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

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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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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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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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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Anomaly Detection in Climate Data Using Stacked and Densely Connected Long Short-Term Memory Model

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Journal of computers (Taiwan) 2020年第4期31卷 42-53页

作者： Saleh Abbas, Bahtiar Wahyono, Teguh Heryadi, Yaya Soeparno, Haryono Doctor of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Industrial Engineering Bina Nusantara University Jakarta Indonesia

Climate anomalies are considered as an important factor closely related to many disasters causing many human losses, such as airline crash, wildfires, drought and flooding in many areas. Many researchers have projected that the rising global temperature will increase the draught, especially in the mid-latitude areas. Taking those problems into account, studies on anomaly detection in climate are crucial. While climate prediction aims to analyze and model regular pattern of climate, climate anomaly studies aim to model climate deviation from its previous general patterns. Long Short Term Memory (LSTM) is a method employed in this research because it has been proven to work effectively in several anomaly detection studies, especially for data with similar characteristics. This paper presents empirical results of using Basic LSTM, Densely Connected (DC) LSTM, and Stacked-DC LSTM models to detect temperature anomaly as a manifestation of climate change in Semarang City. The results show that Stacked DC LSTM produced higher accuracy in detecting anomaly than the other two methods. © 2020 computer Society of the Republic of China. All rights reserved.

关键词： Long short-term memory

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PROMOTING TIMOR LESTE’S TAIS CLOTH USING MOBILE AUGMENTED REALITY APPLICATION

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Procedia computer science 2018年 135卷 700-706页

作者： Marianus Magno Seran Bria Gede Putra Kusuma Louis Khrisna Putera Suryapranata Computer Science Department BINUS Graduate Program - Master 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

The results of observations showed that the book about Tais produced by Secretariat de Estado da Arte e Cultura (SEAC) has not been able to meet the needs of users because the information is less interesting and interactive. This paper’s aim is to introduce the more interesting and interactive way to introduce Tais. Utilization of Augmented Reality (AR) technology in an application built with the Unity3D program is done to provide different way in presenting interesting and interactive information to its users. Based on the results in this paper, the developed application can handle the presentation in more interesting and interactive way. The ideal distance in the tracking process for target objects with size 7 x 6 cm is ranged from 6 cm to 30 cm, with the image ratio that can be detected at the farthest distance is 4% of the camera image. For the detection angle, the target object can be detected properly from approximately ±64 0 . From the data acquired, it can be said that AR can be used to introduce Tais in more interesting and interactive way.

关键词： augmented reality mobile application tais timor leste cultural heritage

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Facial Recognition Development to Detect Corporate Employees Stress Level

Facial Recognition Development to Detect Corporate Employees...

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2019 IEEE International Conference on Engineering, Technology and Education, TALE 2019

作者： Rahman, Munif Faisol Abdul Vincent Giovanni, Vito Christian Warnars, Harco Leslie Hendric Spits Aryono, Gagah Dwiki Putra Megantoro, Bayu Sasmoko Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Smk Pgri of Serang city Serang42117 Indonesia Sman 2 of Bekasi city Bekasi17144 Indonesia Faculty of Humanities Bina Nusantara University Primary Teacher Education Department Jakarta11480 Indonesia

ISBN: (纸本)9781728126654

Technology has developed so well even to the point where machines can recognize our faces. There many APIs and algorithms out there that can recognize human faces. These APIs or algorithms is called Artificial Intelligence or AI. As modern civilian life in modern society, AI has been used so many times and developed into something more. This time, we proposed an idea to recognize motions and emotions on human faces to detect their stress levels. Companies nowadays need to have something that can know how their employees are feeling or think about their work. This program works by taking an image input from mounted cameras on the office's monitor. However, before that, the program must have been trained first to recognize faces and emotions. For this, the eigenfaces algorithm is used. After the input is received, then the program will process the image received and extract the features from the images such as eyes, nose, mouth, etc. to detect if there are faces and also the emotions of the face. After that, the features extracted will be matched with the features in the database to give an output of the percentage of stress. © 2019 IEEE.

关键词： Neural networks

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Code-mixed sentiment analysis of Indonesian language and Javanese language using Lexicon based approach

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Journal of Physics: Conference Series 2021年第1期1869卷

作者： C Tho Y Heryadi L Lukas A Wibowo Department of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach is one of the approaches in extracting the sentiment analysis. This study is aimed to compare two lexicon models which are SentiNetWord and VADER in extracting the polarity of the code-mixed sentences in Indonesian language and Javanese language. 3,963 tweets were gathered from two accounts that provide code-mixed tweets. Pre-processing such as removing duplicates, translating to English, filter special characters, transform lower case and filter stop words were conducted on the tweets. Positive and negative word score from lexicon model was then calculated using simple mathematic formula in order to classify the polarity. By comparing with the manual labelling, the result showed that SentiNetWord perform better than VADER in negative sentiments. However, both of the lexicon model did not perform well in neutral and positive sentiments. On overall performance, VADER showed better performance than SentiNetWord. This study showed that the reason for the misclassified was that most of Indonesian language and Javanese language consist of words that were considered as positive in both Lexicon model.

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Mobile Patient Application for Outpatient 4

Mobile Patient Application for Outpatient

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Kristiadi, Dedy Prasetya Hasanudin, Muhaimin Sutrisno Salim, Jennifer Gunawan, Michael Glenn Laurence, Angeline Chandra, Antoni Hendric Spits Warnars, Harco Leslie Mantoro, Teddy Computer Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Faculty of Science and Technology Sampoerna University Jakarta12780 Indonesia

ISBN: (纸本)9781728122076

We as a human can not avoid the disease, and when we are sick, we need to see a practical doctor. However, in term of location and patient's right for changing the practical doctor, then the patient when moving from one practical doctor to others will have similar and repeated questions such as medicine allergy, history of diseases and so on. Moreover, become a problem for a vulnerable patient such as unconscious patient, disabled or elderly when seeing a new practical doctor and at the end of the day, it will become malpractice. Few of the causes of the problem above are the lack of health education, delay in diagnosing/misdiagnosis, and inaccessible healthcare facilities and with the increasing popularity of telemedicine and IoT across the world, then we need to apply IoT in order to help the patient. In this paper, a framework is created and designed for an IoT-integrated mobile application for the patient where this mobile application is expected to be implemented. © 2019 IEEE.

关键词： Internet of things

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The data warehouse for guarantee of objects in the fiduciary

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： Frabowo Prasetia Parlindungan Tampubolon Arif Rahman Hakim Abba Suganda Girsang Roni Jhonson Simamora Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Barat 11480 Indonesia Universitas Methodist Indonesia Medan Sumatera Utara Indonesia

The data warehouse is a structured data environment for decision support systems (DSS) and online analytical application data sources. Finance the guarantee data is extremely important because this data is checked you will be State-run finance is already good or less good, already underway in accordance with standard operational procedures. Show case of branches; see the status of data has been done by each branch, the amount of any status on a branch that has performed guarantee. The data of the vehicle that has been issued by a fiduciary as well as consumers who have made the assurance to the fiduciary. The methods used in this paper are to follow nine step. The objectives to be achieved from this paper so that the resulting data can answer the question of fiduciary business process, by generating the dashboard as a faster visualization on understanding and a report

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