JOIV : International Journal on Informatics Visualization
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Neural Collaborative with Sentence BERT for News Recommender System
Get PDFThe number of news produced every day is as much as 3 million per day, making readers have many choices in choosing news according to each reader's topic and category preferences. The recommendation system can make it easier for users to choose the news to read. The method that can be used in providing recommendations from the same user is collaborative filtering. Neural collaborative filtering is usually being used for recommendation systems by combining collaborative filtering with neural networks. However, this method has the disadvantage of recommending the similarity of news content such as news titles and content to users. This research wants to develop neural collaborative filtering using sentences BERT. Sentence BERT is applied to news titles and news contents that are converted into sentence embedding. The results of this sentence embedding are used in neural collaboration with item id, user id, and news category. We use a Microsoft news dataset of 50,000 users and 51,282 news, with 5,475,542 interactions between users and news. The evaluation carried out in this study uses precision, recall, and ROC curves to predict news clicks by the user. Another evaluation uses a hit ratio with the leave one out method. The evaluation results obtained a precision value of 99.14%, recall of 92.48%, f1-score of 95.69%, and ROC score of 98%. Evaluation measurement using the hit ratio@10 produces a hit ratio of 74% at fiftieth epochs for neural collaborative with sentence BERT which is better than neural collaborative filtering (NCF) and NCF with news category
Data Mining Techniques for Pandemic Outbreak in Healthcare
Get PDFPandemic outbreaks such as SARS-CoV, MERS-CoV and Covid-19 have attracted worldwide attention since these viruses have affected many countries and become a global public health issue. In 2019, Covid-19 was announced as a pandemic disease and categorized as a public health emergency globally. It is ranked as the sixth most serious pandemic internationally. This pandemic tracking and analysis require an appropriate method that gives better performance in terms of accuracy, precision and recall that defines its pattern since it involves huge and complicated datasets from the pandemic. Pattern identification is currently applied in many instances due to the rapid growth of data besides having the  potential to generate a knowledge-rich environment which can help to significantly improve the quality of clinical decisions and identify the relationships between data items. Therefore, there is a need to review the techniques in data mining on the pandemic outbreak that focuses on healthcare. The goal of this study was to analyze the algorithms from the data mining method that had been implemented for pandemic outbreaks in past research such as SARS-CoV, MERS-CoV and Covid-19. The result shows that 2 main algorithms, namely Naïve Bayes and Decision Tree, from the classification method, are appropriate algorithms and give more than 90% accuracy in both the pandemic and healthcare. This will be further considered and investigated for future analysis on large datasets of Covid-19 which can help researchers and healthcare practitioners in controlling the infection of the coronavirus using the data mining technique discussed
Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework
Get PDFThe number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recognition systems because the architecture has high accuracy, quite lightweight, and easy to implement in the real-time face recognition system. In our research, triplet loss embedding shows good performance in terms of the ability to recognize faces. It can also be used for real-time face recognition for the authentication process in the attendance recording system that uses RFID. In our study, the performance for face recognition using k-NN and SVM classification methods achieved results of 96.2 +/- 0.1% and 95.2 +/- 0.1% accordingly. Attendance recording systems using face recognition as an authentication process will increase student attendance in lectures. The system should be difficult to be faked; the system will validate the user or student using RFID cards using facial biometric marks. Finally, students will always be present in lectures, which in turn will improve the quality of the existing education process. The outcome can be changed in the future by using a high-resolution camera. A face recognition system with facial expression recognition can be added to improve the authentication process. For better results, users are required to perform an expression instructed by face recognition using a database and the YOLO process
Fast Clustering Environment Impact using Multi Soft Set Based on Multivariate Distribution
Get PDFEvery development activity is always related to human or community aspects. This can also lead to changes in the characteristics of the community. The community's increasing awareness and critical attitude need to be accommodated to avoid the emergence of social conflicts in the future. This research is to find out how the public perception about the impact of development on the environment. Two methods are used, i.e., MDA (Maximum Dependency Attribute) and MSMD (the Multi soft set multivariate distribution function). The MDA is to determine the most influential attribute and the Multi soft set multivariate distribution function (MSMD) is to group the selected data into classes with similar characteristics. This will help the police producer plan the right mediation and take quick activity to make strides in the quality of the social environment. The experiment conducted level of impact based on the clustering results with the greatest number of member clusters is cluster 1 (very low impact) with 32.25 % of total data following cluster 5 (Very High impact) with 24.25 % of total data. The experiment obtains the level of impact based on the clustering results. The greatest number of member clusters is cluster 1 (extremely low impact) with 32.25 % of total data following cluster 5 (Very High impact) with 24.25 % of total data. The scatter area impact is spread at districts 6, 7, 10, 11, the most of very high impact and districts 1,2,3,4,5,8 the lowest impact.Â
IT-Architecture Study Literature Research Collaboration: Malay Architecture Context
Get PDFTalking about architecture culture means talking about buildings and architecture. Architecture is a field of research that is always related to space and form. One of the exciting research topics on architecture is research on Malay architecture. Preserving Malay architecture is an important thing that must be done physically and meaningfully, positively impacting the community's development. The rapid development of information technology (IT) should be part of conservation efforts. IT supports various activities that significantly help conservation efforts. The role of IT in architecture is a significant research opportunity because of still little research on this topic. Thus, we conduct a study and analysis using a systematic literature review methodology to review IT-Architecture research, especially Malay architecture. The systematic literature review methodology consists of six stages, namely: (1) research question definition; (2) literature searching by keywords on literature sources; (3) literature assessment; (4) literature quality measurement; (5) data extraction and synthesis; and (6) research recommendation and suggestion. After going through the quality assessment process, only 37 papers were obtained that were relevant to the topic of IT-Architecture. The most discussed research themes in this literature review search were: (1) building information modeling (BIM) and augmented reality (AR) / virtual reality (VR); (2) BIM and geographic information system (GIS); and (3) BIM application and technology. However, based on literature searches, IT, and Malay architecture are still insufficient. Therefore, the topic of IT and Malay architecture still needs to be studied further in the future
A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations
Get PDFThe amount of data in our world has been rapidly keep growing from time to time. Â In the era of big data, the efficient processing and analysis of big data using machine learning algorithm is highly required, especially when the data comes in form of streams. There is no doubt that big data has become an important source of information and knowledge in making decision process. Nevertheless, dealing with this kind of data comes with great difficulties; thus, several techniques have been used in analyzing the data in the form of streams. Many techniques have been proposed and studied to handle big data and give decisions based on off-line batch analysis. Today, we need to make a constructive decision based on online streaming data analysis. Many researchers in recent years proposed some different kind of frameworks for processing the big data streaming. In this work, we explore and present in detail some of the recent achievements in big data streaming in term of contributions, benefits, and limitations. As well as some of recent platforms suitable to be used for big data streaming analytics. Moreover, we also highlight several issues that will be faced in big data stream processing. In conclusion, it is hoped that this study will assist the researchers in choosing the best and suitable framework for big data streaming projects
Identifying the Requirements of Visually Impaired Users for Accessible Mobile E-book Applications
Get PDFBooks are a medium for communicating information and in recent years have taken the electronic form called e-books. This shift has opened new opportunities for the visually impaired in overcoming their struggles with books in the traditional paper format. Yet, the National Federation of the Blind (NFB) claimed that many e-book applications do not meet needs of the visually impaired. Very few studies had investigated this subject matter hence paving the way for this current study to address the above research gap. As a result, equitable access to e-books for the visually impaired is still limited. Hence, there is now a necessity to design usable and accessible e-book interfaces for the visually impaired. To achieve this goal, it is important to identify the e-book requirements of the visually impaired into their e-book applications. An online survey was conducted involving seven visually impaired students at a local Malaysian university. The target participants’ ages are between 21 and 27 years old. The outcomes of this study identified ten requirements for accessible e-book applications for the visually impaired. Among these requirements are features that enable users to zoom, read aloud, and search for book contents. Besides that, screen reader strategy and text-to-speech are also mandatory. Other requirements include clear text and sound, ease of navigation, high contrast, and high brightness. These requirements will involve the field of Human-Computer Interaction design which is applied particularly in the development of usable and accessible mobile e-book applications for the visually impaired
Autonomous Agents in 3D Crowd Simulation Through BDI Architecture
Get PDFAgent based simulation (ABS) is a paradigm to modelling systems included of autonomous and interacting agents. ABS has been tremendous growth and used by researchers in the social sciences to study socio-environmental complex systems. To date, various platforms have been introduced for agent-based social simulation. They are rule based in any logic, python based in SPADE and etc. Although those platforms have been introduced, there is still an insufficient to develop a crowd simulation in 3D platform. Having a 3D platform is needed to enabling the crowd simulation for training purposes. However, the current tools and platform still lack features to develop and simulate autonomous agents in the 3D world. This paper introduced a BDI plug in at Unity3D for crowd simulation. BDI is an intelligent agent architecture and it is able to develop autonomous agents in crowd environment. In this paper, we present the BDI plug with a case study of Australia bush fire and discuss a method to support autonomous agents' development in 3D crowd simulation. The tool allows the modeller to develop autonomous agents in 3D world by taking the advantages of Unity3D
How is The Adoption of Digital Marketing Services for Smart City Application Users?
Get PDFSmart City Mobile Apps is currently being developed by property developers in major cities in Indonesia and is used by businesses to market their products through the application. Technology integration in city governance is possible, thanks to the internet of things, a network of electronic devices interconnected and capable of sending data or following up with minimal human intervention. This study aims to identify the characteristics of Smart City Mobile Apps users in the South Tangerang area. The method used to see how well the implementation of digital marketing in Smart City Mobile Apps combines the TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) models. Questionnaire data were processed using the Structural Equation Modelling (SEM) method. The study results state that the company's digital marketing strategy through Smart City Mobile Apps is already satisfying. It can be seen from the value of adoption of Smart City Mobile Apps users in utilizing this application, which is considerably large at 0.764 based on the coefficient of determination. The attitude variable influences consumers to use the application in finding trade information in the Smart City, with an influence value of 0.412 and the behavior intention to use with an influence value of 0.726, which shows that the intended behavior of the application and the trust in the benefits of the application can encourage users to use this application for purchasing their daily needs
Proposition for LMS Integration for Share, Exchange, and Spread of Online Lectures under Covid-19 Environment
Get PDFThere has been a movement to share and spread online lectures through OCW and MOOC systems. This movement would have been spread widely and adopted widely if those courses could be easily exchangeable with other platforms or services. If this function is available, learning activities, resources, learning outcomes can be accessed between different platforms and services. With this function, the credit exchange between different platforms or services will be easier. It also facilitates course sharing and circulation. Because the LMS is the basic platform for online classes, providing sharable and reusable learning activities, resources, and learning outcomes across the different LMSs is very demanding for online education. Analyzing LMS use in Korean universities, Moodle, Canvas, and domestic LMSs are founded to be the significant three kinds that are widely used in Korea. In this paper, a method of integrating Moodle, Canvas, and domestic LMS services is proposed. A central Moodle server is installed as the main LMS server, and the method to connect or complement with a central Moodle server is proposed for each different kind of LMS. LMS users can easily access a different kind of LMS as a form of imported course, tightly connected service, or log in as SSO. This proposition can be applied to various service fields such as KMOOC, KOCW, credit exchange, lecture exchange between universities, regional unification of online educational centers as a practical problem-solver