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Mining Association rule with Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) data mining technique 2

Mining Association rule with Attribute Oriented Induction Hi...

引用

2nd International Conference on Inventive Communication and Computational Technologies, ICICCT 2018

作者： Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Heryadi, Yaya Trisetyarso, Agung Sanchez, Horacio Emilio Perez Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Guadalupe30107 Spain

ISBN: (纸本)9781538619742

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as proposed new data mining technique has been success to mine frequent and similar patterns. Moreover, the AOI-HEP data mining technique has been improved with confidence mining pattern into two terms, where firstly give confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern. Secondly, give confidence for each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence for each AOI-HEP pattern will show how interested each of AOI-HEP pattern between frequent and similar pattern, whilst confidence per dataset will show how interested each dataset between frequent and similar pattern. In this paper the mining of AOI-HEP has been extended to mine AOI-HEP association rules using the current AOI-HEP frequent pattern, since association rule deal with frequent pattern. Based from previous experiments upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS, there are 9 finding AOI-HEP frequent patterns where 8 from adult and breast cancer datasets respectively. Finally, there are 2 and 1 AOI-HEP association rules from adult and breast cancer datasets respectively. © 2018 IEEE.

关键词： Association rules

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The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of computer science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

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Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs 1

Comprehensive Analysis and Remediation of Insecure Direct Ob...

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1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Abdullah, Roni Reza Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia National Institute of Science and Technology Faculty of Informatics Engineering Jakarta12630 Indonesia Bina Nusantara University Binus Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience. © 2023 IEEE.

关键词： Sensitive data

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Evaluation of Information Technology Governance in STMIK Mikroskil Using COBIT 5 Framework 3

Evaluation of Information Technology Governance in STMIK Mik...

引用

3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Nyonawan, Marwandy Suharjito Utama, Ditdit Nugeraha Computer Science Department STMIK Mikroskil Medan Indonesia Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

This paper describes the maturity degree evaluation of Information Technology Governance at Information System Centre (PSI) in STMIK Mikroskil to measure IT Governance and the success of IT-based facilities that cannot be measured yet. The evaluation measured by using Process Assessment Model (PAM) from Framework COBIT 5 which refers to the specified 10 domain process. Data is collected from 36 returned-questionnaire of 47 distributed-questionnaire. Data is analyzed using Framework COBIT 5, Slovin method is used to determine the number of valid data samples, and Rating Scale Formula operated to determine the scale of capability level for each selected domain. From the evaluation results known 1 domain has been achieved the expected capability that is DSS05 at Level 4, and other process domains still exist under the expected capability level, then the results are used to establish improvement recommendation based on Framework COBIT 5. © 2018 IEEE.

关键词： Surveys

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Telematics Work Field Review Text Classification Using the Naïve Bayes Method

Telematics Work Field Review Text Classification Using the N...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Maesya, Aries Heryadi, Yaya Arifin, Yulyani Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Indonesia

ISBN: (纸本)9781665468763

Indonesia will benefit from a demographic boom in 2030 with a higher labor supply than in earlier decades. Then in industrial revolution 4.0 robotics and artificial intelligence will take the place of low-skilled or menial employment that don't require specialized expertise (AI). To aim research is Telematics Work Field Review Text Classification Using the Naïve Bayes Method. The method using Multinomial Naïve Bayes model which is trained to learn from patterns in training data set without being programmed explicitly. Then, based on the Term Frequency - Inverse Document Frequency, consider the weighting of the word used (TF-IDF). The text classification stage is then carried out using the multinominal nave bayes classification method with evaluation using the confusion matrix, following the acquisition of the TF-IDF value. In the study it took data with web crawling techniques on social media sites twitter. The data collected was 936 data consisting of 7,8% negative sentiments, 26,4% positive sentiments, and 65,8% neutrals. The results of accuracy testing using the Confusion Matrix. And from the results of such tests resulted in an accuracy of 66%, precision 73%, and recall 85%. © 2022 IEEE.

关键词： Telematics

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Multiple-Clustering Comparison in Spatial Data for Additional Accuracy Measurement in Land-use Classification 4

Multiple-Clustering Comparison in Spatial Data for Additiona...

引用

4th International Conference on Informatics and Computing, ICIC 2019

作者： Herlawati Heryadi, Yaya Hendric Spits Warnars, Harco Leslie Gaol, Ford Lumban Abdurachman, Edi Soewito, Benfano Bina Nusantara University BINUS Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728122076

Satellite imageries have been widely used to analyze a region by planners. Data from the satellite usually have lower accuracy than other expensive methods e.g. drone, aerial view, etc. However, the data from satellite have wide range area and sufficient enough for modeling a land use. The accuracy assessment, therefore, becomes a vital task to ensure the model from the satellite imagery meets the minimum requirement. Validating the classification result by comparing to the real location or by other higher resolution images is needed. The paper proposed additional validation by comparing the classification result by another result in different date through the cross-tabulation method. Two satellite imageries in the same year were processed before classification to get the land-use and land-cover classification. Comparing two land-use classified images gave the accuracy statistics using cross-tabulation. The kappa statistic and accuracy showed the classification performance of 0.7592 that similar to the sampling-based accuracy assessment (0.75390). Therefore, the proposed method was appropriate as the accuracy assessment. © 2019 IEEE.

关键词： Satellite imagery

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Detection of Employee Fatigue Based on Image Processing Using Deep Learning Model 4

Detection of Employee Fatigue Based on Image Processing Usin...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Ethan, Michael Kusuma, I. Gede Putra Bina Nusantara University Computer Science Department Binus Graduate Program Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

Fatigue in workplace is a common thing shared by all employees. Continuous exposure of fatigue could lead to negative productivity for companies. Current research on fatigue detection mostly focused to detect fatigues from a single 2D image data, meanwhile research on fatigue detection using each frames from video data is needed for better detection for fatigue process. The main advantage of using each timesteps of frames from video data which makes the model is able to predict long term dependency of fatigue person. To solve this problem, a deep learning model is proposed that could detect employee fatigue based on image processing using video data. Three models are used to train data using Convolutional Neural Network (CNN), which are Time Distributed CNN LSTM, 3D CNN, and 3D CNN LSTM. Out of those three models, the best model to detect fatigue person from video data is Time Distributed CNN Model with F-1 Score value of 0.77 and Accuracy Score of 0.76 for testing data. The model that gives best inference time is also Time Distributed CNN Model with the average value of 382 miliseconds to detect fatigues from 58 testing data with each of the data has duration of 3 seconds and 12 frames. © 2024 IEEE.

关键词： Video analysis

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Customer-oriented diagnosis of memory provisioning for IaaS clouds

Customer-oriented diagnosis of memory provisioning for IaaS ...

引用

Brazilian Symposium on computer System Engineering, SBESC 2013

作者： Pfitscher, Ricardo J. Pillon, Mauricio A. Obelheiro, Rafael R. Santa Catarina State University Graduate Program in Applied Computing Department of Computer Science Brazil

Infrastructure-as-a-service clouds enable customers to use computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One challenge for IaaS customers is the correct provisioning of their resources. Many users end up underprovisioning, hurting application performance, or overprovisioning, paying for resources that are not really necessary. Memory is an essential resource for any computing system, and is frequently a performance-limiting factor in cloud environments. In this work, we propose a model that enables cloud customers to determine whether the memory allocated to their virtual machines is correctly provisioned, underprovisioned, or overprovisioned. The model uses two metrics collected inside a VM, resident and committed memory, and defines thresholds for these metrics that characterize each provisioning level. Experimental results with Linux guests on Xen, running four benchmarks with different workloads and varying memory capacity, show that the model was able to accurately diagnose memory provisioning in 98% of the scenarios evaluated. Copyright 2013 by the Authors.

关键词： Customer satisfaction

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Efficiency of Multi-Language Data Serialization for Hybrid Cloud-Edge HRIS 9th

Efficiency of Multi-Language Data Serialization for Hybrid C...

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

作者： Winata, Andreas Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

In hybrid cloud-edge systems, data processing is distributed between cloud servers and edge servers, this makes data serialization critical for efficient data transfer between servers. This study evaluates the efficiency of multi-language data serialization of Human Resources Information System (HRIS) in a hybrid cloud-edge environment. Because lack of existing studies that specifically evaluate multi-language data serialization for hybrid cloud-edge HRIS, this study conducted a Systematic Literature Review (SLR) to get the list of current state of the art of data serialization methods and then used this result to evaluate the methods. By focusing on HRIS employee data from the employee management module, this study measures both data serialization and deserialization using performance metrics of time, data size, and CPU usage. The results indicate that no methods excel in all metrics, but FlatBuffers, Protocol Buffer, and Apache Avro can provide balanced effectivity across the metrics. The study gives valuable insight for selecting data serialization methods, architecture, and systems requirements in hybrid cloud-edge HRIS to ensure the performance efficiency of the system. © 2024 The Authors.

关键词： Cloud platforms

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Optimal resource allocation for survivable virtual infrastructures

Optimal resource allocation for survivable virtual infrastru...

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10th International Conference on Design of Reliable Communication Networks, DRCN 2014

作者： De S. Cavalcanti, Gustavo A. Obelheiro, Rafael R. Koslovski, Guilherme Graduate Program in Applied Computing Department of Computer Science Santa Catarina State University Brazil

ISBN: (纸本)9781479940097

Virtual infrastructures (VIs) consolidated the dynamic provisioning of computing and communication resources. A VI is a set of virtual machines interconnected by virtual links and switches/routers. Infrastructure providers (InPs) manage the physical substrates in which virtual resources requested by VIs (such as CPU, disk, memory, bandwidth) are reserved and allocated. Resource allocation is a complex problem that needs to satisfy different goals: users expect to run their applications on survivable VIs, while InPs aim to maximize profits, minimize costs and reduce substrate fragmentation. However, there is a dichotomy between minimizing substrate fragmentation, by co-locating VIs, and maximizing VI survivability, by sparsely allocating resources in order to decrease the impact of substrate failures. In this context, this paper discusses VI survivability and its impact on substrate fragmentation. We propose a mixed integer linear programming model to allocate resources considering the joint coordination of fragmentation and survivability. Experimental results suggest that it is possible to enhance VI survivability without significantly impacting substrate fragmentation. © 2014 IEEE.

关键词： Substrates

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