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5th International Seminar on Research of Information technology and Intelligent Systems, ISRITI 2022

作者： Purwandari, Kartika Jeremy, Nicholaus Hendrik Arisaputra, Panji Philip, Samuel Suhartono, Derwin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665455121

Social media communications offer valuable feedback to firms about their products. Twitter users share their opinions about e-commerce products on social networking sites. This paper reports a study in sentiment classification for Indonesian drug products for automatically classifying Twitter data as expressing positive or negative sentiments or opinions. The study investigates the effectiveness of using a Decision Tree, Support Vector Machine, Random Forest, Na rve Bayes, and Logistic Regression, along with the term frequency-inverse document frequency used to classify 531 tweets into recommended (positive sentiment) and not recommended (negative sentiment). Among all traditional machine learning models, the highest average accuracy value is 88.6 in the RF model and the lowest average accuracy value is 80.2 when using the LR model. Judging from the average accuracy obtained, the DT and RF model used has a considerable performance © 2022 IEEE.

关键词： Sentiment analysis

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E-Government Interoperability: Provincial-Level Architecture Model to Enable Fast Healthcare Interoperability Resources (FHIR) 9

E-Government Interoperability: Provincial-Level Architecture...

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

作者： Wijayanti, Diana Urbaya, Satriawansyah Sitompul, Taufiq Adrian, Verry BINUS Graduate Program Bina Nusantara University Department of Information Systems Jakarta11480 Indonesia Program USAID Indonesia Jakarta12930 Indonesia University of Oslo Department of Informatics Oslo0316 Norway Binus Graduate Program - Doctor Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Jakarta Provincial Health Office Center of Data and Information Technology Jakarta10160 Indonesia

ISBN: (纸本)9798350390025

The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Office involves enhancing collaboration among public health entities for efficient data exchange and streamlined processes, especially between the Provincial and District Health Offices, public hospitals, government clinics, and primary health care centers (Puskesmas). Achieving interoperability requires standardized protocols and a well-defined architectural model to integrate data seamlessly. This study presents a provincial-level architectural model focused on improving electronic health records interoperability, aiming to promote the adoption of the national Fast Healthcare Interoperability Resources (FHIR) health information exchange platform and enhance the integrity of health data in Jakarta. The study methodology involves conducting literature reviews, observations, and discussions with representatives from healthcare facilities to develop the e-Government architecture model and prototype of the infrastructure layer aiming to facilitate the interoperability of Electronic Health Records (EHRs) across 93 healthcare facilities, all of which are part of the SPBE users. © 2024 IEEE.

关键词： e-government

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

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Frontiers of Structural and Civil Engineering 2022年第8期16卷 990-1002页

作者： Hai-Bang LY Thuy-Anh NGUYEN Binh Thai PHAM May Huu NGUYEN Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

This study examined the feasibility of using the grey wolf optimizer(GWO)and artificial neural network(ANN)to predict the compressive strength(CS)of self-compacting concrete(SCC).The ANN-GWO model was created using 115 samples from different sources,taking into account nine key SCC *** validation of the proposed model was evaluated via six indices,including correlation coefficient(R),mean squared error,mean absolute error(MAE),IA,Slope,and mean absolute percentage *** addition,the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence *** results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s *** that,an examination of the parameters impacting the CS of SCC was provided.

关键词： artificial neural network grey wolf optimize algorithm compressive strength self-compacting concrete

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Hate Speech Text Classification Using Long Short-Term Memory (LSTM) 4

Hate Speech Text Classification Using Long Short-Term Memory...

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4th IEEE International Conference of computer science and Information technology, ICOSNIKOM 2022

作者： Ariwibowo, Suminar Girsang, Abba Suganda Diana Bina Nusantara University Binus Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399073

This paper aims to build hate speech text classification model by applying a combination of LSTM and FastText. The features of hate speech & non-hate speech, target hate speech, and categories of the hate speech. Dataset of those features taken from previous research by Okky Ibrohim. FastText word embeddings is used for formation of text vectors that will be used as input of the LSTM training model. The evaluation results obtained by getting the level of accuracy using confusion matrix. The accuracy value of text classification in this study is 83.52% on the classification of hate speech, 78.44% on the classification of target labels for hate speech, 82.75% on the classification of the label for category of hate speech. © 2022 IEEE.

关键词： Long short-term memory

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Contribution of Data Visualization to Decision-Making: A Classification of Data Visualization Research Based on the Characteristics of Decision Problems

Contribution of Data Visualization to Decision-Making: A Cla...

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Pacific (formerly Asia-Pacific APVIS) Visualization Symposium

作者： Midori Sugihara Shuhei Takakai Kazutaka Takamatsu Kazuo Misue Graduate School of Science and Technology University of Tsukuba Department of Computer Science University of Tsukuba

ISBN: (数字)9798331505813

ISBN: (纸本)9798331505820

Data visualization is a critical tool for supporting decision-making across various domains. However, its effectiveness in addressing various decision-making problems is yet to be *** study systematically reviewed over 300 papers from major visualization journals and conferences and focused on 40 empirical studies. Using Franz and Kramer’s multidimensional decision-making framework, we classified and analyzed the characteristics of decision problems supported by data *** findings revealed three key insights: (1) data visualization predominantly supports organizational and community-level decision-making, whereas applications at individual and family levels remain limited; (2) support has expanded from structured evaluation problems to include semi-structured and recognition-primed decision-making; and (3) challenges persist in addressing unstructured problems and small-scale *** results highlight the evolving role of data visualization in supporting complex and interdependent decision scenarios. Future studies should address gaps in unstructured decision-making and investigate applications in small-scale contexts to enhance the adaptability and impact of visualization tools.

关键词： Decision making Data visualization

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction 3

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Nurcahyo, Aldian Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Compuer Science Binus Graduate Program Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia Doctor of Computer Science Bina Nusantara University Binus Graduate Program Compuer Science Departement Jakarta Indonesia

ISBN: (纸本)9798350394559

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices. © 2023 IEEE.

关键词： Forecasting

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A STUDY ON DYNAMIC RESPONSE DISPLACEMENT MEASURING METHODS FOR BUILDING UNDER EARTHQUAKE USING SATELLITE technology WITH TWO MOVABLE VIBRATION TABLES

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AIJ Journal of technology and Design 2024年第74期30卷 65-70页

作者： Hashimoto, Akihiro Mukai, Tomohisa Tajima, Kazuyuki Nakamura, Akihiro Ariki, Katsuyoshi Kinugasa, Hideyuki Dept. of Architecture Graduate School of Science and Technology Tokyo Univ. of Science Japan Building Dept. National Institute for Land and Infrastructure Management Program Management Division Ground Facilities Dept. The Japan Aerospace Exploration Agency Dept. of Structural Engineering Building Research Institute Dept. of Structural Engineering Building Research Institute Urban Renaissance Agency Japan Dept. of Architecture Faculty of Science and Technology Tokyo Univ. of Science Japan

In recent years, research has been conducted to establish a method for quickly and appropriately determining damage to buildings during an earthquake using sensors, and it’s useful to appropriately evaluate the maximum and residual displacement during an earthquake. The purpose of this study is to propose a disaster assessment method using a satellite positioning system that directly measures the response displacement of a building from satellite positioning information. In this paper, the positioning accuracy is verified when calculating the relative displacement using two movable vibration tables that assume the top floor of a building and the ground surface under earthquake. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Earthquakes

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Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

Human-Robot Interaction through an Object Grasped with Two F...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Senoo, Taku Konno, Atsushi Kawahara, Hiromichi Ishii, Idaku Course of Systems Science and Informatic Graduate School of Information Science and Technology Hokkaido University Kita 14 Nishi 9 Kita-ku Sapporo Hokkaido060-0814 Japan Smart Innovation Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8527 Japan

ISBN: (纸本)9781665481090

In this study, two-finger grasping based on plastic deformation control for human-robot interaction is designed and implemented. This control strategy is derived based on the concept that balances both retention of grasping force on objects and plastic behavior in response to external forces. The control law consists of a set of constraints and offsets with respect to the springs that appear in the Maxwell model. In particular, the inner loop that is robust against parameter errors is implemented for actual machine experiments. Simulation and actual experiments with a robotic hand are executed to validate the proposed control law. © 2024 IEEE.

关键词： Human robot interaction

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Effect of Introducing Leucine Residues into 2-Aminoisobutyric Acid-Based Amphiphilic Helical Peptides on Intermolecular Interactions and Peptide Self-Assembly

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ACS Omega 2025年第21期10卷 22184-22190页

作者： Yamaguchi, Kasumi Kusumoto, Tomoichiro Araki, Takeshi Gomibuchi, Yuki Yasunaga, Takuo Osada, Satoshi Taira, Junichi Department of Chemistry and Applied Chemistry Faculty of Science and Engineering Saga University Saga 840-8502 Japan Department of Bioscience and Bioinformatics Fukuoka 820-8502 Japan Department of Physics and Information Technology Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka 820-8502 Japan

In recent years, self-assembling de novo-designed peptides have attracted increasing attention as materials for constructing submicrometer-scale structures. We have previously conducted structure-activity relationship studies on the BXBA-20 series of 20-residue amphiphilic peptides containing 2-aminoisobutyric acid (Aib) [Higashimoto, Y. et al. (1999) J. Biochem. 125, 705-712;Hara, T. et al. (2001) J. Biochem. 130, 749-755;Taira, J. et al. (2010) J. Pept. Sci. 16, 607-612]. These peptides share the common sequence Ac-(Aib-Xxx-Aib-Ala)₅-NH₂, where the introduction of a hydrophilic amino acid at the Xxx position results in the formation of a hydrophilic face on one side of the helix. Among them, some peptides exhibited weak intermolecular association and interactions with lipid membranes, though none demonstrated the ability to form submicrometer-scale structures through self-assembly. In this study, we present BKBL-20, a new member of this peptide series incorporating leucine on the hydrophobic face and lysine on the hydrophilic face. Circular dichroism spectroscopy indicated strong association in buffer, while hemolysis assays revealed significant membrane disruption. Transmission electron microscopy further confirmed the formation of ordered fibrous or array-like structures. These findings suggest that BKBL-20 successfully combines self-assembly and membrane-disruptive functions. © 2025 The Authors. Published by American Chemical Society.

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Bamboo Forest Growth Optimization Algorithm for Night Image Enhancement 15th

Bamboo Forest Growth Optimization Algorithm for Night Image...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Shi, Hao-Jie Pan, Jeng-Shyang Chu, Shu-Chuan Kong, Lingping Snášel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9789819700677

The Bamboo Forest Growth Optimization(BFGO) algorithm is an algorithm proposed by the growth law of bamboo forest, which has the advantages of fast convergence and not easily falling into local optimum. In this paper we have experimented the BFGO with several other population intelligence optimization algorithms on 23 benchmark test functions and proved its superiority. Also we apply the bamboo forest optimization algorithm to nighttime image enhancement in this paper, and the algorithm achieves better results on this application. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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