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Measurement of airline service sentiment analysis using vector space model

AIP Conference Proceedings 2024年第1期3132卷

作者： Aries Maesya Harco Leslie Hendric Spits Warnars Ford Lumban Gaol Benfano Soewito Department of Computer Science BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

Airlines are an organization that provides flight services for passengers or goods in Indonesia. There are many airlines available at this time giving passengers the option to choose the airline they want to use. Online reviews are one factor that is quite important in influencing consumer trust and interest in choosing an airline. On the Tripadvisor site, few or many reviews are given by consumers will have an influence on other potential customers but monitoring and organizing reviews from other consumers is not easy. There are too many reviews published from online review sites if they are processed manually. Therefore, it is necessary to use a sentiment analysis application to classify positive, negative, and neutral reviews from consumers so that it speeds up and makes it easier to review the shortcomings of each airline. Method Vector Space Model is used because it is relevant and effective in searching and categorizing text documents by using Cosine Similarity to look for similarities between the query vector and the document vector. The evaluation method used is Confusion Matrix which will calculate the accuracy precision and recall of the resulting test value. The results of the evaluation and validation carried out by this study resulted in an accuracy value of 76,42% with a value of precision of 83% and a recall of 87%.

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Data Mining and Bioinformatics Approaches to Elucidate Bacterial Communities in the Extreme Environment

Data Mining and Bioinformatics Approaches to Elucidate Bacte...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Rudi Nirwantono Faisal Asadi Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Mathematics Department School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

Bacteria are microscopic organisms that can be found in many environments. They are abundant and have many roles in our life. Studying bacteria is essential so that we can identify the bacteria that are needed for many industrial applications. However, the main problem is that majority of the bacteria are unculturable, hampering the exploration of bacteria from different environments. Metagenomics approach which employs Next Generation Sequencing technology could help study bacteria by utilizing 16S rRNA marker gene. This study aims to demonstrate data mining and bioinformatics approaches to analyze 16S rRNA sequencing data. The raw sequencing data of 16S rRNA was collected from biological database. Then, the data were trimmed, denoised, and clustered to generate Amplicon Sequence Variants (ASVs). Diversity (alpha and beta) and taxonomic analyses were then conducted to elucidate the bacterial diversity and taxonomic profile of ASVs. The results of this work showed that Shannon and PD indices in China's hot spring were higher than Singapore and the USA. Furthermore, a significant difference was observed in the PD index. The unweighted UniFrac distance also showed there was a significant difference of the bacterial communities between the three locations. In addition, the taxonomic investigation unveiled prevalent bacterial groups in the ecosystem, namely Proteobacteria, Chloroflexi, Cyanobacteria, and Crenarchaeota. The research outcomes have the potential to serve as a foundational resource for subsequent bacterial metagenomic research, particularly the hot spring environment.

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E-Business Startup: "universia" As University Collaborator System 8

E-Business Startup: "universia" As University Collaborator S...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Oktavia, Tanty Kaslie Gaol, Ford Lumban Hosoda, Takaaki Bina Nusantara University School of Information Systems Information Systems Department Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program-Computer Science Computer Science Department Jakarta11530 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (纸本)9781665416979

According to Covid 19 pandemic every process has to shifting to collaborate with digital technology. One of the field that pushes to shift is Education field. Undergraduate education level, is one of many strategies to improve people competency. In Indonesia, the number of people has steadily increased. However, they have to improve their level of competency to compete with their competitor. According to this condition, many prospective student difficult to find information that their need to decide a place to study. There are many consideration factors that will involved in this decision. Therefore, in this research will build university collaborator system that can support analysis from prospective student perspective to choose education institution. To build this business design this study involve some analysis such as industrial competition will be using Porter Five Force's and supported by Business Model Canvas to define Universia's business model, as well as financial projections for the next seven years. According to the Porter Five Forces model, the information services market around universities still has a lot of room for new entrants. The results of the business model canvas analysis show that, despite being a newcomer to the sector, Universia has a number of value propositions that its competitors do not. Universia's product will be generated in the web based application. The application will be designed using Object Oriented Analysis and Design (OOAD) in conjunction with the Extreme programming approach, which includes steps such as planning, designing, coding, and testing. The result of this study is a system collaborator that can be bridge between prospective student and university, so the prospective student can easily find the information that their need to choose university. © 2021 IEEE.

关键词： Students

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The effects of mobile marketing collaborator on consumers' impulse buying behavior in online marketplace during pandemic 6

The effects of mobile marketing collaborator on consumers' i...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Kusuma, Alvita Vania Daniel, Juan Hasri, Raja Alan Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (纸本)9781665449373

This study analyzes the influence of the COVID-19 pandemic on impulse buying on the marketplace platform in Jakarta. This research is motivated because the COVID-19 pandemic period lasted quite a long time. Therefore, this research was conducted so that it can be useful for entrepreneurs or marketplace sellers during the COVID-19 pandemic. The research method used is descriptive quantitative method. Data collection techniques using questionnaires and literature study. The techniques used in statistical testing include validity testing, reliability testing, and hypothesis testing. When the research was conducted from September 2020 to January 2021. The results obtained were that there was a relationship between variables, such as mobile marketing, discounts, and lifestyle that could affect impulse buying on the marketplace even though they were moderately related. © 2021 IEEE.

关键词： COVID-19

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The Impact of Online Learning System Collaborator on Students' Ability 8

The Impact of Online Learning System Collaborator on Student...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Adrian, Steven Tandy, Jovan Ardiyansyah, Sultan Adhitya Evangeline, Gabriella Dendy Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Bina Nusantara University School of Information System Information Systems Department Jakarta Barat Indonesia Bina Nusantara University Binus Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (纸本)9781665416979

Pandemic Covid-19 has change learning process to use online learning platform to limit interaction between participant of learning and reduce the Covid-19. This shifting has a major impact on education. Even though, many things have been done by education institution, lecturers, and students in adapting to online learning. In this study focus to check the effect of online learning on students' ability to understand the learning process. In this research, we use quantitative approach. To collect the data, this study uses a questionnaire method and in data analysis this study uses descriptive methods. In the results of this research can conclude that there is a positive influence from online learning on student's ability to understand the material. Therefore, higher education institution have to consider online learning to be good so that in the future it can continue to be developed or upgrade so that it can make it easier for students to understand the material and learn effectively and efficiently. © 2021 IEEE.

关键词： Students

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Weather Prediction in Agriculture Yields with Transformer Model

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Procedia computer science 2024年 245卷 750-758页

作者： Yulyani Arifin Ilvico Sonata Maryani Elizabeth Paskahlia Gunawan Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia Information System Department School of Information System Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia

Agriculture has a lot of relations with SDG from United Nations especially in end hungers and sustainable agriculture. One of factor important in agriculture is weather. Weather prediction is very important in agriculture. Weather greatly influences agricultural yields and the types of crops to be planted. Weather predictions, especially temperature and humidity, can be done using time series data analysis. Current developments in deep learning enable more accurate predictions of temperature and humidity based on time series dataset. Some deep learning models can be used to predict data based on training using time series data. The deep programming models used include Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). The Transformer deep learning model, which was first introduced in 2017, is a sequence-to-sequence model which is very suitable for predicting time series data. This paper will explain temperature and humidity prediction using the Transformer deep learning model. Experimental results show that the Transformer model can predict temperature and humidity based on training results using a time series dataset. The accuracy obtained by the Transformer deep learning model is better compared to the LSTM deep learning model as indicated by lower MAE, MSE and RMSE values compared to the LSTM model.

关键词： Forecast LSTM SDG Goals Time series Transformer Weather

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Sarcasm detection in twitter - Performance impact while using data augmentation: Word embeddings

arXiv

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arXiv 2021年

作者： Handoyo, Alif Tri Hidayaturrahman Suhartono, Derwin Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Sarcasm is the use of words usually used to either mock or annoy someone, or for humorous purposes. Sarcasm is largely used in social networks and microblogging websites, where people mock or censure in a way that makes it difficult even for humans to tell if what is said is what is meant. Failure to identify sarcastic utterances in Natural Language Processing applications such as sentiment analysis and opinion mining will confuse classification algorithms and generate false results. Several studies on sarcasm detection have utilized different learning algorithms. However, most of these learning models have always focused on the contents of expression only, leaving the contextual information in isolation. As a result, they failed to capture the contextual information in the sarcastic expression. Moreover, some datasets used in several studies have an unbalanced dataset which impacting the model result. In this paper, we propose a contextual model for sarcasm identification in twitter using RoBERTa, and augmenting the dataset by applying Global Vector representation (GloVe) for the construction of word embedding and context learning to generate more data and balancing the dataset. The effectiveness of this technique is tested with various datasets and data augmentation settings. In particular, we achieve performance gain by 3.2% in the iSarcasm dataset when using data augmentation to increase 20% of data labeled as sarcastic, resulting F-score of 40.4% compared to 37.2% without data augmentation. © 2021, CC BY.

关键词： Social networking (online)

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Analysis of Shoping Intention Using E-Commerce during Pandemic 8

Analysis of Shoping Intention Using E-Commerce during Pandem...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Wijaya, Alessandro Bryan Tio, Fendy Malaysiani, Liza Azzahra Sanjaya, Sandi Martin, Yessin Rio Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665416979

This study aims to investigate people's shopping intentions using e-commerce during the pandemic in Indonesia. The method used in this research is the quantitative method in which the results of the study are used as an assumption and research discussion. Data collection was carried out by questionnaires then measure using t-test. The result can be concluded that the intention to shop using e-commerce during the COVID-19 pandemic is influenced using e-commerce features and e-commerce techniques. These results indicate that the intention to shop using e-commerce can increase if the availability of goods in e-commerce is quite complete, the quality of goods sold is very high, normal prices and technical requirement, such as speed, security, and a good e-commerce design system. © 2021 IEEE.

关键词： COVID-19

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The Role of Financial Technology for Development of Micro, Small and Medium Enterprises (Msmes) in Indonesia 11

The Role of Financial Technology for Development of Micro, S...

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11th International Conference on Communication and Network Security, ICCNS 2021

作者： Meiryani, Meiryani Hanna Uli Pakpahan, Noviyanti Wahyuningtias, Dianka Mad Daud, Zaidi Liawatimena, Suryadiputra Accounting Department Faculty of Economics and Communication Bina Nusantara University Jakarta11480 Indonesia Hotel Management Department Faculty of Economics and Communication Bina Nusantara University Jakarta11480 Indonesia Accounting Department Faculty of Economics and Business Universiti Putra Malaysia Malaysia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450386425

The rapid development has made financial technology/financial technology's innovations more diverse according to the needs and financial problems that arise. With the existence of financial technology (financial technology) it can also make the financial service process faster, more effective and easier. Because of the development in the field of financial technology with the various solutions offered, this study aims to examine the role of financial technology for the development of MSMEs (Micro and Medium Enterprises), this research also includes aspects of the role of financial inclusion for the development of MSMEs to be able to see how much public knowledge is about financial service products and risk knowledge. The case study in this research is MSMEs in the Tangerang area using quantitative methods. The results of research using multiple linear regression analysis found that the role of financial financial technology for the development of MSMEs has a significant positive effect. Meanwhile, financial inclusion for the development of MSMEs has a positive and insignificant effect on the dependent variable. This study concludes that the use of financial technology for MSME businesses, as well as the high reference to financial products, are important factors in encouraging the development of MSMEs. © 2021 ACM.

关键词： Linear regression

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Telematics Work Field Review Text Classification Using the Naïve Bayes Method

Telematics Work Field Review Text Classification Using the N...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Aries Maesya Yaya Heryadi Yulyani Arifin Lukas Wayan Suparta Computer Science Department BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Reseach Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia

Indonesia will benefit from a demographic boom in 2030 with a higher labor supply than in earlier decades. Then in industrial revolution 4.0 robotics and artificial intelligence will take the place of low-skilled or menial employment that don't require specialized expertise (AI). To aim research is Telematics Work Field Review Text Classification Using the Naïve Bayes Method. The method using Multinomial Naïve Bayes model which is trained to learn from patterns in training data set without being programmed explicitly. Then, based on the Term Frequency - Inverse Document Frequency, consider the weighting of the word used (TF-IDF). The text classification stage is then carried out using the multinominal nave bayes classification method with evaluation using the confusion matrix, following the acquisition of the TF-IDF value. In the study it took data with web crawling techniques on social media sites twitter. The data collected was 936 data consisting of 7,8% negative sentiments, 26,4% positive sentiments, and 65,8% neutrals. The results of accuracy testing using the Confusion Matrix. And from the results of such tests resulted in an accuracy of 66%, precision 73%, and recall 85%.

关键词： Social networking (online) Service robots Text categorization Blogs Training data Telematics Data models

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