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

作者： Utama, Ditdit Nugeraha Rustamaji, Eri Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia Information System Department Syarif Hidayatullah State Islamic University Jakart Indonesia

ISBN: (纸本)9781538658215

Human resources (HRs) performance appraisal is one of several parts of HRs planning. It plays the imperative role to encourage HRs to have a good spirit and become correctly loyal to institution. The major objective of research is to propose a constructed decision support model (DSM) for appraising the HRs performance. The methods object oriented, fuzzy logic, hill climbing, and survey are benefitted to be main methods of this study which respectively are used to analyze and design the constructed model, justify and analyze data values, optimize the suggested decision, and collect data. By scientifically taking into account four selected fundamental performance parameters (i.e. education, teaching capability, research, and community service), the study was conducted;where, the measurement of performance bonus for university lecturer is chosen as a research object. Specifically for collecting data, 35 university lecturers were occupied to estimate the significance level of parameters. The lecturers are coming from two faculties of UIN Syarif Hidayatullah (Jakarta, Indonesia);i.e. faculties of science and technology and communication. At last, the model is practically going to assist the decision makers to fairly assess HRs performance;and the study showed a simulation result of assessment based on forty empirical data of university lecturer. © 2018 IEEE.

关键词： Fuzzy logic

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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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Bioinformatics Pathway Analysis Pipeline for NGS Transcriptome Profile Data on Nasopharyngeal Carcinoma

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

作者： Digdo Sudigyo Gisti Rahmawati Dicka W. Setiasari Risky H. Poluan Tjeng Wawan Cenggoro Arif Budiarto Alam Ahmad Hidayat Sri R. Indrasari Afiahayati Sofia M. Haryana Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Study Program of Biotechnology Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Medicine Public Health and Nursing Gadjah Mada University Yogyakarta Indonesia 55281 Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Next-Generation Sequencing (NGS)-based genomics data have a huge potential to be used in transcriptomic profiling of Nasopharyngeal Carcinoma (NPC) to study the biosynthesis mechanism behind it. The high dimensionality of NGS data is the main challenge in performing the data analysis to extract useful information. In this workflow pipeline, memory-efficient Linux-based software such as HISAT2 and HTSeq are utilized to process the raw NGS data. Furthermore, Differential Expression Gene (DEG) list can be obtained by performing advanced analysis to the aligned Ribonucleic Acid (RNA) sequence using the edgeR protocol. This DEG list is one of the main inputs of biological pathway analysis that can be done in DAVID and PANTHER web-based software. Both tools generate a different pathway result related to inflammation.

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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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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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Information as a service on cloud computing technology: A review

Information as a service on cloud computing technology: A re...

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2018 International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2018

作者： Taryana, Ujang Fajar, Ahmad Nurul Utama, Ditdit Nugeraha Universitas Mercu Buana Jakarta Indonesia Information Systems Management Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department BINUS Bina Nusantara University Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia

ISBN: (纸本)9781538674222

Information as a service (IAS) allows any applications to access all types of information thru using the application interface. A service based on everything or 'anything as a service' or 'everything as a service' is a fundamental configuration of developing IAS term that has not been studied comprehensively yet before. Based on systematic review study and also immersed analysis, IAS is proposed as part of the emerging service and specified service in the cloud technology service evolution. Thus, IAS is academically possible to be attached in the cloud service model that is realized in the cloud computing technology. © 2018 IEEE.

关键词： Distributed database systems

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A Model Configuration of Social Media Text Mining for Projecting the Online-Commerce Transaction (Case: Twitter Tweets Scraping)

A Model Configuration of Social Media Text Mining for Projec...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Emil Robert Kaburuan Ang Swat Lin Lindawati Surjandy Siswantini Muhammad Ryanda Putra Ditdit Nugeraha Utama BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Faculty of Economics and Communication Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia UIN Syarif Hidayatullah Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Text mining is a process to extract data based on text. The source of text mining should be coming from social media users' activities; e.g. posting, fans page, group, hashtag, tweet, etc. As raw data and information, the text mining sources are able to be gold information to be operated for academic analyzing purposes. This paper proposes the Python-based model to scrape text from Twitter user's tweets and then analyze them to see the commerce and tax-income potency in purposely Indonesia. The mathematical and statistical methods are technically operated. The constructed model finally exhibited. Also, the information on sale-behavior and tax-income forecasts are able to be portrayed.

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Improvement of Jakarta's air quality during large scale social restriction

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

作者： R Rahutomo K Purwandari J W C Sigalingging B Pardamean Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta Indonesia 10720 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

After Large-Scale Social Restriction (PSBB) established in Jakarta, a change of air quality was indicated by the citizens. Representatives of Indonesia's Agency for Meteorology, Climatology, and Geophysics (BMKG) supported as the fact that mobility of Jakarta's citizen and commuters were reduced. With utilizing Weather Data Acquisition System managed by BMKG, this research compared fluctuations of Jakarta's air quality during two periods of time: Pre-PSBB and During-PSBB. This study proved that Jakarta's air quality has positively improved compared to the previous year, although in the lower range of unhealthy 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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