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International Congress on Applied Information Technology

作者： Yaya Heryadi Dandalina Doctor of Computer Science Program Bina Nusantara University Jakarta Indonesia Master of Information and Technology Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Anomalies in data become ubiquitous and often unavoidable. Despite it might be caused by various errors during the data collection or transportation, some anomalies potentially give important information such as indication of a new underlying process. The aim of anomaly detection task is to determine all such instances in the input dataset in a data-driven fashion. In the past decade, the proliferation of anomaly data in many domains have raised research interest resulted in a plethora of anomaly detection methods A vast number of previous study reports suggested that there is no single model will achieve the best performance for every dataset. This paper presents empiric results on the effect of several kernel functions to performance of One-Class Support Vector Machine (OC-SVM) as an anomaly detector model. The proposed model is tested using financial transactions of microfinance service dataset from an Indonesian Bank. The empiric results showed that OC-SVM model with Sigmoid and RBF kernels achieve the best statistically significant value of training, validation, and testing accuracies than the OC-SVM model with no-kernel, linear kernel and polynomial (degree 3,4,5,6) kernels.

关键词： Kernel Anomaly detection Training Testing Support vector machines Task analysis Feature extraction

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Study of runway crosswind and tailwind potential for airport sustainability: A study of Soekarno Hatta airport, Cengkareng, Indonesia

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： W Sardjono Zulkarnain H Kusnoputranto TEB Soesilo DN Utama J Sudirwan Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management BINA NUSANTARA University Jakarta Indonesia 11480 Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Faculty of Public Health University of Infonesia Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480

Airport runway designs must consider wind climatology to reduce the potential for crosswind and tailwind events that can cause accidents and aircraft delays. The large potential of crosswind and tailwind on a runway at the airport is very detrimental to aircraft passengers and airlines. Therefore, it is necessary to know the potential of crosswind and tailwind on the runway of Soekarno Hatta Airport and find the right parameters for the approximate direction and speed of the wind on the airport runway. Analysis was carried out using the direction and wind speed data from the Soekarno Hatta meteorological station in 2007-2017 to determine the potential for crosswind and tailwind on the runway of Soekarno Hatta airport and run a Weather Research and Forecasting (WRF) weather model to determine the parameterization of the right weather model for wind forecast at Soekarno Hatta airport. The highest maximum crosswind component in the 2007-2017 period occurred in August 30.53 knots, while the highest maximum tailwind of 25 knots occurred in January for a 250-degree runway and 24 knots occurred in August for a 070-degree runway. The potential for crosswind and tailwind is different every month. The scheme produces forecasts of wind direction and speed with a strong level of correlation with observations of wind direction and speed from the Soekarno Hatta meteorological station, the correlation value is 0.61. The most significant social impact of plane delays is time loss for passengers. While the economic impact on one of the crosswind events at Soekarno Hatta airport was an economic loss for one airline of US $ 43,392.

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Data warehouse for analysing music sales on a digital media store

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Journal of Physics: Conference Series 2020年第3期1477卷

作者： Kiefer Stefano Ranti Deyanara Tuapattinaya Calvin Chang Abba Suganda Girsang Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Nowadays, every company knows that when making a decision that has a potential in affecting their assets, an accurately processed report is necessary in order to support the reasoning behind their decision. Generating a report for stakeholders quickly and accurately is highly required in assisting them making a data-driven decision. By developing a data warehouse, it is possible for a company to do a data-driven decision making to appeal to their customer segments. This paper proposes a data warehouse model design to analyse the sales data contained in the database. The method that was implemented for this particular data warehouse development is the nine-step methodology designed by Kimball. The results are then presented in pdf form and an interactive dashboard.

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Employing best input SVR robust lost function with nature-inspired metaheuristics in wind speed energy forecasting

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2020年第3期47卷 572-584页

作者： Caraka, Rezzy Eko Chen, Rung Ching Bakar, Sakhinah Abu Tahmid, Muhammad Toharudin, Toni Pardamean, Bens Huang, Su-Wen College of Informatics Chaoyang University of Technology Taichung City41349 Taiwan School of Mathematical Sciences The National University of Malaysia Bandar Baru Bangi Selangor43600 Malaysia Bioinformatics and Data Science Research Center Bina Nusantara University 11480 Indonesia Manado North Sulawesi91594 Indonesia Department of Statistics Padjadjaran University Jatinagor west java45363 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University and Computer Science Dept. BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Taichung Veterans General Hospital Taiwan

Wind power has been experiencing a quick improvement. Without a doubt, wind is a variable asset that is hard to forecast. For instance, traditionally time series, extra holds are distributed to deal with this uncertainty. This paper presents a comparison of the performance of various Support Vector Regression (SVR) applied to short-term wind power forecasting. The analogy with BORUTA and multivariate adaptive regression splines (MARS) as judge best input and employ genetic algorithm and particle swarm optimization to find best parameter in Support Vector Regression with robust lost function. We measure the accuracy of this models by Symmetric means absolute percentage error (sMAPE) and we get the best model BORUTA-SVR-PSO with sMAPE 2.07155%. Moreover, we measure the energy conversion using Feedback Linearization Control (FLC). © International Association of Engineers.

关键词： Genetic algorithms

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Multiparty mediated quantum secret sharing protocol

arXiv

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arXiv 2021年

作者： Tsai, Chia-Wei Yang, Chun-Wei Lin, Jason Department of Computer Science and Information Engineering National Taitung University No. 369 University Rd. Taitung95092 Taiwan Center for General Education China Medical University No. 100 Jingmao Rd. Beitun Dist. Taichung City 406040 Taiwan Master Program for Digital Health Innovation College of Humanities and Sciences China Medical University No. 100 Jingmao Rd. Beitun Dist. Taichung City406040 Taiwan Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Rd. Taichung South District40227 Taiwan

This study proposes a multiparty mediated quantum secret sharing (MQSS) protocol that allows n restricted quantum users to share a secret via the assistance of a dishonest third-party (TP) with full quantum capabilities. Under the premise that a restricted quantum user can only perform the Hadamard transformation and the Z-basis measurement, the proposed MQSS protocol has addressed two common challenges in the existing semi-quantum secret sharing protocols: (1) the dealer must have full quantum capability, and (2) the classical users must equip with the wavelength quantum filter and the photon number splitters (PNS) to detect the Trojan horse attacks. The security analysis has also delivered proof to show that the proposed MQSS protocol can avoid the collective attack, the collusion attack, and the Trojan horse attacks. In addition, the proposed MQSS protocol is more efficient than the existing SQSS protocols due to the restricted quantum users can only equip with two quantum operations, and the qubits are transmitted within a shorter distance. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum cryptography

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Promoting Timor Leste's Tais Cloth Using Mobile Augmented Reality Application 3

Promoting Timor Leste's Tais Cloth Using Mobile Augmented Re...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Seran Bria, Marianus Magno Kusuma, Gede Putra Putera Suryapranata, Louis Khrisna Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The results of observations showed that the book about Tais produced by Secretariat de Estado da Arte e Cultura (SEAC) has not been able to meet the needs of users because the information is less interesting and interactive. This paper's aim is to introduce the more interesting and interactive way to introduce Tais. Utilization of Augmented Reality (AR) technology in an application built with the Unity3D program is done to provide different way in presenting interesting and interactive information to its users. Based on the results in this paper, the developed application can handle the presentation in more interesting and interactive way. The ideal distance in the tracking process for target objects with size 7 x 6 cm is ranged from 6 cm to 30 cm, with the image ratio that can be detected at the farthest distance is 4% of the camera image. For the detection angle, the target object can be detected properly from approximately ±640. From the data acquired, it can be said that AR can be used to introduce Tais in more interesting and interactive way. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Augmented reality

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Testing Big Data Application

Testing Big Data Application

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Narinder Singh Punn Sonali Agarwal M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology Allahabad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications.

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A Third Order based Additional Regularization in Intrinsic Space of the Manifold

A Third Order based Additional Regularization in Intrinsic S...

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Rakesh Kumar Yadav Abhishek Shekhar Verma S Venkatesan M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology-Allahbad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Second order graph Laplacian regularization has the limitation that the solution remains biased towards a constant which restricts its extrapolation capability. The lack of extrapolation results in poor generalization. An additional penalty factor is needed on the function to avoid its over-fitting on seen unlabeled training instances. The third order derivative based technique identifies the sharp variations in the function and accurately penalizes them to avoid overfitting. The resultant function leads to a more accurate and generic model that exploits the twist and curvature variations on the manifold. Extensive experiments on synthetic and real-world data set clearly shows that the additional regularization increases accuracy and generic nature of model.

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Optimization and simulation methods in addressing COVID-19 physical distancing policy: A bibliometric analysis

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AIP Conference Proceedings 2022年第1期2472卷 040010页

作者： Fazillah Mohmad Kamal Mohd Kamal Mohd Nawawi Ruzelan Khalid Antoni Wibowo Amalia Zahra School of Quantitative Sciences UUM College of Arts and Sciences Universiti Utara Malaysia 06010 UUM Sintok Kedah Malaysia Institute of Strategic Industrial Decision Modeling School of Quantitative Sciences Universiti Utara Malaysia 06010 UUM Sintok Kedah Malaysia Computer Science Department Binus Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

COVID-19 has received tremendous attention from scholars worldwide and even being labelled as a black swan event that has disrupted every aspect of human life. Within a short time span of the pandemic, a large volume of research pertaining to COVID-19 has been published in diverse research fields. This paper adopts a bibliometric analysis to systematically evaluate the research development in the application of optimization and simulation methods to address COVID-19 physical distancing policy (OSPhyD) using Bibliometrix R package. A textual query on Scopus database using the combination of four classes of keywords; covid-19, optimization, simulation, and physical distance has returned a total of 299 original research articles and reviews published in English. Appropriate visualizations were generated to describe the collaborations between different authors, countries, and institutions, whilst co-word analysis that uses text mining technique has produced a conceptual cluster via co-occurrence network map to underscore the emerging themes in the current research interest. The main findings pinpoint that: 1) OSPhyD as a scientific research field is an emerging multidisciplinary research topic that is growing progressively and steadily in the fields of medicine, engineering, social sciences, mathematics and decision science, 2) The field has attracted the attention of scholars from all over the world particularly from United States of America, United Kingdom, European countries including authors from Asia, and 3) Three dominant themes or research front emerged from the publications including COVID-19 mainstream, medical education and undergraduate.

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Convolve4D: A Novelty Approach to Improve Convolutional Process

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Suryadiputra Liawatimena Edi Abdurahman Agung Trisetyarso Antoni Wibowo Wiedjaja Atmadja Fandy Effendi Ivan Sebastian Edbert Computer Science Department BINUS Graduate Program - Doctor ofComputer Science Bina Nusantara University Jakarta Indonesia 11480 ComputerEngineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 ComputerScience Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Convolutional neural networks (ConvNet or CNN) are deep learning algorithms that can process input images, assign meaning to various aspects or objects in the image (biases and learnable weight) and recognize one image from another. The bigger kernel size will take more time to process the *** present a novelty way to use a 4D rank tensor to improve a convolutional process. At the early stage of the Convolve4D development, the edge detection with 3×3 kernel and The Laplacian of Gaussian (LoG) with 5×5 kernel size was used to demonstrate the convolutional process improvement. The Convolve4D needs more elaboration to be used into a CNN algorithm. The advantage of convolve4D is only need 9 loops to calculate 81 outputs, whereas convolve2D need 9 × 9 × 3 × 1 × 7 × 7 = 11.907 loops. The result is 18.5% shorter when using a 5×5 kernel; it reduces from 0.54 seconds to 0.44 seconds for the edge detection convolution process.

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