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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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Design of Mobile Application for a Smart Home Nutrition System (SmartNS) 1st

Design of Mobile Application for a Smart Home Nutrition Syst...

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1st International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2021

作者： Carrisosa, Carlos Alanis, Arnulfo Sotelo, Javier Student of the Master’s Program in Information Technology Department of Systems and Computing National Technology of Mexico Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico Systems and Computer Department National Technology of México Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico Computer Systems Student Department of Systems and Computing National Technology of Mexico Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico

ISBN: (纸本)9783030902407

Every day there are more devices or objects that connect to the internet, these devices are found in different areas in the home, health, industry and others, this project is implemented in the internet of things for homes, it is a module called "nutrition", the which allows you to have a record of diets provided by a nutritionist, this allows reducing costs and food waste because with the mobile application called: Mobile application for smart appliances (EInt), you can obtain the products directly from a preferred provider. Given the situation current due to the COVID-19 pandemic, exits to non-essential situations have been reduced, this prototype pretends to be a support for users when making errand purchases and avoid going out as little as possible. The analysis and design of the device contains several agents, this article describes the nutrition agent, the food ontology, its semantic network. © 2021, Springer Nature Switzerland AG.

关键词： Internet of things

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User Preference Modelling from Movie Database 7

User Preference Modelling from Movie Database

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

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

ISBN: (纸本)9781665404228

Film industry becomes one of the largest amongst the other economic sectors worldwide nowadays. This industry also has a significant impact in the global economic market. Many movies have been produced each year. However, some movies still fail to reach break-even points every year. Players in this industry need to think carefully when spending most of their money to make a great and successful movie in the market. Several attempts also need to be made to estimate the success performance before a movie can be released. On the audience side, there is an indicator that we can use to decide that a movie is good by looking to its ratings. The industry can use this rating systems as a factor to be considered when evaluating the past movie performances to make better movie for the next production. This study aims to predict the movie ratings and find the most important features which correlate to the ratings. We performed an experiment on IMDb dataset which contains 5,043 movie metadata on four models of machine learning, Linear Regression (LR), Decision Tree (DT), Random Forest (RF) and K-Nearest Neighbor (KNN). From the experiment, Random Forest achieves the best performance amongst the four models. © 2020 IEEE.

关键词： Decision trees

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Predicting User Preferences with XGBoost Learning to Rank Method 3

Predicting User Preferences with XGBoost Learning to Rank Me...

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3rd International Seminar on Research of Information Technology and Intelligent systems, ISRITI 2020

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

ISBN: (纸本)9781728184067

Learning user preferences become very important as the personalization systems grow rapidly in this current era. Offering special and personal services can be an added value for the companies to maintain their customer loyalty. Building a personalized recommendation requires a good machine learning model to understand the individual preferences. Every user can be presented with a list of items sorted by its score learned from the individual preferences. So the first couple items shown will be the most liked items by the user. We can borrow the Learning to Rank algorithm from Information Retrieval to solve this problem. In this paper, we present the implementation of user preferences learning by using XGBoost Learning to Rank method in movie domain. We show the evaluation of three different approaches in Learning to Rank according to their Normalized Discounted Cumulative Gain (NDCG) score. We can conclude that in our case study, the pairwise approach appears to be the best solution to produce a personalized list of recommendation. © 2020 IEEE.

关键词： Recommender systems

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Learning Pairwise Preferences from Movie Ratings

Learning Pairwise Preferences from Movie Ratings

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International Conference on ICT For Smart Society (ICISS)

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

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

关键词： Motion pictures Predictive models Recommender systems Social networking (online) Industries Encoding Task analysis

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Predicting User Preferences with XGBoost Learning to Rank Method

Predicting User Preferences with XGBoost Learning to Rank Me...

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International Seminar on Research of Information Technology and Intelligent systems (ISRITI)

作者： Nunung Nurul Qomariyah Dimitar Kazakov Ahmad Nurul Fajar Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia University of York York United Kingdom BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728184067

ISBN: (纸本)9781728184074

关键词： Predictive models Measurement Motion pictures Task analysis Linear programming Boosting Web search

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User Preference Modelling from Movie Database

User Preference Modelling from Movie Database

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International Conference on ICT For Smart Society (ICISS)

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

关键词： Motion pictures Industries Prediction algorithms Machine learning algorithms Predictive models Social networking (online) Random forests

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A microservice-based approach for increasing software reusability in health applications 16

A microservice-based approach for increasing software reusab...

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16th ACS/IEEE International Conference on Computer systems and Applications, AICCSA 2019

作者： Da Silva, Marcio Alexandre Pereira Times, Valeria Cesario De Araujo, Andre Magno Costa Da Silva, Paulo Caetano Center for Informatics Federal University of Pernambuco Recife/PE Brazil Department of Information Systems Federal University of Alagoas Penedo/AL Brazil Master Program in Computing Salvador University Salvador/BA Brazil

ISBN: (纸本)9781728150529

Traditionally, legacy Health applications use software architecture models that make it difficult to reuse components. Reusability is an essential attribute in the software lifecycle, as it improves the quality of applications and reduces maintenance and development costs. This paper proposes the cloud tool Microservice4EHR, which dynamically generates reusable components from existing software artifacts (e.g., graphical interfaces), while conforming to the standards used in the healthcare domain. A software architecture based on Connectors and Microservice components is specified and made tangible by means of three algorithms. The use of both components is applied to a real-world scenario (a Brazilian blood donation center) and serves as an example. As a result, it is possible to notice that Health applications achieve greater reusability when they employ the microservice architecture. Thus, Microservice4EHR enables the use of reusable components in Health application architectures (for both new and legacy systems), increasing software reusability in this context. © 2019 IEEE.

关键词： Health

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Implementation on Indonesian property real estate industry based on service oriented architecture

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

作者： Ahmad Nurul Fajar Nunung Nurul Qomariyah Albert Baihaqi Siregar Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Department of Information Technology Universitas Sumatera Utara Medan Indonesia

This study focuses on the implementation of business property in real estate market. This is due to inability of the current technology to support the property products. Some people feel uncomfortable to buy houses from the online market. Buyers need to be very careful to deal with the sellers as the houses price is considered quite expensive. On the other hand, improving real estate market is still a challenge. This business still needs a physical representation, although it can be sold from the online market. In this paper, we propose the Service Oriented Architecture (SOA) system of virtual reality and drone. We use drone to help scanning the property units and then make 3D models with visual mapping so it can be run in a virtual reality environment, video 360. In real estate, business process can be developed in various ways. Our proposed SOA in this study can be used to integrate all of them.

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Health disparities in jail populations: Mixed methods and multi-disciplinary community engagement for justice and health impacts

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Practicing anthropology 2019年第4期41卷 2-16页

作者： Robert T Trotter Viacheslav Y Fofanov Ricky Camplain Christine L Arazan Carolyn Camplain Emery R Eaves Mary Hanabury Crystal M Hepp Bailey S Kohlbeck Monica R Lininger Marie Peoples Natalia O Dmitrieva Julie A Baldwin Department of Anthropology Northern Arizona University Flagstaff AZ. School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ. Center for Health Equity Research & Department of Health Sciences Northern Arizona University Flagstaff AZ. Department of Criminology and Criminal Justice Northern Arizona University Flagstaff AZ. PhD Student of Interdisciplinary Health Northern Arizona University Flagstaff AZ. Director of Human Research Protection Program Northern Arizona University Flagstaff AZ. Master's Student of Anthropology Northern Arizona University Flagstaff AZ. Department of Physical Therapy and Athletic Training Northern Arizona University Flagstaff AZ. Deputy County Manager for Coconino County Flagstaff AZ. Department of Psychological Sciences Northern Arizona University Flagstaff AZ. Department of Health Sciences Center for Health Equity Research Southwest Health Equity Research Collaborative Northern Arizona University Flagstaff AZ.

This special issue of Practicing Anthropology presents multidisciplinary and multisectoral views of a community engaged health disparities project titled "Health Disparities in Jail Populations: Converging Epidemics of Infectious Disease, Chronic Illness, Behavioral Health, and Substance Abuse." The overall project incorporated traditional anthropological mixed-methods approaches with theory and methods from informatics, epidemiology, genomics, evolutionary and computational biology, community engagement, and applied/translational science.

关键词： criminal justice health disparities incarcerated populations

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