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Service Oriented Smart Model for Flood Controlling 9

Service Oriented Smart Model for Flood Controlling

引用

9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

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

ISBN: (纸本)9798350370126

Opening or closing dam-gate activities manually conducted in Manggarai dam to control the dam water level. The controlling action operated to avoid the flood possibility occurring in Jakarta city (the Indonesian capital). The study was conducted to develop a smart model for flood controlling based on service or called a service-oriented smart model (SOSM). The water-flow algorithm (WFA), fuzzy logic, object and service-oriented are four main methods operated in the study. The WFA is a central method to model the real water flow in the river coming from Katulampa dam (in Bogor city) until Manggarai dam (in Jakarta). The fuzzy logic functioned to simulate the dam's water level and the gate open/close decision should be decided by avoiding the bias value. The object-oriented model analysis and design approach, where the unified modelling language (UML) tools are operated to analyze and design the constructed model. Then, the service-oriented conception is used to integrate all sides in implementing the model. Finally, the constructed model can simulate the flood status in Jakarta via status value in decimal numbers with 6 numbers behind the point. © 2023 IEEE.

关键词： Floods

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Enhancing Fake News Detection with Sentiment Analysis Using Machine Learning 7

Enhancing Fake News Detection with Sentiment Analysis Using ...

引用

7th International Conference on Electronics, Materials Engineering and Nano-Technology, IEMENTech 2023

作者： Bose, Shreea Roy, Reek St Xavier's College Department of Post Graduate and Research Computer Science Kolkata India Belda College Department of Computer Science Paschim Medinipur India

ISBN: (纸本)9798350305517

In the digital age we live in today, fake news has become a serious problem because it has the power to sway public opinion, affect policy decisions, and upend social harmony. Sentiment analysis, which evaluates the content's emotional tone, is essential for spotting and stopping the spread of false information. In this work, we leverage machine learning techniques for sentiment analysis to increase the detection accuracy of fake news. To scrutinize the affective milieu present in news pieces and headlines, we investigate the amalgamation of various sentiment analysis instruments, such as VADER, TextBlob, and NLTK. By translating textual input into numerical properties, TF-IDF vectorization is utilized in conjunction with sentiment analysis to increase the predictive power of machine learning models. Enhancing the feature set through the use of TF-IDF vectorization is essential for teaching machine learning models to discern between authentic and fraudulent news. As classification models, Decision trees, SVM, and Logistic regression are used;each has advantages when it comes to processing tasks involving sentiment-based classification. In this study, we try to classify the emotions that the fake news mainly shows after the prediction. We have seen the trend that mainly Negative emotion is conveyed with fake news. The models have been compared and we're getting 98% accuracy. © 2023 IEEE.

关键词： Decision trees

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A Survey of Refactoring Techniques to Maximize Code Coverage Metric 15

A Survey of Refactoring Techniques to Maximize Code Coverage...

引用

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

作者： Simatupang, Johannes 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

Refasctoring is a technique used in software development to improve the quality of code without changing its functionality. One metric that is often used to measure code quality is Code Coverage. This study aims to examine refactoring techniques that can maximize Code Coverage Metric. Through the study, identification, evaluation, and summary of empirical evidence from various literature sources are carried out. The results of this study provide guidance on effective refactoring techniques to improve Code Coverage as well as other positive impacts for software development. There are ten refactoring techniques that can be used to improve Code Coverage Metrics in software testing. © 2023 IEEE.

关键词： Software testing

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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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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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Service Oriented Fuzzy Smart Model for Agriculture Investment of Hydroponic Green-Leaf Vegetable Plant 10

Service Oriented Fuzzy Smart Model for Agriculture Investmen...

引用

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

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

ISBN: (纸本)9798350339543

An integrated approach is necessary for implementing a model that involves multiple actors. One effective way to achieve this is through a service-oriented approach. The objective of the study was to develop a service-oriented fuzzy model, which combines the functional-structural plant modelling (FSPM) method for the plant computational model (PCM) and the fuzzy logic method for both PCM and the decision support model (DSM). This combined method aims to model the plant behaviour morphologically and propose investment decisions in agriculture, specifically for the hydroponic cultivation of Bok Choy, a green-leaf vegetable. The accuracy of the interconnected model application based on the service concept, known as the service-oriented fuzzy smart model (SOFSM), reached 94.33%. © 2023 IEEE.

关键词： Hydroponics

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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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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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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...

引用

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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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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