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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Isnan, Mahmud Hidayat, Alam Ahmad Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Department of Mathematics School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Classification of Indonesian crops is a critical task in developing farming and getting more understanding of agriculture. However, there is no clear task in classifying types of crops in Indonesia. Transfer learning has been used successfully in a variety of image classification applications. Thus, in this paper, we collected images of Indonesian crops from the internet randomly and proposed a classification by using transfer learning of deep learning with four pre-trained models: EffficientNetB0, ResNet18, VGG19, and AlexNet. In the experiment, augmentation techniques such as random horizontal flip, random vertical flip, and random affine were utilized to prevent the network from overfitting. The result found that EfficientNet-B0 outperformed other models with an accuracy of 82.55. Then, the model struggled to distinguish between crops in the same family. According to the results, although transfer learning can work well to classify images of Indonesian agricultural crops, some improvements are still required to address existing issues. © 2023 The Authors. Published by Elsevier B.V.

关键词： Agriculture Classification Crop Deep Learning Transfer learning

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Users' interest assessment on job portal

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International Journal of Web Portals 2014年第1期6卷 64-75页

作者： Sudiana Pardamean, Bens Computer Science Graduate Program Bina Nusantara University Jakarta Indonesia Bioinformatics Research Group Bina Nusantara University Jakarta Indonesia

Job portal is considerably useful for both job seekers and employers. It enables job seekers to look for an employment, to advance their careers, or to market themselves. As for the employers, they can post vacant positions to be filled with suitable employees. A certain job portal received numerous complaints regarding its features that were unable to fulfill the users' needs. These complaints led to the decrease of the number of users. A study was conducted to determine factors that influenced users' interest by referring to the 7C framework. Questionnaires were distributed to numerous job seekers and employers. The data were analyzed using multiple linear regression technique. Chi-square analysis was also performed to further analyze which elements of the 7C framework were essential for the users. The results showed that only four out of seven elements from the framework affected the users' choice towards job portal, namely the context, the content, the community, and the commerce. Copyright © 2014, IGI Global.

关键词： Commerce

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Count-Data Mixed Models of Topical Tweets: A Case of Indonesia Flood Events 8

Count-Data Mixed Models of Topical Tweets: A Case of Indones...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Hidayat, Alam Ahmad Pardamean, Bens Mathematics Department School of Computer Science 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 Program Bina Nusantara University Jakarta11480 Indonesia

Examining topic-level variability in modeling Twitter data can potentially yield more comprehensive insights into public perception during critical periods, thereby enhancing natural disaster mitigation and surveillance efforts. In this study, we utilized generalized linear mixed models (GLMMs) to illustrate the variability in tweet counts related to specific topics in Indonesia during the flood events that occurred in February 2021. The glmmTMB library in R was employed for this purpose. The data were assumed to follow two distinct exponential distributions: Poisson and Negative Binomial. To incorporate random effects, random intercepts and random slopes were introduced, allowing them to vary randomly across topics in the initial two models. Additionally, the final model addressed issues related to dispersion and zero-inflation. By evaluating the Akaike Information Criteria scores, we determined that a model based on the Negative Binomial distribution with random zero-inflation intercepts best fit the data. The chosen model formulation and the estimated parameters have the potential to forecast topic-specific trends in Indonesian flood-related Twitter data. © 2023 The Authors. Published by Elsevier B.V.

关键词： count data disaster surveillance floods mixed models Twitter

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A spatial genome aligner for resolving chromatin architectures from multiplexed DNA FISH (Jan, 10.1038/s41587-022-01568-9, 2023)

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NATURE BIOTECHNOLOGY 2023年第7期41卷 1027-1027页

作者： Jia, Bojing Blair Jussila, Adam Kern, Colin Zhu, Quan Ren, Bing Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Medical Scientist Training Program University of California San Diego La Jolla CA USA Department of Cellular and Molecular Medicine Center for Epigenomics University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Institute of Genomic Medicine Moores Cancer Center School of Medicine University of California San Diego La Jolla CA USA

Multiplexed fluorescence in situ hybridization (FISH) is a widely used approach for analyzing three-dimensional genome organization, but it is challenging to derive chromosomal conformations from noisy fluorescence signals, and tracing chromatin is not straightforward. Here we report a spatial genome aligner that parses true chromatin signal from noise by aligning signals to a DNA polymer model. Using genomic distances separating imaged loci, our aligner estimates spatial distances expected to separate loci on a polymer in three-dimensional space. Our aligner then evaluates the physical probability observed signals belonging to these loci are connected, thereby tracing chromatin structures. We demonstrate that this spatial genome aligner can efficiently model chromosome architectures from DNA FISH data across multiple scales and be used to predict chromosome ploidies de novo in interphase cells. Reprocessing of previous whole-genome chromosome tracing data with this method indicates the spatial aggregation of sister chromatids in S/G2 phase cells in asynchronous mouse embryonic stem cells and provides evidence for extranumerary chromosomes that remain tightly paired in postmitotic neurons of the adult mouse cortex.

关键词： Stem cells

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MetaPathways v2.0: A master-worker model for environmental Pathway/Genome Database construction on grids and clouds

MetaPathways v2.0: A master-worker model for environmental P...

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IEEE Symposium on Computational Intelligence and bioinformatics and Computational Biology (CIBCB)

作者： Niels W. Hanson Kishori M. Konwar Shang-Ju Wu Steven J. Hallam Graduate Program in Bioinformatics University of British Columbia Canada Department of Microbiology & Immunology University of British Columbia Canada

The development of high-throughput sequencing technologies over the past decade has generated a tidal wave of environmental sequence information from a variety of natural and human engineered ecosystems. The resulting flood of information into public databases and archived sequencing projects has exponentially expanded computational resource requirements rendering most local homology-based search methods inefficient. We recently introduced MetaPathways v1.0, a modular annotation and analysis pipeline for constructing environmental Pathway/Genome Databases (ePGDBs) from environmental sequence information capable of using the Sun Grid engine for external resource partitioning. However, a command-line interface and facile task management introduced user activation barriers with concomitant decrease in fault tolerance. Here we present MetaPathways v2.0 incorporating a graphical user interface (GUI) and refined task management methods. The MetaPathways GUI provides an intuitive display for setup and process monitoring and supports interactive data visualization and sub-setting via a custom Knowledge Engine data structure. A master-worker model is adopted for task management allowing users to scavenge computational results from a number of worker grids in an ad hoc, asynchronous, distributed network that dramatically increases fault tolerance. This model facilitates the use of EC2 instances extending ePGDB construction to the Amazon Elastic Cloud.

关键词： Engines Databases Data structures Graphical user interfaces Monitoring Computational modeling Pipelines

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Enhanced expression of β3-galactosyltransferase 5 activity is sufficient to induce in vivo synthesis of extended type 1 chains on lactosylceramides of selected human colonic carcinoma cell lines

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Glycobiology 2009年第4期19卷 418-427页

作者： Lin, Chi-Hung Fan, Yao-Yun Chen, Yen-Ying Wang, Shih-Hsin Chen, Chun-I Yu, Lung-Chih Khoo, Kay-Hooi Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Institute of Bioinformatics and Structural Biology National Tsing-Hua University Hsinchu 300 Taiwan Institute of Biological Chemistry Academia Sinica Nankang Taipei 115 Taiwan Taiwan and Institute of Biochemical Science National Taiwan University Taipei 106 Taiwan

In general, an elevated expression of β3-galactosyltrans-ferase (β3GalT) activity contributed by β3GalT5 correlates well with increased biosynthesis and expression of type 1 chain (Galβ1-3GlcNAcβ1-) derivatives such as Lewis A and sialyl Lewis A, which are mostly recognized as terminal epitopes and not further extended. Most known β3-N-acetylglucosaminyltransferases show a higher activity toward extending type 2 chain (Galβ1-4GlcNAcβ1-), and an over-expression of β3GalT5 could suppress the formation of the type 2 chain poly-N- acetyllactosaminoglycans. The potential of extending instead the predominant type 1 chain termini synthesized under such circumstances was, however, not investigated, partly due to technical difficulty in unambiguous identification of extended type 1 chains. Using an advanced mass spectrometry-based glycomic mapping and glycan sequencing approach, we show here that type 1 chains carried on the lacto-series glycosphingolipids of colonic carcinoma cells can be extended when the endogenous β3GalT activity relative to competing β4GalT activity, as defined against a common GlcNAcβ1-3Galβ1-4Glc acceptor, is sufficiently high, as found in Colo205 and SW1116, but not in DLD-1 cells. In support of this positive correlation, the lacto-series glycosphingolipids isolated from stably transfected DLD-1 clones over-expressing β3GalT5 were shown to comprise fucosylated dimeric type 1 chains, whereas a mock transfectant and the DLD-1 parent carried only fucosylated dimeric type 2 chains on their lactosylceramides. It suggests that while the natural expression of extended type 1 chain is likely to be determined by many contributing factors including the relative amounts of competing glycosyltransferases and the UDP-Gal level, the enhanced expression of β3GalT5 is sufficient to promote in vivo extension of type 1 chains by furnishing a significantly higher amount of type 1 chain precursors relative to competing type 2 chains. © The Author 2009. Published by Oxfo

关键词： β3-galactosyltransferase β3GalT5 Extended type 1 chain Glycomics Mass spectrometry

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Data mining for epidemiology: The correlation of typhoid fever occurrence and environmental factors 7

Data mining for epidemiology: The correlation of typhoid fev...

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7th International Conference on Computer Science and Computational Intelligence, CSCI 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Typhoid fever is an endemic disease that burdens Indonesia and has a potentially fatal infection multisystem. Salmonella typhi bacterium is responsible for typhoid fever disease. Poor sanitation, crowding, and slums are the main factors of increasing typhoid fever incidences. Environmental factors directly connected to meteorological factors are the main factor in breeding the Salmonella typhi bacterium. This study aims to identify the correlation between meteorological parameters and typhoid fever disease occurrence. The study was carried out in Jakarta, Indonesia, and the Bureau of Meteorological, Climatology, and Geophysics (BMKG) provided the meteorological parameter data. In addition, the Jakarta health surveillance office provided information on typhoid fever hospitalizations from 2019 to 2021. Pearson's concept was utilized d to investigate the correlation between typhoid fever incidences and the meteorological parameters. Humidity, precipitation, and wind speed are the meteorological parameters that significantly affect in contribute to the occurrence of typhoid fever disease. These findings might be used as a reference for Indonesia's government in making public policy to prevent typhoid fever in Indonesia. © 2022 Elsevier B.V.. All rights reserved.

关键词： Data mining

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Sentiment Analysis for TikTok Review Using VADER Sentiment and SVM Model 8

Sentiment Analysis for TikTok Review Using VADER Sentiment a...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Isnan, Mahmud Elwirehardja, Gregorius Natanael Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

TikTok, a social networking site for uploading short videos, has become one of the most popular. Despite this, not all users are happy with the app;there are criticisms and suggestions, one of which is reviewed via the TikTok app on the Google Play Store. The reviews were extracted and then used for training a sentiment analysis model. The VADER sentiment method was utilized to offer the review's initial labeling (positive, neutral, and negative). The result revealed that most reviews were classified as positive, meaning that the data were imbalanced and challenging to handle in further analysis. Therefore, Random Under-sampling (RUS) and Random Over-sampling (ROS) methods were deployed to deal with that condition. The labeled reviews were subsequently pre-processed using tools such as case folding, noise removal, normalization, and stopwords before being used for training a Support Vector Machine (SVM) model for sentiment classification. The SVM trained without resampling produced the most favorable results, with an F1-score of 0.80. © 2023 The Authors. Published by Elsevier B.V.

关键词： Google Play Store Sentiment Analysis SVM TikTok VADER Sentiment

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A systematic literature review of machine learning application in COVID-19 medical image classification 7

A systematic literature review of machine learning applicati...

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7th International Conference on Computer Science and Computational Intelligence, CSCI 2022

作者： Daniel Cenggoro, Tjeng Wawan Pardamean, Bens Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Detecting COVID-19 as early as possible and quickly is one way to stop the spread of COVID-19. Machine learning development can help to diagnose COVID-19 more quickly and accurately. This report aims to find out how far research has progressed and what lessons can be learned for future research in this sector. By filtering titles, abstracts, and content in the Google Scholar database, this literature review was able to find 19 related papers to answer two research questions, i.e. what medical images are commonly used for COVID-19 classification and what are the methods for COVID-19 classification. According to the findings, chest X-ray were the most commonly used data to categorize COVID-19 and transfer learning techniques were the method used in this study. Researchers also concluded that lung segmentation and use of multimodal data could improve performance. © 2022 Elsevier B.V.. All rights reserved.

关键词： COVID-19

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Sentiment Analysis: Indonesia Netflix User's Comment Using Multiple Lexicon-Based Dictionaries 4

Sentiment Analysis: Indonesia Netflix User's Comment Using M...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Mola, Sebastianus Adi Santoso Widiastuti, Tiwuk Roma, Rosa V. K. Isabela Ohe Karnyoto, Andrea Stevens Pardamean, Bens University of Nusa Cendana Faculty of Science and Engineering Kupang Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

A subscription movie streaming service from the United States, Netflix, has been present in Indonesia since 2016 and provides a wide variety of films without showing any single advertisements that can be viewed from anywhere, as long as there is access to the internet. Despite these advantages, many users have complained through the Google Play Store's comments column. Some of the common complaints include frequent buffering and connectivity issues, dissatisfaction with the limited selection of Indonesian movies, lack of subtitles for specific languages, or pricing concerns have also been raised. In this study developed two combined scenario methods using the InSet and SentiStrength-id dictionary to obtain better performance and compare them against independent InSet and SentiStrength-id. This study collected users' comments for the Netflix app in the Google Play Store as a dataset using web scraping techniques through the Google Collaboration tool. The dataset contains 3250 rows spanning the period from January 22, 2024, through June 6, 2024. To ensure proper processing of the text, data cleaning, lowercasing, normalization, tokenization, stemming, and stopwords removal are conducted. The results show that most user opinions are negative. The InSet dictionary has an accuracy of 92%, SentiStrength-id 78%, Combined scenario 1 is 87%, and scenario 2 reaches the highest among others which is 92.52%. © 2024 IEEE.

关键词： Video streaming

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