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Technology Acceptance Readiness Analysis in the Context of Digital Tourism Village using Machine Learning Approach 9

Technology Acceptance Readiness Analysis in the Context of D...

引用

9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Prawira, Indra Andryani, Nur Afny Catur Yufriadi, Ebnu Bina Nusantara University Faculty of Digital Communication and Hotel & Tourism Mass Communication Program Communication Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Digital tourism village potentially accelerates rural development hence improving a country's economy. The Indonesian government has developed hundreds of tourism villages in recent years but has yet to popularize the development of digital villages. Technology design and development are pivotal factors in tourism villages' digitalization. Therefore, the development digital tourism village must consider village readiness by measuring technology adoption readiness or technology acceptance of the corresponding stakeholders. This paper presents the technology acceptance analysis in the context of a digital tourism village. We use a quantitative analysis approach using the TAM-UTAUT model with data collected from a questionnaire of 101 villagers (n=101) in Pasanggrahan Village, West Java, Indonesia. This research uses machine learning with clustering procedures to analyze the level of technology adoption readiness by implementing K-means Clustering algorithm. In addition, to observe the significance of each influencing factor to the technology adoption readiness level, feature importance analysis approach using Extra tree classifier algorithm is employed. The research finds that attitude toward use, perceived ease of use, and facilitating condition-have a considerable impact on the degree of readiness for technology adoption. On the other hand, the perceived utility and social impact are found to have minimal bearing on the preparedness level for technology adoption. Perceived ease of use and facilitating conditions are the most important factors to afford the acceleration of technology adoption readiness. The research contributes to the development of a digital tourism village and the analysis of technology adoption readiness using machine learning. © 2024 IEEE.

关键词： Adversarial machine learning

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Random Forest Based QSAR Model Analysis for Predicting Drug Effectiveness Against Mycobacterium Tuberculosis Bacteria 11

Random Forest Based QSAR Model Analysis for Predicting Drug ...

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Ekosputri, Alicia Josephine Ardianti, Amanda Anggreainy, Maria Susan Artanto, Brychan Fitriawati, Nora Valentina, Fanny Angelia Santoso, Vincent Kartamulya School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11530 Indonesia Bina Nusantara University Binus Online Learning Information Systems Department Jakarta11530 Indonesia

ISBN: (纸本)9798350389654

This research focuses on the use of machine learning methods, especially Random Forest, in designing tuberculosis drugs more effectively and efficiently. The research process begins with the creation of a QSAR (Quantitative Structure-Activity Relationship) model using a dataset from ChEMBL that includes compounds with activity against Mycobacterium tuberculosis. This model aims to predict the pIC50 value, which is an indicator of a compound's biological activity as a tuberculosis drug. The results of the Random Forest model showed high accuracy, which is 92%. This accuracy indicates that the model has a good ability in predicting the effectiveness of compounds against Mycobacterium tuberculosis. With this result, the developed model can be used as an auxiliary tool in the discovery of tuberculosis drugs and can be further developed to increase the effectiveness in drug research. © 2024 IEEE.

关键词： Prediction models

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Decision theory and risk simulation analysis for optimizing profit in paylater services

Decision theory and risk simulation analysis for optimizing ...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： Dominic, Nicholas Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

The projected increase in PayLater utilization reaches up to five million people by 2025. To optimize the yearly profit from their PayLater service, fintech companies must examine all possible risks before a unanimous decision is taken. Therefore, we proposed a unified decision framework derived from decision theory and the Monte Carlo simulation technique. Two schemes were coined: (1) a decision-making scheme, and (2) a risk simulation scheme. Throughout experiments, the framework was able to estimate several alternative decisions and their impacts, analyze the causes of failure and delays in the development of the PayLater service, and execute Monte Carlo simulations in up to 10,000 trials. Outputs of this study will benefit decision-makers in the fintech initiative before launching their PayLater products. © 2023 Elsevier B.V.. All rights reserved.

关键词： Fault tree analysis

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Data mining for the global multiplex weekly average income analysis

Data mining for the global multiplex weekly average income a...

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作者： Dominic, Nicholas Elwirehardja, Gregorius Natanael Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

The box office (BO) income had significantly declined up to 80% in 2020, as the COVID-19 pandemic emerged. To minimize further financial risks, multiplex (multiple cinema complexes) owners need to analyze their potential income for each movie, each week. Therefore, we developed a proper data mining strategy that allows multiplex owners to analyze and discover insights on how successfully produced movies could be. The methodology comprises (1) data loading and exploration, (2) data cleaning, (3) data selection, integration, and transformation using Pentaho, (4) data mining in which the results were stored in the MySQL database, and (5) pattern evaluation and presentation using Qlik Sense as the Business Intelligence (BI) dashboard. Based on our data mining methodology, we revealed that drama, comedy, action, and thriller are favorite genres. We also found that DreamWorks Animation and Pixar Animation Studios are both the most popular production houses, even Apatow Productions and Escape Artists still have the biggest revenue on average. © 2022 The Authors. Published by Elsevier B.V.

关键词： Animation

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A Q-Learning Hybrid BRKGA Applied to the Knapsack Problem with Forfeits 13

A Q-Learning Hybrid BRKGA Applied to the Knapsack Problem wi...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Souto, Gabriel Aritsugi, Masayoshi Mendonca, Israel Simonetti, Luidi González, Pedro Henrique Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350308365

This paper presents a hybrid BRKGA (Q-HBRKGA) that combines BRKGA with Q-learning and a Local Branching technique to solve the Knapsack Problem with Forfeits(KPF). The aim is to tackle this problem, a vari-ant of the 0-1 Knapsack Problem, where a penalty cost is imposed when both items of a forfeit pair are included in the solution. Notably, Q-HBRKGA achieves superior results compared to existing approaches, establishing a valid strategy for KPF problem-solving. Computational experiments, utilizing benchmark instances, demonstrate the efficacy of Q-HBRKGA by outperforming state-of-the-art methods documented in the literature. © 2024 IEEE.

关键词： Reinforcement learning

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Density Based Spatial Clustering of Applications with Noise and Sentence Bert Embedding for Indonesian Utterance Clustering

Density Based Spatial Clustering of Applications with Noise ...

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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Hasani, Muhammad Fikri Heryadi, Yaya Arifin, Yulyani Lukas Suparta, Wayan Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classification is a task of text classification. As in general text classification, the required dataset requires a label to carry out the classification process. To speed up and help the utterance analysis process, there is already a method, namely clustering, and Density-based clustering is a part of clustering that can determine cluster patterns based on arbitrary data, with DBScan as one of its algorithms. This research used 10000 client utterance data of awhatsapp based e-commerce conversation. SentenceBert also used as a state of art sentence embedding. This research yield silhouette score of 0.327 as the best result from eps of 0.1 and MinPts of 95. However, based on the cluster result, sentences labelled as noise can be further clustered. Text Preprocessing, text augmentation and sentence embedding techniques can be explored to increase the cluster performance. © 2023 IEEE.

关键词： Embeddings

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Bioinformatics exploration into potential mechanisms of Calamus draco for colorectal cancer treatment 9th

Bioinformatics exploration into potential mechanisms of Cala...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Kenneth, Christian Nirwantono, Rudi Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

As one of the cancer types with the highest incidence rates, colorectal cancer (CRC) would benefit from treatments with fewer side effects and reduced treatment-resistant potential. One of the options is to harness the anti-CRC potential of natural products. Previous studies have shown that Calamus draco exudate, dragon's blood, has anticancer activity in liver cancer and acute myeloid leukemia, but its bioactivity has not been studied in CRC. Here we conduct a bioinformatics study based on network pharmacology to explore the anti-CRC potential and mechanism of C. draco-derived compounds. The bioinformatics pipeline is composed of compound and target collection, biological network evaluation, and enrichment analysis. We found that there are 43 bioactive compounds from C. draco targeting 91 CRC-related targets, of which most compounds target MEN1, PTGS2, and IDH1. Further analyses show that the targets of C. draco are involved in the cellular response to hypoxia. By inhibiting those targets, C. draco bioactive compounds can potentially hinder angiogenesis and increase treatment response efficacy. © 2024 The Authors.

关键词： Lung cancer

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Mobile Application to Help Abandoned Pets 3

Mobile Application to Help Abandoned Pets

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Rahajeng, Salicca Dewi Nurfitriyani, Siti Julianingsih Akbar, Zakin Izzani Leonardo, Calvin Warnars, Harco Leslie Hendric Spits Warnars, Laurens Spits 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

ISBN: (纸本)9798350354348

As social beings, humans like to interact with each other, including other creatures of God, such as animals, and keep them as pets. Many pets, such as dogs, cats, birds, fish, rabbits, and so on, include unusual pets such as reptiles, pigs, insects, etc. As a result of the lack of human awareness of pets and the nature of keeping animals, which is only for fun, it is not soulful to keep animals. So when people are bored, they abandon their pets, which causes new problems in human life today. In this case, we created a mobile application that can be shared with pet lovers where they can share information about abandoned pets and the possibility of owning pets from these abandoned pets. Mobile applications were designed using use case diagrams to show business processes, class diagrams to show database models, and user interfaces to present a similar interface to users. This mobile application will become a platform that can gather all people who care about pets and make pets a part of humans. © 2024 IEEE.

关键词： Mobile applications

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Intelligent Decision Support System for Higher Education Institutions 9

Intelligent Decision Support System for Higher Education Ins...

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9th International Conference on Signal Processing and Intelligent Systems, ICSPIS 2023

作者： Afriliana, Nunik Meyliana Gaol, Ford Lumban Soeparno, Haryono Bina Nusantara University Binus Graduate Program Computer Science Program Computer Science Department Jakarta Indonesia Bina Nusantara University School of Information System Information System Department Jakarta Indonesia

ISBN: (纸本)9798350369922

To ensure the sustainability of their operations, higher education institutions have to establish a robust strategic plan. Higher education institutions have an obligation to continuously assess the quality of their educational offerings in every program to comply with the standards established by the government and other educational entities. The implementation of intelligent decision support systems is a feasible approach among other techniques for addressing the aforementioned challenges. An intelligent decision support system has the potential to enable the business to uphold its adherence to regulations, enhance operational effectiveness, and optimize overall performance. This study aimed to determine the current state of intelligent decision support systems through the implementation of a comprehensive literature review. The second goal is to evaluate the best practices, methods, and implementation of intelligent decision support systems within higher education institutions. The findings indicate that intelligent decision support systems have the capacity to serve as a viable option for higher education, particularly in terms of enhancing the accuracy and efficiency of decision-making processes. Intelligent decision support systems exhibit a strong correlation with the fields of data mining and computational intelligence techniques. Nevertheless, the amount of research conducted on this subject is limited. © 2023 IEEE.

关键词： Data mining

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Distributed temperature sensing for special induction motor applied in harsh environment 11

Distributed temperature sensing for special induction motor ...

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Photonic Instrumentation Engineering XI 2024

作者： Mazzo, Paulo H.R. Torelli, Gabriel A. Dreyer, Uilian J. Pelegrin, Jessé Stel, Henrique Da Silva, Luiz C.T. Romero, Gabriel A. Morales, Rigoberto E.M. da Silva, Jean C.C. Graduate Program in Electrical and Computer Engineering Federal University of Technology UTFPR Paraná PR Curitiba Brazil Graduate Program in Energy Systems Federal University of Technology UTFPR Paraná PR Curitiba Brazil Multiphase Flow Research Center - NUEM Federal University of Technology UTFPR Paraná PR Curitiba Brazil CENPES/PDIEP EE Petrobras Brazil Federal Institute Catarinense IFC Santa Catarina Brazil

ISBN: (纸本)9781510670464

This paper presents a study and development on the thermal mapping of a Three-phase Induction Motor for harsh environments application. These machines’ exceptional performance and precise speed control make them essential equipment in multiple industrial processes, such as Artificial Lift, which integrates with a multistage centrifugal pump to elevate fluids from the reservoirs to the surface. Increased motor speeds for higher production requirements can result in temperature rise, damaging the stator winding. Employing the Raman Distributed Temperature Sensing System (RDTS), we generate a comprehensive heat distribution map of the motor. ANSYS Motor-CAD was applied for computational simulations to perform steady-state thermal analysis, giving an overview of heat transfer among internal components and thermal limits for the instrumented motor. This preliminary study presents a series of experimental tests to evaluate the advantages of fiber optic temperature sensing in harsh environments, emphasizing its significance in improving electrical machines’ performance and reliability. © 2024 SPIE.

关键词： Centrifugal pumps

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