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Unsupervised News Topic Modelling with Doc2Vec and Spherical Clustering

Procedia computer science 2021年 179卷 40-46页

作者： Arif Budiarto Reza Rahutomo Hendra Novyantara Putra Tjeng Wawan Cenggoro Muhamad Fitra Kacamarga Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information System Bina Nusantara University Jakarta Indonesia 11480 Eureka AI Singapore Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In the digital and Internet era, companies are racing to profile their target users based on their online activities. One of the reliable sources is the news articles they read that can represent their interests. However, extracting latent information from the news articles is not an easy task for a human. In this paper, we introduced a practical model to automatically extract latent information from news articles with pre-determined topics. Our proposed model used unsupervised learning, thus alleviating the need for humans to label news items manually. Doc2vec was used to generate word vectors for each article. Afterward, a spectral clustering algorithm was applied to group the data based on the similarity. A supervised Long Short Term Memory (LSTM) model was built to compare the clustering performance. The best 1, best 3, and best 5 scores were used to evaluate our model. The result showed that our model could not outperformed LSTM model for the best 1 score. However, the best 5 score result indicated that our model was sufficiently robust to cluster the articles based on topic similarity. Additionally, the proposed unsupervised model was implemented in both an on-premise server, and a cloud server. Surprisingly, our proposed method could run faster in the cloud server despite its less number of CPU cores.

关键词： Topic Modelling Latent Information News Article Document Embedding Spherical Clustering

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Blockchain Technology Open Problems and Impact to Supply Chain Management in Automotive Component Industry 6

Blockchain Technology Open Problems and Impact to Supply Cha...

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6th International Conference on Computing, Engineering, and Design, ICCED 2020

作者： Surjandy Meyliana Spits Warnars, Hareco Leslie Hendric Abdurachman, Edi School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728191898

The study of the adoption of Blockchain Technology (BT) of the Supply Chain Management System (SCMS) automotive components industry still in infancy. BT's previous research topic mostly in virtual currency, security, and IoT. However, the automotive market's significant development causes several issues in the SCMS automotive components industry, such as fake components. Blockchain Technology (BT), as identified, might be possible as a way out for the development of SCMS automotive components. There are several research questions in this research, such as how BT can facilitate SCMS open issues? What is the BT impact in the SCM area? The study method used the systematic literature review (SLR) method to gather all information from 12 publishers and an international index journal. Seven open issues identified in this study and SCM's core operational aspect, such as supplier, logistics, manufacturer, distribution, and customer, have been identified impact with BT. © 2020 IEEE.

关键词： Automotive industry

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Decision support system using data warehouse for retail system

Decision support system using data warehouse for retail syst...

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International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Girsang, Abba Suganda Arisandi, Geri Elysisa, Calista Michelle Saragih, Melva Hermayanty Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

CMK company is a retail company that sell and distributes miniature vehicle items to small stores. CMK has several branches in various countries that use for operational and storage warehouse. This company faces the problem for analysing sales to decide the useful strategy since this company only uses Online Transaction Processing (OLTP) database. This study implements Online Analysis Processing (OLAP) database and data warehouse to provide useful information for this company by using the nine-step method designed by Kimball & Ross. The data will be performed into dashboard to make easier for CMK Company to analyze data. Furthermore, many useful information can be provided in short and efficient time. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Data warehouses

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Realtime Vehicle Counting Method Using Haar Cascade Classifier Model

Realtime Vehicle Counting Method Using Haar Cascade Classifi...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Prasetyo Mimboro Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Doctor of Computer Science Graduate Program Faculty of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Atma Jaya University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

The proliferation of digital camera technology has provided many digital images for object detection and counting in public places. This paper presents an experiment on the realtime vehicle counting method to be implemented in a single board computer. The proposed design's objective is to detect and count vehicles entering and exiting at entrances using haar cascade classifier algorithms and other automatic open and close door systems controlled by a single board computer (SBC). The proposed system was tested using raspberry pi 4 model B with a 4GB RAM platform. The empiric results using 3-minute video as input with a total of 113 passing vehicles the proposed method achieve of 91.2 % of average accuracy.

关键词： Mechatronics Automation Computational modeling Digital images Random access memory Object detection Logic gates

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A Blockchain Technology-Based for University Student Enrollment Process 6

A Blockchain Technology-Based for University Student Enrollm...

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6th International Conference on Computing, Engineering, and Design, ICCED 2020

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

ISBN: (纸本)9781728191898

University in Indonesia contemporary is looking for a solution to improve the university documentation such as certificate and transcript. But fake diploma certificate and transcript is an issue reported in several articles recently. The new technology called Blockchain has been elaborate and predicted can be used to solve the issue because of blockchain characteristics which are immutable, secure, tamperproof and unchangeable. The enrollment process is one of the vital process for university before the document can be made. Therefore, the research tries to elaborate deeply to create a model of the university student enrollment process. The research question of this research is how Blockchain Technology can be merge in the enrollment process? The model has been validated by several universities in Indonesia. Forum Group Discussion had been performed to discuss for enrollment process. In the end, many benefits come up from blockchain technology utilization to produce a reliable document such as diploma certificate and transcripts. © 2020 IEEE.

关键词： Blockchain

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Improved LSTM hyperparameters alongside sentiment walk-forward validation for time series prediction

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wahyuddin, Eko Putra Caraka, Rezzy Eko Kurniawan, Robert Caesarendra, Wahyu Gio, Prana Ugiana Pardamean, Bens Department of Statistical Computing Politeknik Statistika STIS Jakarta 13330 Indonesia Statistics Indonesia (BPS) Jl. Dr Sutomo 6-8 Jakarta Indonesia School of Economics and Business Telkom University Bandung 40257 Indonesia Research Center for Data and Information Sciences Research Organization for Electronics and Informatics National Research and Innovation Agency (BRIN) Bandung 40135 Indonesia Faculty of Integrated Technologies Universiti Brunei Darussalam Gadong BE1410 Brunei Darussalam Department of Mathematics Universitas Sumatera Utara Medan 20155 Indonesia Bioinformatics and Data Science Research Centre Bina Nusantara University DKI Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University DKI Jakarta 11480 Indonesia

This study aims to address the common issue of biased estimation errors in time series modeling by analyzing the error in locating ideal hyperparameters and defining appropriate validation methods. Specifically, it focuses on predicting the stock price of Bank Rakyat Indonesia using a combination of historical stock prices, technical indicators, exchange rates, and news sentiment data, while determining the optimal variables for deep learning models. Employing a deep learning-based Long-Short Term Memory (LSTM) model, the study optimizes hyperparameters alongside walk-forward validation for time series prediction. It explores different combinations of variables and adapts the sliding window approach to the context of the data. The results highlight the importance of optimizing hyperparameters and utilizing walk-forward validation for accurate time series prediction. The model incorporating historical stock prices and sentiment scores outperforms others, achieving an RMSE of 96.61 and MAE of 86.97. Incorporating sentiment scores reduces RMSE by 39.55 % compared to models using only historical stock prices, while adding technical indicators does not yield improvement. This study contributes to the field by addressing the issue of biased estimation errors in time series modeling, offering insights into the optimization of hyperparameters and validation methods for accurate predictions. It also underscores the significance of incorporating sentiment analysis alongside historical stock prices for improved forecasting accuracy. © 2024 The Authors

关键词： LSTM Sentiment analysis Stock price prediction Time series modeling Validation methods

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Jakarta Smart City Mobile Application for Problem Reporting

Jakarta Smart City Mobile Application for Problem Reporting

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Artificial Intelligence and Smart Systems (ICAIS), International Conference on

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

ISBN: (数字)9781728195377

ISBN: (纸本)9781728195384

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.

关键词： Smart cities Social networking (online) Databases User interfaces Mobile applications Artificial intelligence Business

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Survey on Quality Assurance Testing on Service Oriented Architecture

Survey on Quality Assurance Testing on Service Oriented Arch...

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International Conference on Information Management and Technology (ICIMTech)

作者： Jonathan Andreas Pangestu Lim Dionisius Saviordo Thenuardi Benfano Soewito Anna Antonyova BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia University of Presov Slovak Republic

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Service-Oriented Architecture (SOA) has greatly influenced the world of software development with the proposed combination of business process and application (service). Ensuring that correct implementation of business process in each service in SOA environment is quite different than monolithic applications, where each service must be tested independently and jointly, depending on targeted testing scope. With numerous proposed approaches for solving such challenge, this paper reviews some of those approaches to ease readers understanding of what can be done in testing in SOA environment. More specifically, this paper provides review on generic proposed approaches, unit testing, and integration testing approaches as part of quality assurance testing on SOA environment. In summary, the details of testing implementation will differ for each enterprise/organization as each has different set of requirements to satisfy.

关键词： Testing Service-oriented architecture Business Tools computer science computer architecture

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Evaluation Model of Success Change Management in Banking Institution Based on ITIL V3 (Case Study)

Evaluation Model of Success Change Management in Banking Ins...

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International Conference on Information Management and Technology (ICIMTech)

作者： Recky Arisenta Suharjito Arief Agus Sukmandhani BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Online Learning Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Management of Information Technology Services (ITSM) is very important to improve good services to stakeholders, especially in the banking world. A company often has problems to achieve the standardization of Information Technology (IT) services. This study aims to find forms of improvement that can be carried out by the System Change Management division based on the Information Technology Infrastructure Library (ITIL) version 3 framework in making recommendations for improvement and increasing maturity level measurements based on the value expected by management and evaluating the Continual Service Improvement process already done this time.

关键词： Organizations Process control Standards organizations Information technology computer science

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Identification of Features in ANN's Black Box using Dimensional Reduction and Correlation Analysis: A Case Study of Cardiovascular Disease Dataset

Identification of Features in ANN's Black Box using Dimensio...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Boby Siswanto Yaya Heryadi Wayan Suparta Antoni Wibowo Haryono Soeparno Lukas Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Atma Jaya University Jakarta Indonesia

ISBN: (纸本)9781665499705

Artificial Neural Network (ANN) is a machine learning algorithm that can perform classification. ANN has limitations; namely, it has a black box working principle, which is unsure which feature is the most influential. This study is to identify the most influential features inside the ANN's black box using a classification model by applying Principal Component Analysis (PCA) dimension reduction combined with Pearson correlation analysis. The result of the proposed model can identify the name of the main features of the data inside the ANN's black box. This study uses two public Kaggle cardiovascular datasets. The first dataset consists of 13 features, and the second dataset consists of 12 features. The result is height and gender are the most influential features in the first dataset with the correlation value of 0.734; sex and smoking are the most influential features in the second dataset with the correlation value of 0.728. Black box model result with 2 PCA's features against a model with height and gender features in the first dataset resulting from the same accuracy on the test dataset of the classification prediction results with the value of 49.90%, while on the second dataset 58.30%.

关键词： Dimensionality reduction Analytical models Correlation Mechatronics Machine learning algorithms Artificial neural networks Predictive models

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