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2021 International Conference on Artificial Intelligence and Mechatronics Systems, AIMS 2021

作者： Sinaga, Ardiles Astuty, Eriana School of Computer Science Bina Nusantara University Informatics Department Bandung Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Bandung Indonesia

ISBN: (纸本)9781665424820

This study aims to help companies to be able to estimate the procurement of raw materials for production, not having stock of raw materials in the warehouse, and determine which suppliers can send goods quickly with affordable prices and good quality. Thus, the company is not optimal in the procurement of raw materials and the selection of appropriate raw material suppliers. In addition, the research aims to optimize the procurement of raw materials that can be used in forecasting in controlling raw materials and decision support systems for the selection of raw material suppliers. The method used to estimate the availability of raw materials is the Simple Moving Average and Analytical Hierarchy Process (AHP) method to determine suppliers. The results of this study indicate that the average percentage of forecast error is 4.17%. Whereas for supplier selection, the AHP method that is used can recommend which suppliers are eligible to be chosen based on predetermined criteria, then the results are sorted by highest ranking. It is expected that the results of this study can be used as a reference for further development, for example by creating information systems that can help companies. © 2021 IEEE.

关键词： Forecasting

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Development of Buffer Zone into Living Lab - Garuda Smart City Framework: Systematic Review

Development of Buffer Zone into Living Lab - Garuda Smart Ci...

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International Conference on ICT For Smart Society (ICISS)

作者： Gunadi Emmanuel Suhono Harso Supangkat Ford Lumban Gaol Benny Ranti Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Fakultas Sains dan Teknologi Univ. Katolik Musi Charitas Palembang Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Computer Science Department Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The phenomenon of urbanization in Indonesia is inevitable. The new residential and economic centers in suburban areas is also a problem in city development. The gradual planning and development of smart cities in a living lab require consideration of the right location for a living lab. This study wants to show that suburban areas as city buffer zones can become living laboratories for smart city development. The diversity of situations in cities and regencies across Indonesia, the potential for resources, and the problems faced are the challenges of developing a living lab - Garuda Smart City Framework. This research uses the method of reviewing the literature of research publications for the last five years (2019–2023) to obtain information on Smart City development in Indonesia. We collected selected articles from databases in Google Scholar, IEEE, and Scopus using the Publish and Perish 8. The search keywords used were garuda AND Smart city AND Framework. The findings show the potential and dynamics of buffer zones to become appropriate living laboratories. Smart city regional planning can more holistically involve neighborhoods and address urban issues.

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5S towards sustainable competitive advantage in franchise retail business 2

5S towards sustainable competitive advantage in franchise re...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Astuty, E. Sinaga, A. Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Bandung Indonesia Informatics Department School of Computer Science Bina Nusantara University Bandung Indonesia

This study aims to find empirical evidence in filling the "how-to"gap of a service company in order to have a sustainable competitive advantage by adopting lean system or known as a workplace organization. This study surveyed 150 customers from three largest franchise minimarts in Bandung City in order to determine the characteristics and interrelations that occur in the three research objects observed, namely 5S or workplace organization, service's waste, and service quality. The method used is descriptive method and structural equation modeling based on the least squares method or PLS-SEM. The statistical tools used are SPSS20 and SmartPLS3. The results reveals that the three largest franchise minimarts in Bandung City, had a high level of service quality, low service's waste, and well-managed workplace organization. The relationship between them shows that the three franchise minimarts continue to survive and continue to grow after operating for more than 3 decades, because they implemented a workplace organization (5S, seiri-seiton-seiso-seiketsu-shitsuke), so that this can reduce the occurrence of service's waste by 82.4 %, where even this has an impact on increasing service quality by 27.9% with a very high model strength of 73.5%. © Published under licence by IOP Publishing Ltd.

关键词： Quality of service

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Ardian Budi Kusuma Atmaja Egi Muhammad Idris Hidayat Bambang Riyanto Trilaksono Simon Siregar Natsir Habibullah School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department Computer Engineering Faculty of Applied Science Doctoral Program of Electrical Engineering Institut Teknologi Bandung Telkom University

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees.

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Multi-Modal Music Mood Classification with Dynamic Classifier Selection

Multi-Modal Music Mood Classification with Dynamic Classifie...

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： João G. Bracaioli Vitório Alceu S. Britto Junior Costa Yandre M. G. Carlos N. Silla Graduate Program in Computer Science (PPGIA) Pontifícia Universidade Católica do Paraná (PUCPR) Curitiba Brazil Department of Informatics State University of Maringá (UEL) Maringá – Paraná Brazil

In this paper we investigate the suitability of different types of Dynamic Classifier Selection approaches for the task of multimodal music mood classification. The dynamic selection methods evaluated were: KNORA-UNION, KNORAELIMINATE, Dynamic Ensemble Selection Performance, Overall Local Accuracy, Local Class Accuracy, Multiple Classifier Behaviour, A Priori and A Posteriori. The experiments were performed using the Brazilian Music Mood Database, which is a multimodal database, containing the audio signal itself, beyond their visual representation (i.e. spectrogram) and the lyrics. The obtained results have shown that the use of dynamic classifier selection methods can improve the classification results for the task at hand.

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Comparison of Machine Learning Text Classification for Intent Sentiment Analysis

Comparison of Machine Learning Text Classification for Inten...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Abulwafa Muhammad Sarjon Defit Gunadi Widi Nur Cahyo Department of Informatics Technology Faculty of Computer Science Universitas Putra Indonesia YPTK Padang Padang Indonesia Doctoral Program in Information Technology Universitas Putra Indonesia YPTK Padang Padang Indonesia

Tourist destination reviews on Google Maps have become a valuable point of reference for visitors seeking enjoyable spots to visit. Additionally, users can gain insight into the reasons for writing reviews. Text classification is used to determine the motivation behind these reviews. The aim of this study is to compare machine learning (ML) text classification techniques for identifying the intent behind sentiments expressed as complaints (0), suggestions (1), opinions (2), statements(3), and awards (4). The ML techniques assessed are Multinomial Naive Bayes (MNB), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). To achieve this, tourist destination review data sets, comprising 738 reviews, were collected using web scraping from the Google Maps website. Preprocessing stages, including case-folding, tokenisation, filtering and stemming, are executed prior to the data being prepped for feature extraction with TF-IDF. The employed classification models perform well with KNN achieving 1.00 accuracy on a 90:10 data split, and SVM obtaining 0.90 on the same data split. Although, the Multinomial Naive Bayes algorithm with 0.70 accuracy on a 90:10 data split is classified as fair. Comparison of methods was conducted by means of a Receiver Operating Characteristic (ROC) diagram. The testing accuracy for the SVM method was found to be 95%, MNB at 91%, and KNN at 84%.

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An Approach to Detect Abnormal Submissions for CodeWorkout Dataset

arXiv

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arXiv 2024年

作者： Hicks, Alex Shi, Yang Arun-Balajiee Yan, Wei Marwan, Samiha Dept of Computer Science Virginia Tech BlacksburgVA United States Dept of Computer Science Utah State University LoganUT United States Lekshmi-Narayanan Intelligent Systems Program University of Pittsburgh PittsburghPA United States School of Informatics Computing and Cyber Systems North Arizona University FlagstaffAZ United States Dept. of Computer Science University of Virginia CharlottesvilleVA United States

Students’ interactions while solving problems in learning environments (i.e. log data) are often used to support students’ learning. For example, researchers use log data to develop systems that can provide students with personalized problem recommendations based on their knowledge level. However, anomalies in the students’ log data, such as cheating to solve programming problems, could introduce a hidden bias in the log data. As a result, these systems may provide inaccurate problem recommendations, and therefore, defeat their purpose. Classical cheating detection methods, such as MOSS, can be used to detect code plagiarism. However, these methods cannot detect other abnormal events such as a student gaming a system with multiple attempts of similar solutions to a particular programming problem. This paper presents a preliminary study to analyze log data with anomalies. The goal of our work is to overcome the abnormal instances when modeling personalizable recommendations in programming learning environments. © 2024, CC BY-NC-SA.

关键词： Students

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review 3

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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3rd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Noprisson, Handrie Ermatita, Ermatita Abdiansah, Abdiansah Ayumi, Vina Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3-25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50. © 2021 IEEE.

关键词： Weaving

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Scientometric Analysis of Artificial Intelligence Research in Agriculture 4

Scientometric Analysis of Artificial Intelligence Research i...

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4th International Conference on informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Pramono, Andi Hamim, Miftahul Prihatin, Sukeipah Yuli Arifuddin, Rahman School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Bina Nusantara University Entrepreneurship Business Creation Jakarta11480 Indonesia Politeknik Kota Malang Informatics Study Program Malang Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

Artificial Intelligence Research in Agriculture has grown so common, and the potential they provide is so revolutionary that it is considered essential for competitive growth. Until we conducted this research, only 1064 academic documents on Trends of Artificial Intelligence Research in Agriculture that we found from 2012 to 2021 were obtained by searching the Scopus database. This study uses bibliometric analysis methods to map scientific publications worldwide. We use an article selection process, the year limitation, then the database is exported to RIS and CSV format files. Researchers in the United States had the most published articles and were indexed by Scopus among the most prolific authors ($\mathrm{N}=287$), followed by the United Kingdom at second ($\mathrm{N}=139$) and Italy with 66 academic publications. Data analysis reveals an increasing trend in the number of Trends of Artificial Intelligence Research in Agriculture publications worldwide, as measured by the Scopus index. © 2022 IEEE.

关键词： Agriculture

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Post-Covid-19 Digital Nomadism: Beyond Work from (Almost) Anywhere

Post-Covid-19 Digital Nomadism: Beyond Work from (Almost) An...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： De Almeida, Marcos Antonio De Souza, Jano Moreira Correia, António Schneider, Daniel Rio de Janeiro Brazil Inesc Tec University of Tras-os-Montes e Alto Douro Vila Real Portugal College of Information Science & Technology University of Nebraska Omaha United States Postgraduate Program in Informatics Ppgi Ufrj Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

ISBN: (纸本)9798350337020

In this paper, we continue our investigations on digital nomadism and the impact of COVID-19 pandemic on the work-related aspects and lifestyle of digital nomads (DN). The findings presented in this empirical study reflect the analysis of the impact of COVID-19 outbreak (and its waves) on the market economy and work-life boundaries of DNs as perceived from posts and comments gathered from a Reddit community during the period of early March 2020 until the end of 2022. From this point, our results indicate that the massification of remote work among formal workers in response to COVID-19 pandemic has impacted both the formal labor market and the DN ecosystem. As a consequence, we argue that digital nomadism tends to play a critical role beyond work from (almost) anywhere (WFA) in a post-COVID-19 era taking into account the novel facets of nomadic work-lifestyle. © 2023 IEEE.

关键词： COVID-19 digital nomadism lifestyle Reddit slowmads wannabes work from almost anywhere

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