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Restaurant Customer Feedback Sentiment Analysis using Aspect Embedding Long Short-term Memory Model

Restaurant Customer Feedback Sentiment Analysis using Aspect...

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2023 International Conference on computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Fitria Murad, Dina Tho, Cuk Hashimoto, Kiyota BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

In the past ten years, there has been a proliferation of unstructured textual data from a variety of fields, allowing for the analysis of the sentiment polarity of the text authors in each of those datasets. To analyze sentiment polarity from unstructured data, machine learning tasks such as aspect-based sentiment analysis are used. The public dataset of restaurant patron feedback was used as the input for this study's empirical results of aspect-based sentiment analysis utilizing the Aspect Embedding Long Short-Term Memory model. The primary experiment's results show that the aspect embedding long short-term memory model can predict aspect sentiment polarization from customer feedback to restaurant service and aspect text representation (aspect text embedding) as input with excellent performance. For example, the Aspect Embedding Long Short-term Memory model, which uses ReLU as its activation function in the Dense layer tends to achieve higher performance (0.97 average accuracies) than the same model equipped with Sigmoid, and Tanh functions which achieve 0.954 and 0.956 average training accuracy respectively. © 2023 IEEE.

关键词： Sentiment analysis

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Comparing the Effect of Attention Mechanism and Aspect Embedding on the Performance of Long Short-term Memory Model for Aspect-Based Sentiment Analysis

Comparing the Effect of Attention Mechanism and Aspect Embed...

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2023 International Conference on computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

The attention mechanism is one of the key enablers which have positioned transformer models as the state-of-the-art models in Natural Language Processing. By having the attention mechanism, the first version (vanilla) transformer model can retrieve the hidden state but at the same time can maintain a low requirement on the context vector dimension by selectively choosing to which encoder hidden states to give priority attention. The objective of this study is to evaluate the effect of modified Long Short-term Memory models architecture on the model performance as a predictive model. The first model is modified by adding an attention mechanism to its architecture;whilst, the second model is modified by adding additional input to its architecture. The performance of both models is compared by assigning each model the same task: to address the aspect-based sentiment analysis task. The experiment results show that adding an attention mechanism is not significantly increase the performance of the Long Short-term Memory model in comparison to adding input to the same model. In particular, the average training accuracy of the former model is 0.885;whilst, the average training accuracy of the latter model is 0.942. © 2023 IEEE.

关键词： Sentiment analysis

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Model for Endometriosis Detection Using Machine Learning Algorithms

Model for Endometriosis Detection Using Machine Learning Alg...

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Software Engineering and computer Science (CSECS), International Conference on

作者： Alexis Bautista Jahir Tardillo José Luis Castillo-Sequera Lenis Wong Information Systems Engineering Program Universidad Peruana de Ciencias Aplicadas Lima Peru Department of Computer Science Universidad de Alcalá Alcalá de Henares Spain

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Endometriosis is a chronic disease that affects a considerable percentage of women of reproductive age and is characterized by the presence of endometrial tissue outside the uterine cavity, leading to symptoms such as pelvic pain and dysmenorrhea. The aim of this study is to develop a predictive model for the classification of endometriosis using four Machine Learning algorithms: Random Forest, LASSO, SVM, and Naive Bayes. For this purpose, a dataset from the Global Health Data Exchange was utilized, consisting of 1,000 cases of patients with endometriosis. The methodology included data cleaning and preprocessing, as well as the evaluation of each algorithm's performance using four metrics: precision, recall, F1-Score, and accuracy. The findings revealed that the Random Forest algorithm was the most effective in identifying endometriosis, outperforming the other algorithms with a precision of 0.99 for the “endometriosis” class and an overall accuracy of 0.98.

关键词： Support vector machines Measurement Training Machine learning algorithms Accuracy Software algorithms Predictive models Bayes methods Random forests Software engineering

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Jakarta Smart City Mobile Application for Problem Reporting

Jakarta Smart City Mobile Application for Problem Reporting

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2021 International Conference on Artificial Intelligence and Smart systems, ICAIS 2021

作者： Bongestu, Dejan Rivaldo Yappiter Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univerisity Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728195377

This paper discusses the possibility of a better smart city implementation with the Jakarta information App. Our App will be a one-stop go platform where people could access new information regarding the city live and instantaneously, the information contained is not just from an average news report, but people from social media or communities can also contribute in giving up to date news 24/7. In order to create this app, some processes are done to dive deeper into Jakarta's core infrastructure, the way of living, and the society behind the city. Jakarta information App's goals are to connect the people everywhere at any time or place;it is not just an average social media app, its main objective is to be some hub for the city, it is an a2-way connected dots, the city with the people and also the reverse. The proposed system has been modeled with a use case diagram to design the business process and using the class diagram to model the database model diagram. The user interface has been designed as a means of communication between the user and the system. © 2021 IEEE.

关键词： Smart city

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Aspect-based Sentiment Analysis using Long Short-term Memory Model for Leveraging Restaurant Service Management

Aspect-based Sentiment Analysis using Long Short-term Memory...

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2023 International Conference on computer Science, information Technology and Engineering, ICCoSITE 2023

ISBN: (纸本)9798350320954

In general, the hospitality industry has been acknowledged as a major sector that gives a high contribution to economic development in many countries including Indonesia. For that reason, many initiatives have been implemented to help the growth of the hospitality industry in many countries including Indonesia to rebound from the harsh impact of the Covid-19 Pandemic. One such initiative is improving restaurant services as the main sector of the hospitality industry. This paper presents empirical results of sentiment analysis as a means to assess the quality of restaurant services as the first step to improving service quality. In particular, this study explores the aspect-based sentiment analysis method to identify some aspects of restaurant service which need improvement by learning the polarity of customers toward the restaurant services without having to meet the customers directly. By using the aspect-based sentiment analysis method, the customer sentiments comprising opinions, sentiments, evaluations, attitudes, and emotions from restaurant service can be analyzed using customers' online reviews as input. The main experiment findings showed that the Long Short-term Memory model can achieve high performance in predicting aspect polarization in restaurant service reviews. Other findings suggest that Sigmoid as an activation function achieved 0.97 average training accuracy and 0.69 average testing accuracy giving a better performance to the model in comparison to ReLU, Tanh, and ELU activation functions. © 2023 IEEE.

关键词： Sentiment analysis

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Mobile application for the futsal sports community in Jakarta

Mobile application for the futsal sports community in Jakart...

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2021 International Conference on Artificial Intelligence and Smart systems, ICAIS 2021

作者： Deksano, Farel Darari Erfiandhi, Dimas Raka Prasetya, Anggy Cahya Patmuryanto, Aditya Satria Nagara Warnars, Harco Leslie Hendric Spits 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

ISBN: (纸本)9781728195377

The rapid development of technology makes many changes that occur in the community in carrying out daily activities, one of which is the use of online-based applications to support community activities in Jakarta. This study aims to build applications to support community activities in the field of futsal sport, namely ordering Android-based sports arenas. This ordering application consists of Home, Schedule, sparring, profile, info, and ordering. This application makes it easier for people to find information about the sports arena and make it easier to order sports fields anytime, anywhere, so they can increase profits for the sports arena business. This mobile application was applied with android studio and using MySQL for the database. Hopefully, creating this mobile application will reduce the number the crime rate committed by youth and expand their friendship not only around their house or school but for future development it is possible to run a competition that can be held at the provincial level, or at the national level and possibly even at the South East Nation country (ASEAN) level which involving several ASEAN countries. © 2021 IEEE.

关键词： Sports

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Record the transcript of student activity in higher education based on blockchain technology 15

Record the transcript of student activity in higher educatio...

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14th International Conference on ICT, Society, and Human Beings, ICT 2021, 18th International Conference on Web Based Communities and Social Media, WBC 2021 and 13th International Conference on e-Health, EH 2021 - Held at the 15th Multi-Conference on computer Science and information systems, MCCSIS 2021

作者： Meyliana Chandra, Yakob Utama Cassandra, Cadelina Surjandy Widjaja, Henry Antonius Eka Fernando, Erick Prabowo, Harjanto Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789898704306

Apart from the core competency, learning in the organization also brings students opportunities to improve their soft skills. Good soft skills can help students when working in a company with many people. Students can get soft skills by participating in various non-academic activities such as new student orientation, Student organization, seminar, and workshop. For every non-academic activity participated by students, they will get points and recorded in Student Academic Transcript (SAT). SAT is an integral part of a diploma certificate. The research method used in this research is a user-centered design to build an education value chain model for recording student activity transcripts based on blockchain technology. Blockchain technology is used to ensure data validity, reliability, and integrity for all student non-academic activities. © 14th International Conference on ICT, Society, and Human Beings, ICT 2021, 18th International Conference on Web Based Communities and Social Media, WBC 2021 and 13th International Conference on e-Health, EH 2021 - Held at the 15th Multi-Conference on computer Science and information systems, MCCSIS 2021. All rights reserved.

关键词： Students

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Implementation of Malaria Detection Using MobileNetV2 Pretrained Model for Improved Deep Learning Based Diagnostics

Implementation of Malaria Detection Using MobileNetV2 Pretra...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Rahmat Hidayat Achmad Solichin Adhitia Erfina Sudin Saepudin Muhamad Muslih Mohd Zainuri Saringat Master of Computer Science Budi Luhur University Jakarta Indonesia Information Systems Study Program Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Tun Hussein Onn Malaysia University

ISBN: (数字)9798331529376

ISBN: (纸本)9798331529383

The Plasmodium parasite, which causes malaria, is an acute fever illness that infects people when a female Anopheles mosquito bites them. It is predicted that malaria would claim 619,000 lives in 2021, with 96% of those deaths occurring in the African continent. We can achieve this by using a microscope to examine thick and thin blood smears. The proficiency of a microscope examiner is crucial for doing microscopic examinations. Consider how time-consuming, ineffective, and costly it would be to examine thousands of malaria cases. Consequently, Creating an automated method for detecting malaria parasites is the aim of this study. We employ a MobileNetV2 pretrained model with CNN technology. Because it has been trained on dozens or even millions of data points, this pretrained model is incredibly light but dependable. There are two main benefits of automatic malaria parasite detection: firstly, it can offer a more accurate diagnosis, particularly in locations with limited resources; secondly, it lowers diagnostic expenses. The optimizer utilizes Adam Weight, the criteria uses NLLLoss, and the model is trained using 32 for batch_size. In the fourteenth epoch, we obtained the maximum accuracy score of 96.26% based on the training data. The outcomes of the predictions demonstrate how excellent this score is. EfficienceNet, DenseNet, AlexNet, and other pretrained models are among the alternatives that scientists are advised to try training with.

关键词： Training Adaptation models Accuracy Costs Malaria Microscopy Data visualization Training data Cost function Data models

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A NEW HOPE: contextual privacy policies for mobile applications and an approach toward automated generation 24

A NEW HOPE: contextual privacy policies for mobile applicati...

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Proceedings of the 33rd USENIX Conference on Security Symposium

作者： Shidong Pan Zhen Tao Thong Hoang Dawen Zhang Tianshi Li Zhenchang Xing Xiwei Xu Mark Staples Thierry Rakotoarivelo David Lo School of Computing Australian National University and Software and Computational Systems Research Program CSIRO's Data61 Software and Computational Systems Research Program CSIRO's Data61 Khoury College of Computer Sciences Northeastern University School of Computing and Information Systems Singapore Management University

ISBN: (纸本)9781939133441

Privacy policies have emerged as the predominant approach to conveying privacy notices to mobile application users. In an effort to enhance both readability and user engagement, the concept of contextual privacy policies (CPPs) has been proposed by researchers. The aim of CPPs is to fragment privacy policies into concise snippets, displaying them only within the corresponding contexts within the application's graphical user interfaces (GUIs). In this paper, we first formulate CPP in mobile application scenario, and then present a novel multimodal framework, named SEEPRIVACY, specifically designed to automatically generate CPPs for mobile applications. This method uniquely integrates vision-based GUI understanding with privacy policy analysis, achieving 0.88 precision and 0.90 recall to detect contexts, as well as 0.98 precision and 0.96 recall in extracting corresponding policy segments. A human evaluation shows that 77% of the extracted privacy policy segments were perceived as well-aligned with the detected contexts. These findings suggest that SEEPRIVACY could serve as a significant tool for bolstering user interaction with, and understanding of, privacy policies. Furthermore, our solution has the potential to make privacy notices more accessible and inclusive, thus appealing to a broader demographic. A demonstration of our work can be accessed at https://***/SeePrivacy/

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Nge-BatikVR: Innovative Batik Learning and Marketing Through Virtual Reality Serious Games with Immersive Hands-On Experience

Nge-BatikVR: Innovative Batik Learning and Marketing Through...

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Advanced Applied Informatics Winter (IIAI-AAI-Winter), International Congress on

作者： Dimas Ramdhan Galih Dea Pratama Michael Francis Wijaya Muhammad Edo Syahputra Wihendro Computer Science Department Game Application & Technology Program School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia

Batik is a cultural heritage of Indonesia, recognized by WHO as an Intangible Cultural Heritage. Batik is dyed by skilled craftsmen who make patterns with dots and lines on the fabric from melted wax. The process is complicated, so few people can experience all the steps in crafting Batik. From these problems, immersive learning media are needed so everyone can learn and gain experience in Batik crafting from start to finish. In this study, we will present Nge-BatikVR, a serious game application that introduces Batik through Virtual Reality and offers an immersive experience of learning Batik from various regions with interactive hands-on feature aimed at people to better understand and learn Batik. Nge-BatikVR offers four main features called Sinau (Learn), Kuis (Quiz), Nge-Batik (Simulation) and Toko (Shopping), with the main purpose to present interactive and engaging media useful for introducing and learning Batik with a fully immersive experience.

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