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Convolve4D: A Novelty Approach to Improve Convolutional Process

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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Proposed Autonomous Vehicle Framework for Safe Driving

Proposed Autonomous Vehicle Framework for Safe Driving

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International Conference on Cyber and IT Service Management (CITSM)

作者： Amadeus Suryo Winoto Michael Kristianus Brandon Linardi Harco Leslie Hendric Spits Warnars School of Computer Science BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The proposed idea to improve the usage of an autonomous vehicle to increase safe driving based on the DARPA project, which already has shown the bright future of the autonomous vehicle. This paper proposes a new idea regarding the sensors and the autonomous vehicle framework, such as the usage of some algorithms and new UI along with the data logger. Moreover, the use of a LIDAR sensor is extended, along with a stereo camera and also ultrasonic sensor to make it more precise. Then, a calibration system is made for the stereo camera, which will take help from the ultrasonic sensor. Not the only ultrasonic, camera, and LIDAR, and IMU and GPS sensor are used to know the angle of x, y, and z of our vehicle. Both IMU and GPS are helping in the perception and mostly in the RNDF Localization that will be used in the pathfinding, planning, and control. The global Dynamic-Window approach is applied for the path selection algorithm and combining it with the Autonomous System Approach. The speed selection algorithm will decide on the speed limit and the camera. Not only that but the implement the Inter-Vehicle Algorithm is implemented, which makes the vehicles can exchange information with the other vehicles in the radius of the vehicle. Which all of this together can make a safer driving environment, not only for cars but another vehicle as well. Hope this framework can be used for any other vehicle project and becoming the base of all autonomous vehicle.

关键词： Sensors Cameras Acoustics Autonomous vehicles Automobiles Laser radar Roads

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Sport Field Reservation Based on Mobile Application

Sport Field Reservation Based on Mobile Application

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International Conference on ICT For Smart Society (ICISS)

作者： Tonto Claudinus Made Prayoga Wicaksana Nicolas Kornelius Sitorus Marsa Ariqi Gustiandza Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda School of Computer Science Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

This paper presents the sports apps based on a mobile application that has a function to help the provider or the owner of the sports field and sports vendor to promote their business in the apps. Due to the popularity and convenience that mobile applications had and high interest from many people in having a healthy life, it is a great opportunity to combine both of them. Therefore, this study focusses to build mobile sports application using object-oriented analysis and design method, that could meet the demand of lots of peoples that wants to do a sport especially a ball sport. Otherwise, the application can help and support the community and public, especially for ball sports fans, to make reservations for the sports field easier without having to come to the location and also meet their sporting needs.

关键词： Sports Mobile applications Business Schedules computer science Real-time systems IEEE merchandise

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

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

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International Conference on Informatics and Computing (ICIC)

作者： Herlawati Yaya Heryadi Harco Leslie Hendric Spits Warnars Ford Lumban Gaol Edi Abdurachman Benfano Soewito BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

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.

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A literature review of crowd-counting system on convolutional neural network

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

作者： A Chrysler R Gunarso T Puteri H L H S Warnars Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480

With the proliferation usage of video surveillance for safety, traffic control, and privacy purposes and with the constant growth of population, it is important to keep monitoring using Closed-Circuit Television (CCTV). With new upcoming developed technologies, new systems and algorithms are introduced and implemented to the crowd counting system today retrieving live video surveillance from the CCTV. However, recent studies show that there are some challenges still faced regarding the crowd counting system which uses the density estimation. The problems that occurred have resulted from the inaccuracy of the system that is caused by several factors. Factors such as the perspective distortion which is caused by the lack of data training and the method such as face detection is an ineffective method to determine the population density. Studies proposed have projected the idea of developing a more robust crowd counting methodology by implementing crowd counting by detection, clustering, and regression. Implementing these methods using the Convolutional Neural Network (CNN) will better the result of the detection since in CNN the image can be inputted and it will undergo several layers which will result in the system being able to differentiate one image from the other. With CNN the process of crowd counting will be able to be more advanced.

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Analysis of Gender Identification in Bahasa Indonesia using Supervised Machine Learning Algorithm

Analysis of Gender Identification in Bahasa Indonesia using ...

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International Conference on Information and Communications Technology (ICOIACT)

作者： Evawaty Tanuar Edi Abdurachman Ford Lumban Gaol Lukas School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

The following topics are dealt with: learning (artificial intelligence); feature extraction; image classification; convolutional neural nets; pattern classification; support vector machines; medical image processing; ... 详细信息

ISBN: (数字)9781728173566

ISBN: (纸本)9781728173573

关键词： Support vector machines Machine learning algorithms Biometrics (access control) Signal processing algorithms Artificial neural networks Speech recognition Classification algorithms

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GOROdsm: Local Wisdom Inspired socioDSM for Reconstructing Public Facility

GOROdsm: Local Wisdom Inspired socioDSM for Reconstructing P...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Ditdit Nugeraha Utama Suharjito BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

Gotong royong (GORO) is an impressive cultural spirit of Indonesia. It means practically “working together” without considering their dissimilarities and disparities to solve a problem. Specifically in public facility construction, at some time the citizen have to work together to do so with their own capital and resources through donation activity. It occurs century by century. Based on that unique phenomenon, this paper proposes a decision support model (DSM) that fundamentally created based on the GORO spirit to reconstruct the damage. The model is able to suggest the most objective damaged public facility that should be rehabilitated first. The method fuzzy logic is the main method operated in this work. The object-oriented method was used to design and develop a model. The simulated-annealing was functioned as an optimization method to optimize a selected decision. Finally, the model was tested by using experimental data to see its running.

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Scoring Urban Sustainability as a Guidance and Self-Learning for City Planners

Scoring Urban Sustainability as a Guidance and Self-Learning...

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International Congress on Applied Information Technology

作者： Herlawati Yaya Heryadi Agung Trisetyarso Wayan Suparta Chul Ho Kang Bahtiar Saleh Abbas BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

City planners worldwide have tried to develop their cities following the concept of sustainable development. To allocate land use properly, the zoning method has been widely used, especially in densely populated cities, namely a kind of sustainable urban form with considers the mix of use/diversity of land use to minimize travel distance. This study proposes a method for calculating how much a city meets the sustainable urban forms based on compact city criteria, i.e. compatibility, dependency, and compactness. After the survey filling in compatibility and dependency scores for each land use, and compactness was calculated for each sub-district. Fuzzy C-Means clustering was used to cluster the result to classify other areas. In addition, this method can be used by planners to check whether their plans meet the concept of sustainable development or not.

关键词： Urban areas Sustainable development computer science Education Matrix converters Hospitals

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Prediction Diabetes Mellitus Using Decision Tree Models

Prediction Diabetes Mellitus Using Decision Tree Models

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International Congress on Applied Information Technology

作者： Aswan Supriyadi Sunge Harco Leslie Hendric S. Warnar Yaya Heryadi Edi Abdurachman Benfano Soewito Ford Lumban Gaol BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Health is an essential thing in human life, but Indonesian people are still far from the word healthy lifestyle. One disease that can be caused by an unhealthy lifestyle is diabetes mellitus that can cause many deaths. So far, there are many data in the hospital, but the data can not be maximized well even if it can be used to predict diabetes. The need for accuracy to produce better results. In conducting this test, the results obtained using C 4.5 only algorithm is 72.08%.

关键词： Diabetes Data mining computer science Classification algorithms Diseases Decision trees Testing

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An Enhanced-BLCA for Assessing Performance of Company's Growth

An Enhanced-BLCA for Assessing Performance of Company's Grow...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Ditdit Nugeraha Utama BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

This paper purposes an improved algorithm of the butterfly lifecycle for calculating the performance of the company's growth. Three types of change for the better are regarding mathematical model, conception in calculating the growth performance parameters, and also data operated practically for testing the proposed algorithm. Three simple stages of study conducted are previous study-re-analyzing and re-reviewing, mathematical model constructing, and model testing. Here, roulette-wheel technique was technically functioned to generate probability of positive and negative factor values; that influence the performance of artificial butterfly's metamorphoses process (also could affect the quality of butterfly finally). Nineteen mathematical equations successfully produced are able to perfect the previous algorithm, particularly in the detailed calculation of performance in every single stage of metamorphoses. Conclusively, a balanced scorecard approach adopted as conception in calculating the company's internal aspect performance that benefited from testing the new improved algorithm. Similar to the previous study, the company's external factors considered as well in stage of model testing.

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