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Smart Data Intelligence (ICSMDI), International Conference on

作者： Elvina Jacia Gabriel Dyan Amelia Ifan Ford Lumban Gaol Tokuro Matsuo Department of Information System Bina Nusantara University Alam Sutera Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Social media is a tool that can be used by people to become with each other by creating, sharing, and exchanging information virtually through a network. However, in the current era, the notion of social media is not only about exchanging information, but also to support business products. The problem is how to compete tightly in this modern era in increasing the selling value of business products. The positive impact of social media for sales in business products are huge such as, increase sales, increase product promotion, greater market distribution. On the other side, the negative impact also takes part such as, the more competitors, the products compete fiercely in the market. This research aims to identify more the impact of social media on sales of business products that focused on business, benefit, and factor. The research method that we used is quantitative which focuses on the number of samples of respondents to support the research results and the results are in the form of a graphic that shows the answers of the respondents to the questionnaire.

关键词： Graphics Freeware Video on demand Social networking (online) Multimedia Web sites Media Internet telephony

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Integration of the Use of Conventional technology Towards Smart Home technology for People in the City of Jakarta

Integration of the Use of Conventional Technology Towards Sm...

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International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Febian Wijaya Lintang Gerald Christian Ongko Griselda Valerie Michelle Benedicta Vieri Aska Juneio Sembiring Zaldy Raditya Ananta Takaaki Hosoda Ford Lumban Gaol Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Smart Home technology offers technological concepts that can be controlled through smart devices to make it easier for the community. Therefore, smart home technology is starting to seize the home electronics market in Indonesia, especially in the city of Jakarta. This study aims to determine the integration of conventional technology into smart home technology for people in Jakarta. The research model in this study uses UTAUT2 which analyzes nine variables, namely Perceived Usefulness, Perceived Cost, Perceived Ease of Use, Social Influence, Perceived Compatibility, Trust, Perceived Pleasure, and Effort Expectations, Intention to Use Smart Home technology. After the responses were received, data analysis was carried out using the PLS-SEM approach with the SmartPLS application. The results of this study show that there are many people who live in Jakarta who are helped by the presence of smart home technology. However, there are some people who don't really know how to use a smart home because of a lack of knowledge about this technology.

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Long short-term memory (LSTM) model-based reinforcement learning for nonlinear mass spring damper system control

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Procedia computer science 2023年 216卷 213-220页

作者： Santo Wijaya Yaya Heryadi Yulyani Arifin Wayan Suparta Lukas Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta 55281 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

The Neural Networks (NN) model which is incorporated in the control system design has been studied, and the results show better performance than the mathematical model approach. However, some studies consider that only offline NN model learning and does not use the online NN model learning directly on the control system. As a result, the controller's performance decreases due to changes in the system environment from time to time. The Reinforcement Learning (RL) method has been investigated intensively, especially Model-based RL (Mb-RL) to predict system dynamics. It has been investigated and performs well in making the system more robust to environmental changes by enabling online learning. This paper proposes online learning of local dynamics using the Mb-RL method by utilizing Long Short-Term Memory (LSTM) model. We consider Model Predictive Control (MPC) scheme as an agent of the Mb-RL method to control the regulatory trajectory objectives with a random shooting policy to search for the minimum objective function. A nonlinear Mass Spring Damper (NMSD) system with parameter-varying linear inertia is used to demonstrate the effectiveness of the proposed method. The simulation results show that the system can effectively control high-oscillating nonlinear systems with good performance.

关键词： Model-based Reinforcement Learning Random-Shooting Policy LSTM MPC Nonlinear System

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IoT-Based Strawberry Disease Detection With Wall-Mounted Monitoring Cameras

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IEEE Internet of Things Journal 2024年第1期11卷 1439-1451页

作者： Lin, Yi-Bing Liu, Chun-You Chen, Wen-Liang Chang, Chia-Hui Ng, Fung-Ling Yang, Krista Hsung, Jerry Department of Computer Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan China Medical University College of Humanities and Sciences Taichung404 Taiwan National Cheng Kung University MiinWu School of Computing Tainan701 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Yang Ming Chiao Tung University College of Biological Science and Technology Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Industrial Development Graduate Program College of Biological Science and Technology Hsinchu30010 Taiwan Proto Solution System Company Ltd. Hsinchu302052 Taiwan

This article proposes StrawberryTalk, an Internet of Things (IoT) platform for image-based strawberry disease detection. StrawberryTalk reuses the wall-mounted monitoring cameras without extra hardware cost. The contributions of StrawberryTalk are the utilization of IoT for automatic photo shoot and the wind detection mechanism to eliminate the obscure photos due to the wind effects. Also, the data preprocessing and the infection detection models are manipulated as IoT devices to simplify the implementation of the multicascade artificial intelligence (AI) models. We derive the relationship between the camera zoom factor and the distance between the camera and the strawberries for optimal disease detection. Accuracy of detection may be affected by obscure photos. In terms of eliminating obscure photos due to wind effect, we analytically derive the relationship between the wind alert delay and the number of obscure photos that must be retaken. For the greenhouses in the Bao Mountain, we only need to retake one photo. Based on the experiments, the mean average precision (mAP) of StrawberryTalk (to detect exact spots in a leaf) can be up to 92.37%, which is better than the previous approaches. To detect if a pot has infected leaves, the accuracy of StrawberryTalk can be up to 97.92% at the zoom factor 30×. In commercial operation, it is important to detect all infected strawberry pots. StrawberryTalk is able to detect all infected pots (i.e., recall is 100%) with a camera of zoom factor of 12× . The accuracy is 96.88%. © 2014 IEEE.

关键词： Cameras

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System analysis for technology transfer readiness assessment of horticultural postharvest

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IOP Conference Series: Materials science and Engineering 2018年第1期337卷

作者： M Hayuningtyas T Djatna Graduate Program of Agro-industrial Technology School of Graduate and Post Graduate Studies Bogor Agricultural University Indonesia Department of Agro-industrial Technology Bogor Agricultural University Indonesia

Availability of postharvest technology is becoming abundant, but only a few technologies are applicable and useful to a wider community purposes. Based on this problem it requires a significant readiness level of transfer technology approach. This system is reliable to access readiness a technology with level, from 1-9 and to minimize time of transfer technology in every level, time required technology from the selection process can be minimum. Problem was solved by using Relief method to determine ranking by weighting feasible criteria on postharvest technology in each level and PERT (program Evaluation Review Technique) to schedule. The results from ranking process of post-harvest technology in the field of horticulture is able to pass level 7. That, technology can be developed to increase into pilot scale and minimize time required for technological readiness on PERT with optimistic time of 7,9 years. Readiness level 9 shows that technology has been tested on the actual conditions also tied with estimated production price compared to competitors. This system can be used to determine readiness of technology innovation that is derived from agricultural raw materials and passes certain stages.

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"Inviteful" engineering: Student perceptions of industrial engineering

"Inviteful" engineering: Student perceptions of industrial e...

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ASEE 2004 Annual Conference and Exposition, "Engineering Researchs New Heights"

作者： Trytten, Deborah A. Shehab, Randa L. Rhoads, Teri Reed Fleener, M. Jayne Harris, Betty J. Reynolds, Anne Walden, Susan E. Moore-Furneaux, Sandra Kay Kvach, Elizabeth Warram, Kim R. Murphy, Teri J. University of Oklahoma School of Computer Science University of Oklahoma Department of Industrial Engineering Human Technology Interaction Center University of Oklahoma College of Engineering School of Industrial Engineering University of Oklahoma Graduate Studies and Research College of Education Women's Studies Program Department of Anthropology University of Oklahoma Dept. of Instructional Leadership University of Oklahoma Res. Institute for STEM Education University of Oklahoma Department of Communication University of Oklahoma Department of Mathematics University of Oklahoma

Interviews of twenty-six industrial Engineering students and graduates were conducted during the first year of a three year study of the unexpected attainment of gender parity in the School of industrial Engineering at the University of Oklahoma (OU). An analysis of the pattern of participant responses gives insight into industrial engineering (IE) student perceptions of IE. The perceptions were grouped into three broad themes: Career Profile, Discipline Profile, and Discipline Meta-Profile. The Career Profile includes the availability of multiple career paths and flexible careers in this discipline in addition to the potential for the attainment of status through entry into management. People-oriented, broad, and systems-oriented are terms that were used to describe the Discipline Profile. Discipline Meta-Profile is used to describe the participant's perception of other people's perceptions of industrial engineering (i.e. what IE students think other people think). These participants felt that other engineers think of IE as easy, or "imaginary" engineering. The participants also thought that the discipline is invisible, even to other engineers. While the meta-perception of IE might seem to be problematic for the discipline, many of the participants reject the meta-perception. Some participants recognized that IE's focus on people and systems is simply different than other engineering disciplines, not necessarily easier. Other participants felt the potential to enter into management outweighed the discipline meta-perception. One student summarized the response particularly well when he noted that IE is "inviteful" engineering.

关键词： Engineering education

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A design of competitive cocoa agro-industry supply chain system in Putat village, Gunung Kidul district

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IOP Conference Series: Earth and Environmental science 2019年第1期335卷

作者： D M S Turnip Y Arkeman Muslich Graduate Program of Agro Industrial Technology School of Graduate & Post Graduate Studies Bogor Agricultural University Indonesia Department of Agro Industrial Technology Bogor Agricultural University Indonesia

Inconsistency quality and availability of cocoa beans become a serious problem for cocoa agro-industry. In general, we can not trace whose cacao beans are processed in the industry. This is due to the lack of integrated supply chain consisting of farmer, collector, trader, exporter and industry. This study aimed to produce a design of competitive cocoa agro-industry supply chain system with dynamic system approach. Integrated partnership between Sidodadi farmer's group in Putat village, Patuk subdistrict, Gunung Kidul district with TTP Nglanggeran, Cokelat nDalem and local collector give a competitive value for cocoa agro-industry supply chain. Through this, fermented beans directly distributed to industry and processed. Cocoa supply in scenario increase 2.61% from existing, decreasing the balance of cocoa beans supply demand up to 0.7%, raising the first level of cocoa beans quality up by 2022, and lifting the accumulation of Farmers group's profit up to 29.31%. The design of this system is expected to inform cacao stakeholders about the importance of partnerships to improve cocoa agro-industry competitiveness.

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction

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

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Intelligent Cybernetics technology & Applications (ICICyTA), International Conference on

作者： Aldian Nurcahyo Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Compuer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Compuer Science Departement Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

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.

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Evaluation of total phenolic compounds and antioxidant activity in amazon fruit

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Chemical Engineering Transactions 2018年 64卷 649-654页

作者： Ismael Montero, F. Chagas, Edvan A. Melo Filho, Antonio A. D. E. Saravia, Selvin A. M. Santos, Ricardo C. Chagas, Pollyana Cardoso Ednalva da, D. R. S. Duarte Post Graduate Program in Biodiversity and Biotechnology Bionorte State Coordination of Roraima UFRR Campus Paricarana Boa Vista-RRCEP 69304-000 Brazil Embrapa Rodovia 174 Km 8 Industrial District Boa VistaRRCEP 69301970 Brazil Post-Graduate Program in Chemistry PPGQ Center for Research and Graduate Studies in Science and Technology NPPGCT UFRR Campus Paricarana Boa Vista-RRCEP 69304-000 Brazil Post Graduate in Agronomy POSAGRO UFRR Campus Paricarana Boa Vista-RRCEP 69304-000 Brazil National University of Agriculture Carretera a Dulce Nombre de Culmi El Espino Catacamas-Olancho Spain National Postdoctoral Program of CAPES PNPD/CAPES associated to POSAGRO/UFRR Campus Cauamé BR 174 s/n Km 12 District Monte Cristo Boa Vista-RRCEP 69310-250 Brazil Graduate Program in Chemistry Center in Science and Technology CCT UFRR Campus Paricarana Boa Vista-RRCEP 69304-000 Brazil

ISBN: (纸本)9788895608563

In this work, nine fruits cultivated in the northern Amazon were studied: abiu (Pouteria caimito), acerola (Malpighia emarginata), araçá (Psidium cattleianum), bacuparí (Rheedia gardneriana), biribá (Rollinia mucosa), caçarí (Myrciaria dubia) (Annona squamosa), graviola (Annona muricata) and taperebá (Spondias mombin L.). The total phenolic compounds were evaluated in the pulp, seed and bark by means of the colorimetric reaction of Folin Ciocateau, as well as the antioxidant capacity in the different extracts. DPPH method and on the other hand by the iron reduction method. As the fruits that presented a greater quantity of phenolic compounds are in mg gallic acid. 100g-1 sample, we have: bark of camu camu (1241.1 ± 12.04), followed by the abiu bark with (1132,43 ± 8,10), araçá pulp (1080,21 ± 1,1) and Pulp of acerola (1071.4 ± 22.2). Evaluating the antioxidant capacity, the evaluated fruits that present a higher value of antioxidant capacity are the Araçá seed with EC50 value of (471,23 ± 21,23 g / g DPPH) and for iron reduction of (57,21 ± 4.11 mmol Fe2SO4 / g), followed by the EC50 of abiu bark (521.71 ± 1.34 g / g DPPH) and iron reduction of 411.43 ± 27.12 µmol Fe2SO4 / g), and for the camu-camu pulp (549.24 ± 21.13 g / g DPPH) and for reduction of iron (235.47 ± 11.44 mmol Fe2SO4 / g). Multivariate analysis methods were applied through Principal Component Analysis (PCA) with pulp having the highest correlation between data variability with 93.6% according to PCA. Copyright © 2018, AIDIC Servizi S.r.l.

关键词： Fruits

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