliferation of misinformation. One of the crucial is-sues in this domain is the inherent class imbalance, where genuine news articles significantly outnumber fake ones. This imbalance severely hampers the performance of machine and deep learning models in accurately identifying fake news. Consequently, there is a compelling need to address this problem effectively. In this study, we delve into fake news detection and tackle the critical issue of imbalanced data. We investigate the application of Easy Data Augmentation (EDA) techniques, including back-translation, random insertion, random deletion, and random swap to mitigate the adverse effects of imbalanced data. This study focuses on employing these techniques in conjunction with a deep learning framework, specifically a Bidirectional Long Short-Term Memory (BiLSTM) architecture. The results of the EDA techniques will be systematically compared to see their effectiveness and their impacts on model performance. This study reveals that various EDA techniques, when coupled with a BiLSTM architecture, yield significant improvements in fake news detection. Among the experiments, it shows that Random Insertion, with an impressive accuracy rate of 81.68%, a precision score of 89.38%, and an F1-Score of 87.77% emerges as the most promising technique. The study also highlights the exceptional potential of Back-translation stands out with an 87.16% recall performance. © 2023 IEEE.

关键词： Long short-term memory

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Neural Network and Resampling to Handle Imbalance Class on Estimate Software Defect 15

Neural Network and Resampling to Handle Imbalance Class on E...

引用

15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Setiawan, Tri Agus Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Rapid progress in the field of artificial intelligence has created opportunities for extensive applications in software development. One area that receives attention is the evaluation of code quality using machine learning techniques. In this investigation, we examined the possible application of machine learning to predict the likelihood of defects in computer code. We employ NASA archival data as case studies. Machine learning models employ neural network algorithms. Our exploration involves partitioning the dataset into training data and test data for performance evaluation. The findings indicate that the Neural Organize technique with resampling yields a high level of accuracy in predicting software defects. Our simulated neural network is capable of identifying intricate patterns in the data and providing precise measurements of the size and intensity of defects. These results have significant implications in the software business, enabling developers to promptly identify possible vulnerabilities and take preventive measures before product release. © 2023 IEEE.

关键词： Machine learning

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Cancer Classification in Imbalance Data Using Double Filtering Approach 7

Cancer Classification in Imbalance Data Using Double Filteri...

引用

7th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2023

作者： Mujhid, Almuzhidul Tedjasulaksana, Jeffrey Junior Masaling, Nikita Ananda Putri Girsang, Abba Suganda Graduate Program - Master of Computer Science Bina Nusantara University Binus Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350382266

Cancer, also known as malignant neoplasm, is a complex and potentially fatal disease characterized by uncontrolled and abnormal cell growth in the body. The main problems with microarray cancer studies are the high curse of dimensionality and small sample size caused by redundant and irrelevant genes. To deal with the number of features that exceed the amount of data, this research purposed double filtering method Lasso-GA, Lasso is used to select the features based on feature correlation while Genetic Algorithm is used to optimize the most important features with accuracy traditional machine learning as its fitness function. The results show how effective the suggested method is;in breast cancer, the linear SVC model achieves excellent accuracy (0.93), precision (0.94), recall (0.94), and F1 score (0.94), while in lung cancer, the linear SVC, random forest, and logistic regression models perform well (accuracy: 0.95, precision: 0.92, recall: 1, F1 score: 0.95). Logistic regression is the most effective method for bladder cancer, with an accuracy of 0.82, precision of 0.77, recall of 1, and F1 score of 0.87. © 2023 IEEE.

关键词： Genetic algorithms

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Website Personalization Using Association Rules Mining 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Soewito, Benfano Johan, Jeffrey Computer Science Department Master of Computer Science BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Many companies are redefining their business strategies to improve the business output. Business over internet provides the opportunity to customers and partners where their products and specific business can be found. Web usage mining is the type of web mining activity that involves the automatic discovery of user access patterns from web servers. A real-world challenging task of the web master of an organization is to match the needs of user and keep their attention in their web site. So, web pages can capture the intuition of the user and provide them with the recommendation list. Personalize e-commerce website is done after knowing the habits and behavior patterns of customers e-commerce website using web usage mining with association rules mining apriori algorithms. The method used is a method of analysis and design. In the method of analysis, research variables are determined, and data of sales are collected. In addition, the method of analysis is also performed to measure the accuracy of the apriori algorithm. Designing apriori, program design, and the design of the screen is done in the design method. Results are achieved in the form of an e-commerce website that is personalized using association rules mining apriori algorithm that can recommend the goods in accordance with the preferences and needs of the user. The conclusion of this study is to obtain patterns of association, it takes the data transactions made by customers and the recommendations given by the apriori algorithm would be more accurate if the transaction data is processed more, the categories of goods are fewer, the limit minimum value of support and the limit minimum value of confidence are high. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Websites

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Irrigation Control System for Seedlings Based on the Internet of Things 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： de Carvalho, André Kusuma, Gede Putra Handoyo, Alif Tri Department of Computer Science BINUS Graduate Program—Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

The agricultural activities in the Vocational School of Agricultural Engineering (ESTVA) in Timor-Leste requires large quantities of water with high availability for the production and cultivation of plants. However, the crop results sometimes decrease due to challenges problem faced by the management of the water resources. This study aims to design an Internet of Things (IoT) based automatic control system to control water supply and maintain soil moisture conditions effectively. The evaluation of manual and automatic irrigation systems during the 21 days trial shows that the automatic system provides stable utilization of water with watering frequency of 274 occurs only in 12 days, with an amount of total watering of 35.3 L. Meanwhile, the manual system uses up to 49.8 L of water, which is 14.5 L more than the water spent by the automatic system. The results of the evaluation also indicate that automatic system obtains the average moisture value of 509 with a standard deviation of 63, which is smaller than the manual system that obtains an average moisture value of 559 and a significant standard deviation of 126. From these results, the automatic system is more effective in maintaining the soil moisture level and yet requires less water compared to the manual watering system. Furthermore, the quality and productivity of the growth of mustard seedlings with automatic system prove that the seeds are more stable and feasible to continue transplanting since the automatic system produces 12 more mustard trees compared to the manual system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Soil moisture

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An Object Oriented Floating Fuzzy Decision Model for Evaluating the Student Performance 6

An Object Oriented Floating Fuzzy Decision Model for Evaluat...

引用

6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Utama, Ditdit Nugeraha Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350358346

The concept of object-oriented (OO) serves is a fundamental approach in the development of models. The stages associated with this method contribute significantly to ensuring that the resulting model is both lucid and transparent. The primary objective of the study is to create a decision model for evaluating student performance. Floating fuzzy logic (FFL) is employed as a technique to handle fluctuating data within the model. Moreover, OO conception plays a central role in analyzing, designing, and constructing the model through the utilization of four distinct types of Unified Modeling Language (UML) diagrams: object, activity, state-machine, and sequence diagrams. The model itself is crafted using the Python programming language and executed in the Google Colab platform. Additionally, this model has the capability to simulate changes in students' performance on a semester-by -semester basis, exhibiting a variance of 15 % when compared to the conventional fuzzy logic model. © 2023 IEEE.

关键词： Fuzzy logic

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Variational quantum neural network with optimized ansatz for predicting malignant ventricular arrhythmias 9th

Variational quantum neural network with optimized ansatz for...

引用

9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Dominic, Nicholas Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Preventive strategies should be the utmost priority when dealing with diverse patients suffering from malignant ventricular arrhythmia (MVA) that can lead to sudden cardiac death (SCD). Electrocardiogram (ECG) data is commonly used as a predictor for MVA predictive models. In this study, all ECG signals from MIT-BIH databases were fragmented into five-minute durations with a frequency sampling of 128 Hz. To solve the absence of hybrid optimizations in Machine Learning (ML) models, a novel Variational Quantum Neural Network (VQNN) was invented. Empowered by deep learning capabilities and optimized quantum circuits design, VQNN achieved remarkable performances designated by an accuracy of up to 95.1%, a perfect 100% recall, and a 95.2% score of the area under the Receiver Operating Characteristic curve (AUC ROC) with Conjugate Gradient as an optimizer and EfficientSU2 as a quantum ansatz. Despite the susceptibility to quantum noise, this research settles a new trajectory of utilizing quantum variational algorithms to predict and expand its applicability for MVA cases. © 2024 The Authors.

关键词： Quantum computers

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Analyzing the Impact of Service Design on Maintainability Factor in Microservices Architecture 15

Analyzing the Impact of Service Design on Maintainability Fa...

引用

15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Gintoro Gaol, Ford Lumban Soeparno, Haryono Arifin, Yulyani Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Applications designed utilizing Microservices Architecture (MSA) provide the desirable trait of good maintainability. To ensure optimal maintainability, it is important to provide services that are suitable and adhere to prescribed rules. Multiple aspects must be taken into account while designing services to ensure optimal maintainability. The objective of this study is to examine the elements that impact the capacity to sustain and improve maintainability in service design, ultimately resulting in an application that possesses strong maintainability. The Systematic Literature Review (SLR) will be utilized to identify variables and strategies for their enhancement, by examining pertinent publications on the subject. After examining 45 publications, the study discovered 8 elements and 14 solutions that can enhance the highlighted parameters throughout the services design process. The outcomes of this systematic literature review (SLR) are anticipated to give valuable insights to application developers, empowering them to generate service designs that exhibit commendable maintainability for the developed applications. © 2023 IEEE.

关键词： Maintainability

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The Impact of Shift-Left Testing to Software Quality in Agile Methodology: A Case Study 8

The Impact of Shift-Left Testing to Software Quality in Agil...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Andriadi, Kus Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

The point of Agile Methodology is continuous improvement, delivering a small feature quickly without sacrificing the feature quality;every sprint must be better than the previous sprint, and better can be fewer bugs, faster development, and testing. We will present how we reduce production bugs by customizing our sprint iteration. As we know, bugs are unavoidable, there is no software engineer that can make software without a bug;however, we can reduce bugs in production if we can find bugs in lower environments as early as possible. The case study in this paper was taken from one of technology company in Indonesia, the activity was done by the Quality Engineer (QA) Team. We will show that shift-left testing can help us reduce bugs in production. Testing is part of agile methodology, and the main idea of shift-left testing is to move testing early and could be done by any team member, not only QA. We include shift-left testing in our agile methodology for one year in 2022 and compare the result in the previous year. © 2023 IEEE.

关键词： Software testing

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Multi-Criteria based Decision Model for Evaluation 6

Multi-Criteria based Decision Model for Evaluation

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Utama, Ditdit Nugeraha Bin Widayat, Muhamad Akbar Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350358346

Addressing multiple criteria and parameter issues in computer modelling presents a significant challenge. Several factors including data types, parameter behaviours, and purposes, must be taken into account to enhance computer modelling capability;particularly in evaluation cases. Through the utilization of a multi-criteria and method approach, a decision model was effectively developed to assess a case of environmental sustainability level of a building. One method operated in the study is the curve method for handling membership function form in realizing fuzzy logic. This innovative model demonstrates superior performance. It achieves an impressive accuracy rate of 96%, surpassing the previous model that employed a trapezoidal approach to describe fuzzy membership functions hy 1%. © 2023 IEEE.

关键词： Fuzzy logic

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