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Waiting-Time Estimation in Bank Customer Queues using RPROP Neural Networks

Procedia computer science 2018年 135卷 35-42页

作者： Rinda Parama Satya Hermanto Suharjito Diana Ariadi Nugroho Computer Science Department BINUS Graduate Program- Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In daily banking customer queues, unknown waiting-time could lower customer experience. Little’s Law formula in Queue Theory provides a generic formula for waiting-time, but it cannot be implemented directly to give finite wait-time estimation in real-life. This study aims to investigate predictive variables that explain waiting-time duration. This paper uses Fast Artificial Neural Network engine to implement Artificial Neural Networks method. To train Artificial Neural Networks, Resilient Propagation was used. Time-series approach and structural approach for input neuron was compared. Average duration from previous interval and number of server was proposed to increase structural variable like Queue Length and Head of Line Duration estimator variable. To determine the best configuration for number of neuron in input and hidden layer, experimental method was used. The results of this study show that structural approach provides better estimation than time-series approach. Furthermore, modified helper variable combination provides a more refined result.

关键词： waiting-time estimation neural networks time-series queue

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Image Size, Color Depth, Age variant on Convolution Neural Network 1

Image Size, Color Depth, Age variant on Convolution Neural N...

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1st Indonesian Association for Pattern Recognition International Conference, INAPR 2018

作者： Pranoto, Hady Budiharto, Widodo Hendric Spits Warnars, Harco Leslie Matsuo, Tokuro Heryadi, Yaya Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781538694220

Facial recognition as of biometric authentication used in the field of security, military, finance and daily use is become a trend or famous, because of its natural and not intrusive nature. Many methods for face recognition such as holistic learning, the use of local features, shallow learning and deep learning, some methods are susceptible to variations in pose change, illumination, expression and age variation. State of the art of face recognition today is a deep learning technique that delivers high accuracy. In this paper author replicate an face recognition using deep learning architecture called OpenFace Convolutional Neural Network. In this research author make variation on the size of image, color dept and age, and see how that factor impact on accuracy of face recognition in that architecture. As the result from the research, the accuracy of a model depends on the image size, color depth, and age variation, but in OpenFace CNN that recognition still provides fairly good accuracy when reducing the size of image and color depth, as long as the image can still be detected on the landmark facial, so the alignment process can be done on the face image. © 2018 IEEE.

关键词： Face recognition

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Improve Understanding and Dissemination of Disaster Management and Climate Change by Using Knowledge Management Systems

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IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Wahyu Sardjono Harisno Widhilaga Gia Perdana 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

In Law Number 24 Year 2007 concerning Disaster Management, it is stated that the central government and regional governments are responsible for implementing disaster management, with an emphasis on preparedness and mitigation in dealing with natural disasters, as well as based on the provisions of article 1 of Presidential Regulation No. 46 of 2008 concerning the National Council on Climate Change that climate change is a change in average conditions of climate and / or climate diversity from one period of time to another as a result of human activity. However, the socialization of these two matters is not regulated in existing laws and regulations, so that the information dissemination plan and dissemination of the information must be carried out to the community itself. In line with developments in technology and information systems that have entered the era of media convergence, the acceleration of the process of spreading government programs can also be done by using this technology. The SECI method model (Socialization, Externalization, Combination, Internalization) was developed through implementation based on the 'Knowledge Management System Cycle' theory, so that a knowledge management system was formed. The results of research on community preparedness in the application of Knowledge Management Systems (KMS) for natural disaster preparedness and mitigation can be used to support the dissemination and dissemination of disaster management mitigation, global warming, and community-based climate change, including performance measurement of success.

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Data annotation system for intelligent energy conservator in smart building

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IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Bens Pardamean Tjeng Wawan Cenggoro Bloomest Jansen Chandra Reza Rahutomo Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department College of Letters and Science University of Wisconsin 53706 Madison WI USA

The concept of smart building includes the optimization of energy usage in a building. One of the possible solutions for this is to adaptively adjust appliances utilization according to activity level in the building. Thus, an intelligent activity estimation system needs to be developed. However, massive annotated dataset is necessary to train the system. Therefore, we propose a system that enables rapid data annotation to collect the massive dataset. With the proposed system, an image can be annotated within 4.8 seconds in average.

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Measuring the quality of various version an object-oriented software utilizing CK metrics 1

Measuring the quality of various version an object-oriented ...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Binanto, Iwan Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Abdurachman, Edi Soewito, Benfano Informatics Department Faculty of Scence and Engineering Sanata Dharma University Yogyakarta55002 Indonesia Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

There are many object-oriented software quality measurement techniques. One of them is CK metric. This paper utilizes CK metrics to measure qualities per version of an open source software namely Statcato. Measurements are done in each class, each version of the software. The measurement is used to analyze the quality of the software. This paper concludes that the quality of software has improved during its lifecycle, although its features increase. © 2018 IEEE.

关键词： Open source software

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Clustering Steam User Behavior Data using K-Prototypes Algorithm

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Journal of Physics: Conference Series 2019年第1期1367卷 012018-012018页

作者： Kiefer, Stefano Ranti Salim, Kelvin Girsang, Abba Suganda Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

The use of user telemetry to gather player behavioral data on video games can be very beneficial to game developers with a certain business model. With the help of user telemetry in game development, it can provide access to data on user behavior from installed game clients platform such as Steam. These behavioral data can be used to find out the Steam user behavioral patterns on playtime distributions that can be studied by developers in order to have a deeper understanding of the behaviors of their players. In this study, the data are clustered using the k-prototypes algorithm, a combination of k-means and k-modes algorithm that can be used to cluster mixed attributes. The result shows that the clusters represent the types and preferences of the players.

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Ecological Show Cave and Wild Cave: Negative Binomial Gllvm's Arthropod Community Modelling 3

Ecological Show Cave and Wild Cave: Negative Binomial Gllvm'...

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

作者： Caraka, Rezzy Eko Shohaimi, Shamarina Kurniawan, Isma Dwi Herliansyah, Riki Budiarto, Arif Sari, Shinta Purnama Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia Department of Statistics Padjadjaran University Indonesia Department of Biology UIN Sunan Gunung Djati Bandung Indonesia Kalimantan Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Ecology is a branch of biology that studies the interaction and relationship between organisms and their environment. Abundance, distribution of organisms and patterns of biodiversity are great interests for many ecologists. One of interesting ecosystems to be studied is a cave. A cave has a typical environment character with a vulnerable ecosystem. Many caves in Indonesia, particularly in Gunungsewu karst area have been developed into tourist objects (show caves) and managed imprudently. Such cave management has potential to harm the environment and leads to ecosystem destruction. Arthropods are the most abundance fauna in cave that play critical roles in maintaining cave ecosystems equilibrium. In the heart of statistical ecology, we need to analyze the differences on Arthropods community and abiotic (climatic-edaphic) parameters among show caves and wild caves. Statistical techniques are needed for the extraction of such information. GLLVM is one method that is able to explain spatial-based information and is particularly suitable for ecology. In this paper, we use negative binomial models to see the differences on spatial patterns of predator and decomposer Arthropods, also characteristic of edaphic and climatic in each cave. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Caves

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Fast artificial bee colony for clustering

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Informatica (Slovenia) 2018年第2期42卷 211-219页

作者： Girsang, Abba Suganda Muliono, Yohan Fanny, Fanny Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Artificial Bee Colony (ABC) is one of good heuristic intelligent algorithm to solve optimization problem including clustering. Generally, the heuristic algorithm will take the high computation time to solve optimization problem. Likewise, ABC also consumes too much time to solve clustering problem. This paper intends solving clustering problem using ABC with focusing reduction computation time called FABCC. This idea proposes detecting the pattern of redundant process then compacting it to effective process to diminish the computation process. There are five data sets to be used to prove the performance of FABCC. The results shows that FABCC is effective to prune the duration process up to 46.58 %. © 2018 Slovene Society Informatika. All rights reserved.

关键词： Heuristic algorithms

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Extended-RSA for Encryption Process to Improve Application Server Availability

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IOP Conference Series: Materials science and Engineering 2019年第1期598卷

作者： A Susanto Herman M I Putranto D N Utama A Wibowo Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Every enterprise stores and operates its transactions confidentially, therefore it has to encrypt the transaction to protect it from data intruders. Technically, most encryption processes are ranging from hundreds of milliseconds. If there is a lot of encrypting process, then the performance will be getting bottleneck and the transaction's speed is being slowed down. In this paper, a promising scheme by adding GZIP compression on the former RSA encryption method to increase speed is proposed; thus every transaction is going to require less times, therefore the number of failed transactions or requests will be reduced. Hence, this way makes the transaction easier for customers to do. The result of little experimental test shows that using XOR to stream cipher-text to replace the absent of padding into specific bytes shows a lot of performance increase resulting other factors such as availability also affected without sacrificing the security level.

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An initial research on Halstead's technique for pattern similarity relationship study 1

An initial research on Halstead's technique for pattern simi...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Denny Prabowo, Yulius Warnas, Harco Leslie Hendric Spits Gaol, Ford Lumban Abdurachman, Edi Soewito, Benfano Informatics Departement Faculty of Creative Industry Institut Teknologi Dan Bisnis Kalbis Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

Halstead Complexity Measures is a software metrics introducted by Maurice Howard Halstead in 1977. This metrics used to identify measurable properties of the code and relation between them. Several measures can be calculated with this method are program vocabulary, program length, volume, difficulty and effort. In learning process, the final result obtained by students should be linear with the results obtained each time the students doing their exercises. This study aims to see the pattern similarity relationship between coding that students do on each exercise in term of difficulty, programming effort and programming time with the final value that they obtained. The experiment was done by giving the students three sets of exercise questions which were derived from the final problem, then each set of exercise code done by each students measured using halstead method and compare with the final grade obtained by each student. © 2018 IEEE.

关键词： Students

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