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Biclustering Method to Capture the Spatial Pattern and to Identify the Causes of Social Vulnerability in Indonesia: A New Recommendation for Disaster Mitigation Policy

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Procedia computer science 2019年 157卷 31-37页

作者： Puspita Anggraini Kaban Robert Kurniawan Rezzy Eko Caraka Bens Pardamean Budi Yuniarto Sukim Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia College of Informatics Chaoyang University of Technology Taichung City 41349 Taiwan (R.O.C.) Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Geographically, Indonesia is a meeting point of three continental plates. Scilicet, the Eurasian Plate, the Indo-Australian Plate, and the Pacific Plate. Therefore, Indonesia is part of the infamous volcanic zone called the ”Ring of Fire” and one of the areas prone to natural disasters such as volcanic eruptions, earthquakes, tsunamis, floods, and landslides. This study aims to capture the spatial pattern and identify the causes of social vulnerability in the districts/cities in Indonesia using the biclustering method. The data is extracted from the Indonesian National Socio-Economic Survey (SUSENAS) by BPS-Statistics in 2014. The biclustering result indicates that each district/city has its own social vulnerability characteristics and shows that the vulnerable aspects of each district/city are different. The adjacent observations tend to have social vulenrability characteristics. The results of this study can be used as a reference for national disaster mitigation policy in Indonesia.

关键词： biclustering disaster mitigation social vulnerability SoVI spatial pattern

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Fuzzy ecoDSS Development for Road Traffic Engineering 3

Fuzzy ecoDSS Development for Road Traffic Engineering

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

作者： Nurlatifani, Sofie Retnowardhani, Astari Utama, Ditdit Nugeraha UIN Syarif Hidayatullah Information System Jakarta Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program - Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

A road traffic engineering (RTE) is realistically required to reduce the road traffic congestion (RTC) degree. The congestion negatively affects not only to economy and physiology factors, but also for human environment and health. This paper methodologically represents the development of ecological decision support system based on the concept of fuzzy logic (Fuzzy ecoDSS) for RTE. Three types of core method operated here;fuzzy logic, water flow algorithm (WFA), and object oriented. The method fuzzy logic used to avoid the fuzziness in parameterizing and prioritize the parameters. The WFA approach functioned to replicate the flow of road traffic and optimize it thru RTE. Finally, the method object oriented benefited to analyze and design the constructed system. Thus, the simulation result exhibits the best decision alternative taken gives better air condition (more 200% than normal condition) and better road traffic velocity (more 2,200% than normal situation). © 2018 IEEE.

关键词： Decision support systems

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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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Development of smart public transportation system in Jakarta city based on integrated IoT platform 1

Development of smart public transportation system in Jakarta...

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

作者： Murad, Dina Fitria Abbas, Bahtiar Saleh Trisetyarso, Agung Suparta, Wayan Kang, Chul-Ho Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

Travel security, traffic congestion and the efficiency of the global transport sector are key issues in some developing countries. Jakarta is one of the big cities and is the capital of Indonesia. This study aims to provide solutions to congestion problems in the capital city by maximizing the intelligent transportation system, convenient and safe for passengers. This research finds the fact that people's need for Trans Jakarta is relatively high but in fact it is not directly proportional to the public interest towards the use of Trans Jakarta buses. This study finds issues related to the needs and expectations of the community using Trans Jakarta facilities. Not only convenience and security and cheap price offered but also the ease and speed in transacting. This research provides ideas related to the facilities provided by Trans Jakarta as one of public transportation owned by the government. Combining smart phones with the use of internet-based technology (IOT). This research proposed an integrated system (integration platform). The solution with IOT-based technology enhancements makes it easy to present all information about bus availability, bus scheduling, booking places and easy online payment. This study uses a comparative study related to the needs of passengers in using Trans Jakarta. This study found the need of passengers for the existence of an integrated system that presents all information and ease of public transportation access in the city of Jakarta. © 2018 IEEE.

关键词： Internet of things

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Evaluation of the used of visual electronic banking system application using UTAUT 2 in Bank Central Asia corporation 2

Evaluation of the used of visual electronic banking system a...

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2nd Nommensen International Conference on Technology and Engineering, NICTE 2018

作者： Fajar, Ahmad Nurul Johanes, Frits Septian Girsang, Abba Suganda Wang, Gunawan Information Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information System Management Bina Nusantara University Jakarta Indonesia Infor. Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

The purpose of this study is to determine the factors that encourage the use of visual electronic banking system (VEBS) application in Bank Central Asia Corporation, and provide an idea to increase the use of VEBS. This study using UTAUT 2 model approach. The primary data obtained from interviews, direct observation and questionnaires that distributed and processed using SEM-PLS. The results of this study provide qualitative calculation results of UTAUT 2 variable. The conclusion obtained that interest of the use of application VEBS affected by variables facilitating condition, performance expectancy and behavioral intention. From these conclusions this study provided an idea to the future development of application's features for more effective and efficient use. © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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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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Instant Messaging as Information Goldmines to Digital Forensic: A Systematic Review 3

Instant Messaging as Information Goldmines to Digital Forens...

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

作者： Sihombing, Harry Chandra Fajar, Ahmad Nurul Utama, Ditdit Nugeraha Mercu Buana University Master of Electrical Engineering Jakarta Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The use of instant messaging (IM) application is very communal among smartphone users, as it delivers ease in interaction and communication. The speed at which technologies, growth, and expansion of networks infrastructure for high-speed data networks (e.g. wifi, 4G, etc.) are changing and the high number of IM applications are available. IM application usage is significantly escalating, also for doing illegitimate purposes, particularly to organize and coordinate criminal acts. They are practically exploited by the criminality groups involved when they target and interact with the victims, or try to run away from criminal occurrences. By systematically conducting a review to understand and to investigate IM applications topic coming from a number of scientific sources (e.g. manuscripts, metadata, files, etc.), a broader picture and opportunity to regain the valuable evidence in the investigation is academically provided. © 2018 IEEE.

关键词： Smartphones

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Face Recognition Using Modified OpenFace

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Procedia computer science 2018年 135卷 510-517页

作者： Kevin Santoso Gede Putra Kusuma Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Face recognition is a widely utilized biometric method due to its natural and non-intrusive approach. Recently, deep learning networks using Triplet Loss have become a common framework for person identification and verification. In this paper, we present a new method on how to select appropriate hard-negatives for training using Triplet Loss. We show that, by incorporating pairs which would otherwise have been discarded yields better accuracy and performance. We also applied Adaptive Moment Estimation algorithm to mitigate the risk of early convergence due to the additional hard-negative pairs. In LFW verification benchmark, we managed to achieve an accuracy of 0.955 and AUC of 0.989 as opposed to 0.929 and 0.973 in the original OpenFace.

关键词： Face Recognition Deep Learning Triplet Loss Adam Algorithm OpenFace

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Business Intelligence Model to Analyze Social Media Information

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Procedia computer science 2018年 135卷 5-14页

作者： Parama Fadli Kurnia Suharjito Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Social media is a platform to share information that is very liked by everyone nowadays because some of the facilities that make it easier for us to communicate with each other, share documents, chat and even create a community. In addition, we can also analyze the content of social media by using several methods in data mining, so that we can get new the information to support decision making that can bring benefits to individuals and companies. The purpose of this research, to create a business intelligence dashboard to observe the performance of each Topic or channel of news posted to social media accounts such as Facebook and Twitter. Topical performance in social media is the number of Topics in articles posted to social media getting like, share, comment etc. To be able to know the Topic of a news post in social media, used some text classification techniques such as Naive Bayes, SVM and Decision Tree. The comparative results of the algorithms are taken which has the best accuracy of SVM for subsequent implementation in the data warehouse. Meanwhile, the business intelligence dashboard data source will be sourced from the data warehouses that have been made before.

关键词： Social Media Naive Bayes SVM Decision Tree Business Intelligence

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The prediction of scholarship recipients in higher education using k-Nearest neighbor algorithm 3

The prediction of scholarship recipients in higher education...

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3rd Annual Applied science and Engineering Conference, AASEC 2018

作者： Kurniadi, D. Abdurachman, E. Warnars, H.L.H.S. Suparta, W. Department of Informatics Sekolah Tinggi Teknologi Garut Jalan Mayor Syamsu 1 Garut44151 Indonesia Department of Computer Science Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

This article aims to implement the algorithm model of k-Nearest Neighbor (k-NN) in analyzing, predicting, and classifying students who have potentials to get scholarships in universities. The k-NN algorithm works by making a prediction based on the closest data points between the old data history as training data and the new data as testing data. The data collected totals 1018 students with 24 scholarship receiver candidate students are used as the dataset for the test purposes. The attributes used in the prediction process are a semester, parents' income, number of family dependents, and Cumulative Grade Point Average. The distance calculation of the value from testing attribute to each training attribute uses Euclidean Distance equation, while the test of the model accuracy value is calculated using Confusion Matrix. The results of the simulation of the prediction model show that the determining factor of training data from both the number and the variation of different values can improve the performance of the k-NN algorithm with the best accuracy rate of 95.83 percent in predicting students who have the greatest chance of getting the scholarship. © Published under licence by IOP Publishing Ltd.

关键词： Students

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