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International Conference on Information Management and Technology (ICIMTech)

作者： Kartika Purwandari Join W. C. Sigalingging Muhammad Fhadli Shinta Nur Arizky Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia National Central University Taoyuan Taiwan BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Managing customer satisfaction has become an important business trend, including restaurants business. This study aims to determine the application of the K-means, Spectral Clustering (SC), and Agglomerative Clustering (AC) method for measuring customer satisfaction on a family restaurant in Taiwan. We contribute the data collection process and application of data mining in a family restaurant. The clustering analysis based on agglomerative clustering approach performs as well as the K-means approach to cluster the same characteristics of the customers. At last, this study shows the measurement result of customer satisfaction and provides improvement suggestion to the restaurant concerned.

关键词： Data mining Customer satisfaction Principal component analysis Computer science Reliability Data visualization

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Provoking Tweets by Indonesia Media Twitter in the Initial Month of Coronavirus Disease Hit

Provoking Tweets by Indonesia Media Twitter in the Initial M...

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International Conference on Information Management and Technology (ICIMTech)

作者： Ika Nurlaila Reza Rahutomo Kartika Purwandari Bens Pardamean BINUS Online Learning Bina Nusantara University Jakarta Indonesia Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

After months in denial, on 2 nd March 2020 the first case of COVID-19 in Indonesia was announced and soon was declared as a national pandemic. COVID-19 was since being the headlines of the news offline and online. This trigger either positive or negative responses from the readers, which in turn affect at least the depth of understanding and furthermore the effectiveness of any enforced intervention taken with the purpose to control the transmission of the COVID-19. In order to assess how likely the COVID-19-containing news being forwarded to reach more readers and how the pertinent news bridge further virtual interaction, we crawled data from Twitter as the major online microblogging platform to analyze how likely COVID-19-containing tweets were echoed and what typical tweet about COVID-19 that gained attentions. This is critical to evaluate how people virtually responded against the tweets. Our analyzed data is visualized using Matplotlib by Python and Graph Prism8 accordingly. We figured out that timing and number of followers are not determinative for the tweets being retweeted. Instead, provoking headline add likelihood for the tweets to be moving forward. Also appeared in our analysis that the top two media (Detik and Kompas) shared the same proportion on their tweet type fractions on where information dominated the fraction of their tweets.

关键词： Twitter Media Corona Tagging Diseases Data visualization

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Financial transaction database design for jamu small-medium enterprises

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AIP Conference Proceedings 2023年第1期2594卷

作者： R. Rahutomo A. Permatasari Y. Lie B. Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial ...

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial stability with its capabilities in recording electronic transactions accurately. As the initial step in technology empowerment for jamu SMEs, the research proposes a concept in facilitating jamu SMEs to adapt in online business. A combination of Connolly and Begg's database design principles and McCarthy's Marketing Mix 4P generates a conceptual design of PoS database targeted specifically for jamu SMEs. The database design manages online purchasing transactions for jamu products by involving not only jamu SMEs and consumers but also a system administrator who manages data verification and extraction.

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Systematic literature review: Accelerate the rice production for global food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： N. Dominic T. W. Cenggoro B. Pardamean 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 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

By 2050, about 70% of extra food production is needed to feed the world's population. As a majority staple food, the expansion of rice production should be accelerated. This systematic literature review aims to discover the factors that influence rice yields through a methodology that is partitioned into four main stages, i.e., query entry into multiple database sources, article title filtering, abstract filtering, and final article selection. The results show that genetics, irrigation system management, and farmers’ long-evolved local knowledge or experiences are the three big factors that elevate the rice production rates. Nevertheless, global warming is a serious challenge that should be deeply considered due to its great impact on reducing rice yields by up to 14.5%. Thus, the development of genetically modified rice varieties needs to be escalated while still maintaining other exogenous factors. This study contributes to providing a broader perspective for decision-makers and other relevant experts to accelerate rice production to achieve global food security.

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science 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 Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Questionnaire design for analyzing important risk factors of cervical cancer

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AIP Conference Proceedings 2023年第1期2594卷

作者： K. Purwandari D. Sudigyo A. S. Perbangsa A. Irwan B. Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Cervical cancer is Indonesia's second leading cause of death, following only breast cancer. According to the World Health Organization (WHO), non-communicable disorders will be blamed for 70% of all deaths and illnesses in 2020, while other disease types will account for 60%. Cervical cancer can be detected earlier, lowering the chance of death. This study aims to validate and check the pap smear test results obtained from the previously conducted pap smear screening program. The pap smear questionnaire developed would help in the compilation of a patient's habit history that has undergone a pap smear test during his life based on the factors associated with the occurrence of cervical cancer. Specific details, social-demographic features, diet, genital hygiene activities, reproductive background and behaviors, and health care and cancer prevention behavior are also included in the questionnaire template. The consequence of this design is the completeness of evidence on the theory of anomalies dependent on the findings of pap smear sampling.

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Lymphatic endothelial mTORC1 instructs metabolic and developmental signaling during lymphangiogenesis

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Developmental Cell 2025年

作者： Han, Fei Simeroth, Summer Zhu, Jie Gryniuk, Irma Pranay, Atul Chen, Weiqing Wang, Yuan Cai, Yuanyuan Shen, Zhiyuan Wang, Guangyu Griffin, Courtney T. Xia, Lijun Yu, Pengchun Cardiovascular Biology Research Program Oklahoma Medical Research Foundation Oklahoma City 73104 OK United States Department of Cell Biology University of Oklahoma Health Sciences Center Oklahoma City 73104 OK United States Aging and Metabolism Research Program Oklahoma Medical Research Foundation Oklahoma City 73104 OK United States Center for Bioinformatics and Computational Biology Houston Methodist Research Institute Houston TX United States Department of Physiology Biophysics & Systems Biology Weill Cornell Graduate School of Medical Science Weill Cornell Medicine Cornell University New York NY United States Department of Radiation Oncology Rutgers Cancer Institute and Robert Wood Johnson Medical School Rutgers University New Brunswick NJ United States Center for Cardiovascular Regeneration Houston Methodist Research Institute Houston TX United States Center for RNA Therapeutics Houston Methodist Research Institute Houston TX United States Department of Cardiothoracic Surgery Weill Cornell Medicine Cornell University New York NY United States Department of Biochemistry and Physiology University of Oklahoma Health Sciences Center Oklahoma City OK United States

The lymphatic vasculature comprises lymphatic capillaries and collecting vessels. To support lymphatic development, lymphatic endothelial cells (LECs) utilize nutrients to fuel lymphangiogenic processes. Meanwhile, LECs maintain constant prospero homeobox 1 (PROX1) expression critical for lymphatic specification. However, molecular mechanisms orchestrating nutrient metabolism while sustaining PROX1 levels in LECs remain unclear. Here, we show that loss of RAPTOR, an indispensable mechanistic target of rapamycin complex 1 (mTORC1) component, downregulates PROX1 and impairs lymphatic capillary growth and differentiation of collecting lymphatics in mice. Mechanistically, mTORC1 inhibition in mouse and human LECs causes Myc reduction, which decreases hexokinase 2 (HK2) and glutaminase (GLS), inhibiting glycolysis and glutaminolysis. Myc or HK2/GLS ablation impedes lymphatic capillary and collecting vessel formation. Interestingly, mTORC1 regulation of PROX1 is independent of Myc-HK2/GLS signaling. Moreover, genetic interaction analysis indicates that Myc and PROX1 play crucial roles in mTORC1-regulated lymphatic development. Collectively, our findings identify mTORC1 as a key regulator of metabolic programs and PROX1 expression during lymphangiogenesis. © 2025 Elsevier Inc.

关键词： glutaminase glutaminolysis glycolysis hexokinase 2 lymphangiogenesis lymphatic endothelial cell lymphatic vessel mTORC1 Myc PROX1

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The development of video analysis instrument to determine teacher's character

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AIP Conference Proceedings 2023年第1期2594卷

作者： Y. B. Gromang M. A. Rudhito D. Sudigyo T. Suparyanto B. Pardamean Department of Mathematics Education Universitas Sanata Dharma Paingan Maguwoharjo Depok Sleman Yogyakarta Indonesia 55282 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

This study aims to develop a valid and reliable video analysis instrument to determine teachers’ character in the opening lesson in terms of its utterances and produce video analysis on micro-teaching that will be used in training related to Artificial Intelligence (AI). The type of research used is research and development. The subject of this research is the micro-teaching video of class E students’ batch 2019, Mathematics Education Study program at Sanata Dharma University. The product of this research is a video analysis instrument to find out the character of the prospective teachers, such as confidence, enthusiasm, and happiness in terms of voice utterances. This study uses the ADDIE research model. The results show that the video analysis instrument has a validity value of 4.80 which means it's very valid. Video analysis instrument to find out the enthusiastic character has a value of validity of 4.70, which means it's very valid. Then, the video analysis instrument to find out the character of happiness has a validity value of 4.60 which means it's very valid. The practicality of the developed video analysis instrument meets the required criteria with a practicality value of 4.31. Overall, the video analysis instrument developed belongs to an effective category.

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Characterizing Mutually Exclusive Driver Mutations in Pan-Cancer

Characterizing Mutually Exclusive Driver Mutations in Pan-Ca...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Yifan Zhang William Yang Jun S. Liu Mary Qu Yang MidSouth Bioinformatics Center and Bioinformatics Program University of Arkansas at Little Rock Univ. of Arkansas Medical Sciences Little Rock USA Carnegie Mellon University School of Computer Science Pittsburgh USA Harvard University Cambridge USA

ISBN: (纸本)9781728118680

Efforts on cancer genomic study have revealed that mutations in cancer-driving oncogenes tend to mutually exclusive. To understand this tumorigenic mechanism and common cancer features, large-scale genomic study and molecular analyses across many cancer types are essential. We compiled somatic mutation and transcriptome profiles for a pan-cancer dataset that contains tumor tissue samples from 32 cancer types for over 10,000 patients. The genomic and molecular analysis was applied to four pan-cancer subgroups including pan-gastrointestinal, pan-gynecological, pan-kidney and pan-squamous, as well as the entire patient group. We identified seven genes, TP53, PIK3CA, PTEN, PIK3R1, LRP1B, CDH1, and TRRAP exhibited mutually exclusive mutation patterns across all cancer types (adjusted ). The mutations in these genes occurred in 55.9% of all cancer patients and over 70% of patients with pan-gastrointestinal, pan-gynecological and pan-squamous. Excepting LRP1B, the other six genes are included in the known cancer pathways. Notably, TP53, PIK3CA, and PIK3R1 are involved in over 20 cancer-related pathways. The co-expression network analysis suggested that LRP1B was associated with multiple genes that showed significant enrichment in Wnt signal pathway (adjusted p=0.0023) and ERBB signal pathway (adjusted p=0.0097). We further constructed a regulatory network to infer novel regulations of LRP1B in cancer. In addition, based on the mutations in the seven genes, we divided the patients into different groups for survival analysis. We found that the survival rate of the patient group with TP53 mutations was significantly shorter than in other groups (log rank p = 5.88e-10) in pan-gynecological. Our analysis systematically revealed the mutually exclusive mutation patterns of seven cancer genes across 32 cancer types. It helps us to better understanding the relations among different cancer types and pan-cancer subgroups, providing new insights into common mechanisms underlying diver

关键词： cancer cellular biophysics genetics genomics gynaecology kidney molecular biophysics tumours LRP1B gene cellular biophysics molecular biology Gynecology Genomics Mutually exclusive Tumours PIK3R1 gene Genetics Mutation Kidney Oncogenes

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Solution of SEIRD mathematical model for the COVID-19 transmission using microsoft excel

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AIP Conference Proceedings 2023年第1期2594卷

作者： D. P. W. Putra M. A. Rudhito D. Sudigyo T. Suparyanto B. Pardamean Department of Mathematics Education Faculty of Teacher Training and Education Sanata Dharma University Yogyakarta Indonesia 55281 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Mathematical modeling in the epidemiology study can be applied to describe the current transmission of viruses, one of which is compartments. However, this simulation model is rig...

Mathematical modeling in the epidemiology study can be applied to describe the current transmission of viruses, one of which is compartments. However, this simulation model is rigorous to understand, especially in interpreting the parameter values in influencing the solution. Therefore, it is necessary to present a coherent mathematical model solution. This study aims to determine the SEIRD model solution in the COVID-19 transmission using Microsoft Excel with three conditions (normal, new normal, and lockdown) to facilitate the interpretation of data. The SEIRD model used in this study considers natural population growth, namely natural births and deaths. Three stages to evaluate the model solution in this study are constructing a mathematical model, deciding the parameter intervals, and creating an applet in Microsoft Excel. The system of differential equations is converted into a system of difference equations to obtain numerical model solutions. The results showed that the differences in the infection rates for old normal, new normal, and lockdown conditions were 24%, 4%, and 3%, respectively.

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