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Information Technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Faisal Asadi Gregorius Natanael Elwirehardja Joko Pebrianto Trinugroho Reza Rahutomo Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The Ministry of Health of Indonesia has referred to pre-eclampsia as one of the most severe diseases affecting women. As an urgency, it is crucial to administrate pre-eclampsia cases for disease prevention as a long-term national healthcare strategy. Regarding health science, case data was significant in developing research and innovation. However, the main problem regarding pre-eclampsia case administration is data handling, recording, and management incompetence. Hence, this research proposed a conceptual design of a database for pre-eclampsia case administration. The proposed design covered conceptual, logical, and physical design. We elaborate the concept into three concepts of pre-eclampsia disease: pre-treatment, treatment, and post-treatment. This study proposed a solution to gain more data and study pre-eclampsia disease in Indonesia.

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Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

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On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization

arXiv

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arXiv 2021年

作者： Luo, Yuetian Li, Xudong Zhang, Anru R. Data Science Institute University of Chicago United States School of Data Science Fudan University China Department of Biostatistics and Bioinformatics Duke University United States

In this paper, we propose a general procedure for establishing the geometric landscape connections of a Riemannian optimization problem under the embedded and quotient geometries. By applying the general procedure to the fixed-rank positive semidefinite (PSD) and general matrix optimization, we establish an exact Riemannian gradient connection under two geometries at every point on the manifold and sandwich inequalities between the spectra of Riemannian Hessians at Riemannian first-order stationary points (FOSPs). These results immediately imply an equivalence on the sets of Riemannian FOSPs, Riemannian second-order stationary points (SOSPs), and strict saddles of fixed-rank matrix optimization under the embedded and the quotient geometries. To the best of our knowledge, this is the first geometric landscape connection between the embedded and the quotient geometries for fixed-rank matrix optimization and it provides a concrete example of how these two geometries are connected in Riemannian optimization. In addition, the effects of the Riemannian metric and quotient structure on the landscape connection are discussed. We also observe an algorithmic connection between two geometries with some specific Riemannian metrics in fixed-rank matrix optimization: there is an equivalence between gradient flows under two geometries with shared spectra of Riemannian Hessians. A number of novel ideas and technical ingredients including a unified treatment for different Riemannian metrics, novel metrics for the Stiefel manifold, and new horizontal space representations under quotient geometries are developed to obtain our results. The results in this paper deepen our understanding of geometric and algorithmic connections of Riemannian optimization under different Riemannian geometries and provide a few new theoretical insights to unanswered questions in the literature. © 2021, CC BY-SA.

关键词： Geometry

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Machine Learning Implementations in Childhood Stunting Research: A Systematic Literature Review

Machine Learning Implementations in Childhood Stunting Resea...

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International Conference on Information Management and Technology (ICIMTech)

作者： Reza Rahutomo Gregorius Natanael Elwirehardja Mahmud Isnan Faisal Asadi Bens Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Childhood stunting is a condition anticipated to affect the growth potential of children under the age of five. With numerous stunting researches that have been conducted, stunting datasets are now widely available to facilitate stunting research. This provides an opportunity to implement machine learning (ML) principles to produce a broader insight or a novel technique in stunting prediction. A systematic literature review is necessary to discover the landscape of machine learning implementation in the application domain as a preliminary study for creating an effective research roadmap. This paper presents a systematic literature review (SLR) of 22 curated manuscripts that focuses on identifying the ML models applied in stunting research, as well as the datasets used in such studies that were published during 2017–2022. The SLR process found that ML principles have been applied in stunting research since 2017, and the diversity of ML implementation has become more varied in 2021–2022. In terms of ML models, XGBoost and Random Forest are recognized as the two most utilized models, and stunting prediction is the most common ML implementation. The majority of stunting research utilizing ML has been conducted in Indonesia. Although national survey data has been the most commonly utilized dataset in stunting research, researchers in Indonesia have shown a preference for utilizing data from regional or independent surveys. This study will be followed by developing a classifier model for stunted children using XGBoost and Random Forest algorithms. The model will be trained on a dataset generated from StuntingDB.

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Twitter-based text classification using svm for weather information system 6

Twitter-based text classification using svm for weather info...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Purwandari, Kartika Rahutomo, Reza Sigalingging, Join W. C. Ajy Kusuma, Mahisa Prasetyo, Aji Pardamean, Bens Research Center Bina Nusantara University Bioinformatics and Data Science Jakarta11480 Indonesia BMKG Meteorological Climatological and Geophysical Agency Database Center Division Jakarta10720 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

The popularity of social media amplified the amount of text data that is used to enrich text classification research with machine learning approach. The modernization in weather information system is needed to produce real-time weather information using the involvement of Twitter users. GetOldTweets was used to cover data acquisition from Twitter. Support Vector Machine (SVM) was deployed as a machine learning model for text classification. The result was delivered in Esri Maps features. It facilitated a social sensing for Indonesia weather information system by using Twitter posts from Indonesian users with 93% accuracy. © 2021 IEEE.

关键词： data acquisition

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Bayesian multinomial logistic normal models through marginally latent matrix-T processes

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2022年第1期23卷 255-296页

作者： Justin D. Silverman Kimberly Roche Zachary C. Holmes Lawrence A. David Sayan Mukherjee College of Information Science and Technology Department of Statistics and Institute for Computational and Data Science Penn State University University Park PA Program in Computational Biology and Bioinformatics Duke University Durham NC Department of Molecular Genetics and Microbiology Duke University Durham NC Department of Molecular Genetics and Microbiology and Center for Genomic and Computational Biology Duke University Durham NC Departments of Statistical Science Mathematics Computer Science Biostatistics & Bioinformatics Duke University Durham NC

Bayesian multinomial logistic-normal (MLN) models are popular for the analysis of sequence count data (e.g., microbiome or gene expression data) due to their ability to model multivariate count data with complex covariance structure. However, existing implementations of MLN models are limited to small datasets due to the non-conjugacy of the multinomial and logistic-normal distributions. Motivated by the need to develop efficient inference for Bayesian MLN models, we develop two key ideas. First, we develop the class of Marginally Latent Matrix-T Process (Marginally LTP) models. We demonstrate that many popular MLN models, including those with latent linear, non-linear, and dynamic linear structure are special cases of this class. Second, we develop an efficient inference scheme for Marginally LTP models with specific accelerations for the MLN subclass. Through application to MLN models, we demonstrate that our inference scheme are both highly accurate and often 4-5 orders of magnitude faster than MCMC.

关键词： Bayesian statistics multivariate analysis count data microbiome gene expression

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A Fast and Accurate Model of Thoracic Disease Detection by Integrating Attention Mechanism to a Lightweight Convolutional Neural Network

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Procedia Computer science 2021年 179卷 112-118页

作者： Branden Adam Sangeroki Tjeng Wawan Cenggoro Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

The utilization of Deep Learning, especially the Convolutional Neural Network (CNN), is currently the best approach for thoracic disease detection from Chest X-Ray images. However, CNN typically has a slow runtime, hence potentially can introduce a bottleneck in the healthcare that uses the technology. To answer the challenge, we proposed a model that integrates an attention mechanism to a lightweight CNN. The proposed model can run faster than the state-of-the-art thoracic disease detection model while having the second-best performance among the thoracic disease detection models.

关键词： chest x-ray thoracic disease deep learning attention mechanism convolutional neural network

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Expert system for oil palm leaves deficiency to support precision agriculture 6

Expert system for oil palm leaves deficiency to support prec...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Putra, Dian Pratama Bimantio, Prasanto Suparyanto, Teddy Pardamean, Bens Institute of Agriculture STIPER Agrotechnology Department Yogyakarta55281 Indonesia Institute of Agriculture STIPER Agricultural Engineering Department Yogyakarta55281 Indonesia Research Center Bina Nusantara University Bioinformatics and Data Science Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Expert systems are an option in the implementation of agricultural cultivation, which can provide comprehensive information to make crop cultivation more precise. The expert program currently used in oil palm plants is still unable to provide accurate information on actual deficiencies. Thus, there is a need for an expert system that can provide valid information. This research creates an expert system in agriculture that can help farmers to make decisions by knowing the types of nutrient deficiencies in oil palm. Besides that, it can help the process of disseminating information and knowledge through applications that can be accessed at any time by farmers to save time and money and support their existence. Edge detection using the Sobel method and the Robert method using the High Pass Filter (HPF) is the basis for this expert system creation method. This expert system can be used for any type of mature oil palm plant where yellow spots are found, due to a lack of nutrients or deficiency. Diseases that arise due to deficiencies depend on each nutrient, in this study all deficiencies are specific to the upper part of the plant, namely leaves. Tests carried out 15 times resulted in the deficiency most often raised by oil palm trees due to the lack of primary essential nutrients, namely nitrogen nutrients. The validation assessment is then carried out by an expert (human) directly and assesses the deficiency directly, then from the results of the test and assessment, there are 11 images from 15 images that match the assessment by the expert. © 2021 IEEE.

关键词： High pass filters

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Duck Eggs Hatching Procedure with A Low Cost User Convenient Integrated Device for Developing Countries 9

Duck Eggs Hatching Procedure with A Low Cost User Convenient...

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9th Edition of IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2021

作者： Hossain, Eftakhar Zeyad, Mohammad Ahmed, S.M. Masum Tasrif Anubhove, Md Sadik Computational Biology and Data Science Laboratory Bangladesh Energy and Technology Research Division Advanced Bioinformatics Chattogram Bangladesh Erasmus+ Joint MSC In Smart Cities and Communities Department of Thermal Engineering Bilbao Spain Mons Belgium

ISBN: (纸本)9781665432405

Poultry agriculture is a form of livestock farming that involves raising chickens, turkeys, ducks, etc, and raises them to provide eggs or meat. However, this work sheds light on the method of hatching duck eggs which maintains a suitable environment around the eggs through an automated and low cost device by controlling temperature (T) and relative humidity (RH). This paper presents a control strategy for automatic temperature and relative humidity control systems for the egg/s hatching procedure for rural areas people or unprivileged communities in the developing countries. One of the best outcomes of this work is the proper hatching procedure steps shown from the beginning to the end. Moreover, for a better understanding and outcomes, the research work has been done under a poultry farm in Charsita village, Lakshmipur, Bangladesh for 6 consecutive months of 2020. The experiment (egg/s hatching) has been conducted under an ice-box. Furthermore, a microcontroller (ATmega328p) is used to monitor the temperature and relative humidity by receiving data from the sensor DHT22 and manipulating the appropriate temperature and humidity using a logic algorithm code. Egg/s need a constant temperature and relative humidity of 35.6 °C to 37.8 °C and 60% to 80%, respectively. Nonetheless, an LCD (16*2) with a matrix keypad (4*4) has been integrated into the unit, allowing farmers to easily set, run, and monitor the appropriate temperature and relative humidity levels within the ice-box. Finally, the results of sensor testing, system device management, and performance rates are recorded to ensure the research's success. © 2021 IEEE.

关键词： Microcontrollers

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Lockdown strategy worth lives: The SEIRD modelling in COVID-19 outbreak in Indonesia 2

Lockdown strategy worth lives: The SEIRD modelling in COVID-...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Nurlaila, I. Hidayat, A.A. Pardamean, B. Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Lockdowns, despite their conflicting restrictions and consequences they might offer when enforced as a national strategy, are deemed to be suggestive for a prompt conquer to the Coronavirus Disease-19 (COVID-19) outbreak. There have been some success stories such as in China, South Korea and our ASEAN member fellow, Vietnam, which exhibited extremely fallen numbers of COVID-19 cases post the enforcement of lockdown. Indonesia, however, remains in the crux of dispute whether or not the lockdown is opted to force COVID-19 transmission down under control. We, in this respect, employ the most popular model which has been broadly applied in the field of epidemiology, referred to as SEIRD (Susceptible, Exposed, Infectious, Recovered, and Death), the extension form of an age-structured SEIR, where the Death (D) is included to provide more factual situation. We modify the I (Infectious) fraction as symp-tomatic (Is) and asymptomatic (Ia) infectives. There are three lockdown scenarios simulated in our modified SEIRD with the starting date are 26 April 2020 when the immediate lockdown was enacted-and a-week and two-week-gaps, respectively. We figured out that by stipulating the lockdown without delay (26 April 2020), the new cases could be kept below 10,000. A week delay escalates case number to 5,000 and delay for one more week results in beyond 20,000 new cases. Furthermore, when the intervention is delayed following the delayed lockdown, normalization would demand a longer period within which dealing with more critical and dying patients is unavoidable and should be more anticipated. © Published under licence by IOP Publishing Ltd.

关键词： Coronavirus

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