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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

Procedia computer science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 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

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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The by-product of oil palm dosage application on Turnera subulata growth supports water supply

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AIP Conference Proceedings 2024年第1期3026卷

作者： Pauliz Budi Hastuti Gilang Tri Anggara Wiwin Dyah Ully Parwati Teddy Suparyanto Digdo Sudigyo Bens Pardamean Faculty of Agriculture STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Plant growth with complex organic matter content can be enhanced by using oil palm by-products. These organic materials can maintain the water supply in the plant body. Therefore, in oil palm plantations with significant groundwater consumption, organic matter’s the ability to sustain water availability. Caterpillars that devour palm leaves are among the numerous pests that threaten oil palm plantations. Predators of leaf-eating caterpillars use the holly rose flower (Turnera subulata) in oil palm farms as a habitat. Therefore, the effect of the type and dose treatment of oil palm by-products on the growth of Turnera subulata was observed to support sustainable water management in oil palm plantations. The research was carried out using a factorial design arranged in a Completely Randomized Design (CRD) consisting of two components: the type of palm oil mill by-product (boiler ash, empty bunches, and solid) and the dose of a by-product (% volume) consisting of four dosages (0, 25, 33, and 50% volume). The research data were analyzed using variance at the 5% test level. A DMRT test at the 5% test level was conducted on the treatment that had a significant effect. The growth of Turnera subulata was most positively impacted by a solid application dose of 50% volume. Turnera subulata plants responded the least favorably to the application of empty bunches in any dose treatment.

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Mighty Math Knight: A Game for Learning Basic Math Operations

Mighty Math Knight: A Game for Learning Basic Math Operation...

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Latin American Conference on Learning Objects and Technology (LACLO)

作者： Luciana Da Costa Varjolo Rodrigo De Souza Santos Gustavo Guedes Master’s Program in Computer Science CEFET/RJ Rio de Janeiro RJ Brazil UERJ Rio de Janeiro RJ Brazil CEFET/RJ Rio de Janeiro RJ Brazil

ISBN: (纸本)9781665423595

Digital games applied in education collaborate with the transmission and assimilation of knowledge, as they are motivating and attractive tools for students. This type of games causes a feeling of immersion in the player and provides the applicability of previously acquired concepts, that makes the learning process less complicated and more enjoyable. Studies indicate that educational digital games facilitate the absorption of more abstract science content, such as mathematics that is considered one of the most complex in elementary school. This article presents the Mighty Math Knight game, developed with the goal of helping learning the four mathematical operations to elementary school students.

关键词： Absorption Education Games Mathematics

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A Computational Approach for Predicting the Termination of COVID-19

A Computational Approach for Predicting the Termination of C...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Prateek Dutta Abhiroop Sarkar Yash Ambekar Hui Ting Pek F. H. Juwono Gopal Sakarkar Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur M.H India Department of Computer Science G H Raisoni College of Engineering Nagpur M.H India Dept. of Mechatronics and Biomed. Eng Universiti Tunku Abdul Rahman Kajang Selangor Malaysia Computer Science Program University of Southampton Malaysia Nusajaya Johor Malaysia D.Y. Patil Institute of Master of Computer Applications and Management Akurdi Pune M.H India

ISBN: (纸本)9781665486644

In 2019, there was an epidemic to the human society, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus causes coronavirus disease 2019 (COVID-19). It is an uncertain disease encountered in society for which the technology and human society had not prepared before. COVID-19 first spread over the Wuhan city of China. Since, the past two years of time-span, it has affected the citizen’s life culture and expectancy. Now, most of the population are concern about when will be COVID-19 terminate. Basically, this paper aims to analyze the COVID-19 data with features as total confirmed cases, death rate, and vaccination rate around the world-wide region. On analyzing the data, with the help of Machine Learning (ML) algorithms, we estimate the termination of COVID-19. The rapid expansion of the COVID-19 epidemic has compelled the need for technology in this field.

关键词： COVID-19 Pandemics Time series analysis Urban areas Sociology Predictive models Prediction algorithms

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Machine learning-based classification of children affected by malnutrition using multimodal sMRI and DTI brain images

Machine learning-based classification of children affected b...

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Medical Information Processing and Analysis (SIPAIM), International Symposium on

作者： Daniel Colin Garnica Ramon Cota-Aguiar Israel Vaca-Palomares Juan Fernandez-Ruiz Nidiyare Hevia-Montiel Jorge Perez-Gonzalez Master Program in Computer Science Universidad Nacional Autónoma de México Mérida México Facultad de Psicología Universidad Nacional Autónoma de México Mexico City México Unidad Académica del IIMAS en el Estado de Yucatán Universidad Nacional Autónoma de México Mérida México

Child malnutrition is a prevalent pathological condition in developing countries, such as Mexico, with scarce studies on its anatomical cerebral effects. This study analyzed 26 infants subjects that included brain volumes from two neuroimaging modalities: DTI and sMRI. Twelve of the subjects involved children with normal nutrition in their early years of life, and 14 represented severe malnutrition cases. Segmentation was obtained by FreeSurfer from 94 and 103 regions for sMRI and DTI modalities, respectively. Each region was analyzed using several morphological and diffusion features; afterwards, seven classification models were trained to differentiate between the two groups. The results indicate notable differences that allow accurate classification, with an accuracy up to 1.0 and an AUROC of 1.0 for classification with SVM, LR, KNN, and MLP algorithms.

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Learning Pairwise Preferences from Movie Ratings 7

Learning Pairwise Preferences from Movie Ratings

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Qomariyah, Nunung Nurul Fajar, Ahmad Nurul Bina Nusantara University Faculty of Computing and Media Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

Preference Elicitation is now considered a crucial stage in recommender system. That is the stage where we collect and query preferences of the users as part of interactive decision support system. Preference elicitation can be performed using many ways, such as asking the user explicitly to give ratings or feedbacks for some products, or implicitly observing their behaviour. Once this preference has been collected by the system, it can then be used to generate item recommendation. Using explicit feedback itself, such as rating only, has several drawbacks. Using ratings is very subjective. Two users with similar taste might give different rating to the same item. A user also may not be consistent in giving number to express their liking. In other case, a user may like an item more than the other items, but feels difficult to give lower rating on the other item, because it means that the particular item is just as bad as the one he/she does not like. By showing two different items as a pair, it will be easier for the users to pick which one is the best. In this paper, we show the result of our experiment in predicting user pairwise preferences by using their movie ratings data. We evaluated five different machine learning algorithms to predict the data in pairwise preference format. The result shows that K-Nearest Neighbour and Random Forest outperformed the other algorithms. © 2020 IEEE.

关键词： Recommender systems

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Transformative Sport science Using Social Media as a Collaboration Tool 7

Transformative Sport Science Using Social Media as a Collabo...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Syahir, Arsyan Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

Sports science can have a significant and positive impact on coaches and athletes, as well as for the professional sports organization. According to this situation, more and more organizations are competing to implement sports science as the monitoring systems. Along with the development of technology, it becomes easier for humans to carry out their activities, including communication with each other. Advances in the field of communication technologies have led to the use of social networks to support all activity. With social media, all kinds of information that people want to search for can be found easily. Social networks have their uniqueness in their characteristics. Like LINE has free calling and video calling features, while Instagram has features like Instagram Story, where users can document their activities in the form of photos or recordings. By all the characteristics of social networks, it will support the activity of sports science. The methodology of this research focused on quantitative research based on the T-test approach. The result shows that social media involvement can significantly support collaboration in sports science, so it can increase people's motivation to interact with other participants in sport organizations. © 2020 IEEE.

关键词： Sports

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The Effect and Technique in Search Engine Optimization

The Effect and Technique in Search Engine Optimization

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International Conference on Information Management and Technology (ICIMTech)

作者： Ardi Dramilio Calvin Faustine Stephen Sanjaya Benfano Soewito School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program -Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

In this modern era, we can find for anything anytime, anywhere on the internet. Most people will find it on Google. When we look for something, we will go to Google search engines. Google has more than 35 trillion Web Pages on the internet and if we have a website how can people notice your website that is buried with other 35 trillion websites? The question is how to make our website can be in the top position of search results. The answer is simple, that is by optimizing search engines on your website. In this paper we will inform SEO techniques such as onsite optimization and offsite optimization along with the effects of the two techniques which also allows your website to be on the top search of results. Finally, we also discussed the benefits of the website being to be the top in search engine.

关键词： Search engines Optimization Google computer science Engines Business Web search

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Communicaton On Mobile Phone For The Deaf Using Image Recognition

Communicaton On Mobile Phone For The Deaf Using Image Recogn...

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International Conference on Information Management and Technology (ICIMTech)

作者： Benfano Soewito Alexander Khrisna Satyadhana Raymond Sarah Maria BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Sign language is an absolute thing that is mastered by some people, especially people who have hearing or deaf problems. Problems will occur if they want to communicate via mobile devices. They have to use an application that translate sign language to text and vice versa. The research in this field still open because each language will have different sign language. In the other hand the image that was captured by the mobile devices depend on the environment such as brightness and the background. The sign language captured with static background has high accuracy compared with dynamic background that has colorful background. Most of research do not include the dynamic background. Therefore in this study introduced an application used image recognition that can translate sign language with dynamic background into a text so that it can be used to communicate among people who have hearing problems and also between deaf and normal people. The experimental showed that accuracy of our system is 87%.

关键词： Assistive technology Gesture recognition Auditory system Artificial neural networks Neurons computer science Mobile handsets

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Dynamic logistic models for stock price fluctuation during Covid-19 pandemic in Indonesia

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AIP Conference Proceedings 2023年第1期2975卷

作者： Andree Sulistio Chandra Viska Noviantri Siti Komsiyah Ade Suhendar Mathematics Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School Master Program Bina Nusantara University Jakarta Indonesia 11480

Investment is one indicator that can affect the country’s economy. One type of investment with great demand is stocks, so stock price fluctuations are always interesting to be analyzed. This study aims to model stock price fluctuations represented by dynamic logistics models since the stock price has a nonlinear pattern and grows rapidly but with restricted value. The model will be discretized and converted into a differential equation so that the solution can derive for a short period. Meanwhile, fit and forecast data analysis is applied to some actual data for long periods. The data used in this study is the daily closing price of the Indonesia Composite Index (IDX Composite) during the Covid-19 pandemic. Thus, the fluctuation of stock prices in Indonesia during the Covid-19 pandemic can analyze further. The results indicate that our prediction has a high accuracy since the Mean Average Percentage Error (MAPE) average is 4.332%, and the Root Mean Square Percentage Error (RMSPE) average is 5.572%. This study shows that investors can use the dynamic logistic model results to improve their knowledge as a consideration in decision-making.

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