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Implementation of Database Massively Parallel Processing System to Build Scalability on Process Data Warehouse

Procedia computer science 2018年 135卷 68-79页

作者： Fajar Ciputra Daeng Bani Suharjito Diana Abba Suganda Girsang 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

The problem with telecommunications companies today is that transactional data is more extensive than existing source tables. This makes business reporting less efficient and overwhelms query processing results in data warehouses so that they do not meet business requirements. The fast and complex evolution of the digital world must be scalable to the data warehouse process, so that the authors implement it in the data warehouse using massive parallel processing (MPP) with the Greenplum database, so that business users can get reports faster and more optimally. This case study explains how the MPP system implements and measures the performance of the Greenplum database by performing complex queries in the data warehouse with parallel processing. Therefore, this case study analyzes whether the use of MPP systems can measure the scalability of throughput and the response time in the data warehouse so that system performance in the Greenplum database remains stable for daily, weekly, and monthly operations.

关键词： Data Warehouse Massively parallel processing Greenplum ETL

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Human Anatomy Learning Systems Using Augmented Reality on Mobile Application

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Procedia computer science 2018年 135卷 80-88页

作者： Michael H Kurniawan Suharjito Diana Gunawan Witjaksono 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

Students generally experience difficulties in learning human body anatomy due to constraints to visualize the body anatomy from 2D into 3D image. This research aims to develop a human anatomy learning system using augmented reality technology. By using this system, it is expected that students can easily understand the anatomy of the human body using a 3D image visualization. The method used in this system is augmented reality marker on mobile computing platform. The marker is captured by taking a picture. Then, the captured image is divided into pieces and the pattern is matched with images stored in the database. In this research, we use Floating Euphoria Framework and combine it with the SQLite database. Augmented reality anatomy system of the human body has features that can interactively display the whole body or parts of the human organs. To evaluate the usefulness of the application, we tested the augmented reality anatomy system with high school students and medical students for learning the anatomy of the human body. The results show that the human anatomy learning system with interactive augmented reality visualization helps students learn human anatomy more easily.

关键词： Augmented Reality Human Anatomy Learning Android Application

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Intelligent E-commerce for Special Needs

Intelligent E-commerce for Special Needs

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International Conference on Cyber and IT Service Management (CITSM)

作者： Diana Teresia Spits Warnars Leonardo Primadala Putra Logiansa Harco Leslie Hendric Spits Warnars Wiranto Herry Utomo School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computing President University Bekasi Indonesia

Special need is a person who need assistance for their disabilities which include medical, physical, mental or psychological such as person with autism, down syndrome, dyslexia, Attention Deficit Hyperactivity Disorder (ADHD), multiple sclerosis, schizophrenia, cystic fibrosis, cerebral palsy, muscular dystrophy, blindness, deafness, epilepsy, chronic asthma and so on. In this proposed research idea about intelligent E-commerce for special needs, we limited to four types of difficulties such as hearing difficulty, vision difficulty, language difficulty, and learning difficulty. In this paper, we interest in those special needs persons who can use e-commerce and how to model a system that can help them to joy and easy to join with e-commerce. For some, this intelligent e-commerce is not only for shopping only but will become part of their healing for special needs in order to engage with daily human activities and increase their daily confidence in life. This paper also a preliminary investigation that can be used for Ph.D. or Doctoral research degree who is interested in building e-commerce framework for people with a special need or disability.

关键词： Companies Machine learning Speech recognition Tools Pricing

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

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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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Mobile game Application for Religion engagement

Mobile game Application for Religion engagement

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International Congress on Applied Information Technology

作者： Dedy Prasetya Kristiadi Vindy Richard Sambera Andy Julianto Harco Leslie Hendric Spits Warnars Kiyota Hashimoto STMIK Raharja Tangerang Indonesia Game Application & Technology Program School of Computer Science Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Technology and Environment Prince Songkla University Phuket Campus Thailand

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Religion is a part of a fundamental human right to serve and worship their God according to their religion and belief. Mobile game application along with the development of mobile phone technology such as a smartphone, tablet, and laptop, can be used to increase the player or user interest to engage with religion thing. Using the mobile game application in mobile gadgets will expand quickly to install and use for religion engagement. The player can learn religion things with fun and entertain ways, where the player does not realize that they do something serious in an unserious way. This paper will explain the model system design for mobile game application for learning Catholicism in fun and entertaining way and for the first development was limited to only three Catholic catechisms such as bible learning, church lesson, and liturgy celebration. For the early development, three types of games were developed such as True or False game, Scramble words game, and multiple-choice game. The mobile game model was designed with a use case diagram, storyboard, and class diagram, where for the current implementation the mobile game application was implemented using a ten tables database.

关键词： Games Land mobile radio Random access memory computer science Mobile applications Mobile handsets Information systems

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Optimization Sentiments of Analysis from Tweets in myXLCare using Naïve Bayes Algorithm and Synthetic Minority Over Sampling Technique Method

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Journal of Physics: Conference Series 2020年第1期1471卷

作者： Dedi Dwi Saputra Windu Gata Nia Kusuma Wardhani Ketut Sakho Parthama Hendra Setiawan Sularso Budilaksono Dimas Yogatama Agus Hadiyatna Endah Putri Purnamasari Bryan Pratama Deny Novianti Master of Computer Science-Postgraduate Program Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Jakarta Indonesia Graduate School Master's Degree Computer Science Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Jakarta Indonesia Master Faculty of Computer Science-Postgraduate Program University of Mercubuana Jakarta Indonesia Graduate School Master's Degree Computer Science University Paramita Indonesia Jakarta Indonesia Graduate School Master's Degree Computer Science STMIK Bani Saleh Jakarta Indonesia Graduate School Master's Degree Computer Science University of Persada Indonesia YAI Jakarta Indonesia Graduate School Master's Degree Computer Science University of Gadjah Mada Jakarta Indonesia

Text mining can be used to classify opinions about complaints or not complaints experienced by XL customers. This study aims to find and compare classifications in the sentiments of analysis from the view of XL customers. This dataset was derived from tweets of XL customers written on myXLCare Twitter account. In text mining techniques, 'transform case', 'tokenize', 'token filters by length', 'n-gram', 'stemming' were used to build classification and sentiments of analysis. Gataframework tools were used to help during preprocessing and cleansing processes. RapidMiner is used to help create the sentiment of analysis to search and compare two different classifications methods between datasets using the Naïve Bayes algorithm only and Naïve Bayes algorithm with Synthetic Minority Over-sampling Technique (SMOTE). The results of the two methods in this study found that the highest results were using the Naïve Bayes algorithm with Synthetic Minority Over-sampling Technique (SMOTE) with an accuracy of 86.33%, precision 82.85%, and recall ratio 92.38%.

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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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Web Security and Vulnerability: A Literature Review

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Journal of Physics: Conference Series 2020年第2期1477卷

作者： H Yulianton H L H S Warnars B Soewito F L Gaol E Abdurachman Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Information Technology Universitas Stikubank Semarang Indonesia 50243

The web continues to grow and attacks against the web continue to increase. This paper focuses on the literature review on scanning web vulnerabilities and solutions to mitigate web attacks. Vulnerability scanning methods will be reviewed as well as frameworks for improving web security. This research is the basis for future work that will end with the elaboration of web scanning and security with the aim of proposing better innovations.

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A Hybrid Particle Swarm Optimization with Crossover and Mutation of Genetic Algorithm for Solving the Wide Constraint Problem

A Hybrid Particle Swarm Optimization with Crossover and Muta...

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International Congress on Applied Information Technology

作者： Herlawati Yaya Heryadi Lukas 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

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

When optimizing the spatial data, a lot of constraints should be handled. Some constraints might be too wide for a metaheuristic algorithm, e.g. particle swarm optimization, to allocate the candidate locations outside a wide constraint. However, particle swarm optimization notably has fast computation characteristic and many researchers used this method for optimizing their spatial data. In the other hand, genetic algorithm has not only better exploitation-characteristic performance in searching but also has mutation and crossover that was proven in this study can be overcome the wide constraint problem. To minimize the drawback of genetic algorithm, i.e. need many computation resources, the hybrid particle swarm optimization with genetic algorithm through the use of crossover and mutation was used. Half of lower fitness values from particle swarm optimization were optimized using crossover and mutation in genetic algorithm. After merging the results of both methods, the optimum location showed that the proposed method was able to allocate the land use in a case study area outside the wide constraint.

关键词： Genetic algorithms Optimization Particle swarm optimization Spatial databases Mathematical model computer science Linear programming

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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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