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Developing Organizational Resilience Model to Sustain Business Performance

Developing Organizational Resilience Model to Sustain Busine...

引用

2022 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2022

作者： Jonny Mangindaan, Dave Faculty of Engineering Bina Nusantara University Professional Engineer Study Program Industrial Engineering Department Jakarta Indonesia Bina Nusantara University Professional Engineer Study Program Faculty of Engineering Jakarta Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Organizational resilience is about combination of operational and strategic resilience to sustain company's performance. In the time of turbulence like COVID-19 pandemic era, this resilience is extremely needed for any organizations not only to bounce back from its disruption but also ensures its sustained performance. However, knowledge related to this ability is still lacking and developing to cover especially factors needed to develop resilience for organization. Thus, this paper is proposing an organizational resilience model that covers what factors known so far. For this research, 100 organizations were invited for the research using questionnaires as its instrument. Among these invited organizations, only 47 organizations have given their responses at rate of 47%. Partial Least Square Structural Equation Modeling (PLS-SEM) method using SmartPLS 3.0 was utilized for data processing. This confirms that organization should promote its resilience through operational dan strategic resilience to sustain its performance especially in times of turbulence especially during COVID-19 pandemic era. © 2022 IEEE.

关键词： COVID-19

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Sensing Performance Analysis of Mobile Robot Navigation Based on Depth Camera and Lidar

Sensing Performance Analysis of Mobile Robot Navigation Base...

引用

2023 International Conference on Computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Afrisal, Hadha Sofwan, Aghus Widayat, Widayat Isnanto, R. Rizal Diponegoro University Electrical Engineering Department Study Program of Professional Engineers Semarang Indonesia Diponegoro University Faculty of Engineering Electrical Engineering Department Semarang Indonesia Diponegoro University Study Program of Professional Engineers Faculty of Engineering Semarang Indonesia

ISBN: (纸本)9798350320954

One of the potential implementations of mobile robots in mitigating the risk of communicable diseases is for delivering items and handling materials with no-human contact. In that scenario, mobile robots require the capability of performing simultaneous multi-object detection and distance estimation for dynamic exploration in a real-world environment. Some existing research papers have contributed to the development of object detection or distance estimation, separately. However, there is still a lack of studies on simultaneous multi-object detection and distance estimation for robot navigation, especially in terms of performance analysis of the integrated techniques. One of the most challenging issues of integrating multi-object detection and distance estimation is the validation and evaluation of the type of objects with their relevant estimated distance to the robot. For that reason, this research aims to analyze the mobile robot's sensing performance in integrated simultaneous multi-object detection and distance estimation during navigation scenarios. A depth camera of Intel RealSense D455 and a rotating LIDAR of Slamtec RPLidar A1M8 are utilized in the experiments. The result of experiments shows that the object detection algorithm using Mobilenet SSD V2 can perform an accuracy of 74%, with precision, recall, and F1-Score consecutively achieving 74,54%, 74,00%, and 74,22%. The multi-object distance estimator also performs satisfactory results with a low measurement average error of 10.3 cm for indoor experiments. The integrated multiobject detector and distance estimator system can work in a real-time mode of 30 FPS, thence significantly improving the navigation performance of the mobile robot. © 2023 IEEE.

关键词： Object detection

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Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control 8

Threshold-Based Electroencephalography Brain-Computer Interf...

引用

8th Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2023

作者： Rusydi, Muhammad Ilhamdi Amrina, Elita Winata, Yoan Ramadhani, Salisa Nofendra, Riko Graduate School Universitas Andalas Engineering Faculty Program of Engineer Professional Education Electrical Engineering Department Padang Indonesia Universitas Andalas Engineering Faculty Electrical Engineering Department Padang Indonesia

ISBN: (纸本)9798350302851

Brain-Computer Interface (BCI) is a technique that uses real-Time brain impulses to connect with and control external devices. BCI provides a new method for controlling external devices by translating brain signals into computer commands, facilitating the daily lives of people with disabilities and enhancing their ability to exhibit expected behavior. A Brain-Computer Interface (BCI) system based on Electroencephalography (EEG) was built to control the robotic arm. The EEG signals utilized included both eyes blinking, the right eye, the left eye, and the jaw contraction. EEG data were recorded from seven healthy subjects. The threshold approach is used to classify EEG signals, with the feature employed being the amplitude of the EEG signal. The highest threshold value for the blinking signal was 0.6 mV with an accuracy of 97.9%, while the best threshold value for jaw contraction was 0.4 mV with an accuracy of 93.34 percent. The healthy, inexperienced participants took part in system testing. The total results of testing each robot movement yielded an overall success rate of 84.52 percent. Therefore, it was determined that the system could facilitate the operation of the length robot even if the user lacked prior experience with EEG-based systems. © 2023 IEEE.

关键词： Brain computer interface

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Java Bali Grid Mean Time To Failure Prediction using Machine Learning 1

Java Bali Grid Mean Time To Failure Prediction using Machine...

引用

1st International Conference on Technology, engineering, and Computing Applications, ICTECA 2023

作者： Sesotyo, Priyo Adi Pandjaitan, M.M. Lanny W. Lukas Universitas Katolik Indonesia Atma Jaya Professional Engineer Study Program Faculty of Engineering Jakarta12930 Indonesia Universitas Semarang Electrical Engineering Dept. Semarang50196 Indonesia Universitas Katolik Indonesia Atma Jaya Electrical Engineering Master Program Jakarta12930 Indonesia Jakarta12930 Indonesia

ISBN: (纸本)9798350360554

The role of Mean Time To Failure (MTTF) is critical to maintain cost-efficient in smart grids, as the predictive maintenance means for ensuring their reliability. Java Bali grid is the most important power network in Indonesia, because it holds 75% energy sales and the foundation of the Indonesian government, business and industrial sectors. One method for prediction in the machine learning is the Linear Regression, as part of the Supervised Learning technique. The regression model extracts the grid overload variable from MV distribution system, where connected load (MVA) divided by the number of MV customers. The model constructs the Linear Regression function, where the slope and intercept values found from the correlation between predicted response and actual response. After confronting the function f(x) and the coefficient of determination (R2), the test results for the MTTF prediction values for Java-Bali's region shows the higher accuracy when the R2 shows highest value. © 2023 IEEE.

关键词： Forecasting

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Sensing Performance Analysis of Mobile Robot Navigation Based on Depth Camera and Lidar

Sensing Performance Analysis of Mobile Robot Navigation Base...

引用

Computer Science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Hadha Afrisal Aghus Sofwan Widayat Widayat R. Rizal Isnanto Electrical Engineering Department & Study Program of Professional Engineers Diponegoro University Semarang Indonesia Electrical Engineering Department Faculty of Engineering Diponegoro University Semarang Indonesia Study Program of Professional Engineers Faculty of Engineering Diponegoro University Semarang Indonesia

关键词： Laser radar Navigation Robot vision systems Estimation Object detection Detectors Cameras

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Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control

Threshold-Based Electroencephalography Brain-Computer Interf...

引用

Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)

作者： Muhammad Ilhamdi Rusydi Elita Amrina Yoan Winata Salisa 'Asyarina Ramadhani Riko Nofendra Electrical Engineering Department Engineering Faculty Program of Engineer Professional Education Graduate School Universitas Andalas Padang Indonesia Industrial Engineering Department Engineering Faculty Program of Engineer Professional Education Graduate School Universitas Andalas Padang Indonesia Electrical Engineering Department Engineering Faculty Universitas Andalas Padang Indonesia

Brain-Computer Interface (BCI) is a technique that uses real-time brain impulses to connect with and control external devices. BCI provides a new method for controlling external devices by translating brain signals into computer commands, facilitating the daily lives of people with disabilities and enhancing their ability to exhibit expected behavior. A Brain-Computer Interface (BCI) system based on Electroencephalography (EEG) was built to control the robotic arm. The EEG signals utilized included both eyes blinking, the right eye, the left eye, and the jaw contraction. EEG data were recorded from seven healthy subjects. The threshold approach is used to classify EEG signals, with the feature employed being the amplitude of the EEG signal. The highest threshold value for the blinking signal was 0.6 mV with an accuracy of 97.9%, while the best threshold value for jaw contraction was 0.4 mV with an accuracy of 93.34 percent. The healthy, inexperienced participants took part in system testing. The total results of testing each robot movement yielded an overall success rate of 84.52 percent. Therefore, it was determined that the system could facilitate the operation of the length robot even if the user lacked prior experience with EEG-based systems.

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Disclosure Privacy Information Social Media on TikTok 9

Disclosure Privacy Information Social Media on TikTok

引用

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

作者： Syamsuar, Dedy Fahrezi, Fazri Favian, Ahnaf Irwansyah, Edy Irawan, Achmad Fakhri School of Information System Bina Nusantara University Faculty of Engineering Professional Engineer Program Dept. Information System Department Jakarta11480 Indonesia School of Information System Bina Nusantara University Information System Department Jakarta11480 Indonesia School of Information System Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

With the rapid development of technology, the use of social media by the public, especially among young people, is increasing. One of the social media platforms currently used by young people is the TikTok application. It is a video-based TikTok feature accompanied by music, writing, and pictures that are considered attractive, so teenagers like it to show their existence and self-disclosure. Therefore, this study aims to examine the intention of users to disclose their privacy. As the basis of the theory, this study deployed the privacy calculus theory, where the perceived benefits and perceived risks play crucial roles in the intention to disclose their privacy. The study successfully collected 369 responses. The empirical findings indicated that only the relationship between Perceived Personalization (PP) and Perceived Risk (PR) was not supported. However, all the remaining hypotheses were supported. These findings emphasize how several complicated variables influence social media users' intentions to disclose their privacy. When people feel in control of their privacy settings and see significant benefits, they are more likely to divulge personal information;nevertheless, perceived risks can greatly discourage users. © 2024 IEEE.

关键词： Differential privacy

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Prototype Design of Smart Diabetic Shoes with Lora Module Communication

Prototype Design of Smart Diabetic Shoes with Lora Module Co...

引用

2023 International Conference on Computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Purwono, Purwono Burhan, Asmat Nisa, Khoirun Wibisono, Sony Kartika Setiawan Mangkunegara, Iis Dewi, Pramesti Ma'Arif, Alfian Suwarno, Iswanto Universitas Harapan Bangsa Department of Informatics Purwokerto Indonesia Universitas Harapan Bangsa Department of Anesthesiology Nursing Purwokerto Indonesia Universitas Harapan Bangsa Department of Information Technology Purwokerto Indonesia Universitas Harapan Bangsa Nursing Study Program Purwokerto Indonesia Universitas Ahmad Dahlan Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Department of Engineer Professional Program Yogyakarta Indonesia

ISBN: (纸本)9798350320954

Diabetes is a disease that affects many people in the world. Diabetes mellitus is a type of metabolic disease in a person who suffers from blood glucose levels with extreme conditions, namely insufficient insulin production in the human body. Monitoring diabetes is an important concern for researchers because it can be useful for improving the quality of the nursing service system. One of the common conditions in diabetic patients is ulceration which is difficult to detect on time. Technology can minimize the total cost of monitoring chronic diseases such as Diabetes continuously and on time. This research focuses on solutions to produce IoT-based smart diabetic shoes that utilize pressure sensors and the temperature of the feet of people with diabetic feet. Smart diabetic shoes are made using the Lora E32 module to be applied to areas with poor internet connections. The results of the testing carried out for 60 seconds in this study succeeded in detecting the area of the foot that experienced the greatest pressure, which was located on the rear footrest with a portion of pressure of around 25 - 28% of the total body weight. The patient's foot temperature increases when the pedestal load is greater. The Lora E32 module also functions as a media transmitter and receiver at a distance of 2.2 km in sending sensor data. © 2023 IEEE.

关键词： Diseases

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Java Bali Grid Mean Time To Failure Prediction using Machine Learning

Java Bali Grid Mean Time To Failure Prediction using Machine...

引用

Technology, engineering, and Computing Applications (ICTECA), International Conference on

作者： Priyo Adi Sesotyo M.M. Lanny W. Pandjaitan Lukas Professional Engineer Study Program Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Electrical Engineering Dept. Universitas Semarang Semarang Indonesia Electrical Engineering Master Program Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

The role of Mean Time To Failure (MTTF) is critical to maintain cost-efficient in smart grids, as the predictive maintenance means for ensuring their reliability. Java Bali grid is the most important power network in Indonesia, because it holds 75% energy sales and the foundation of the Indonesian government, business and industrial sectors. One method for prediction in the machine learning is the Linear Regression, as part of the Supervised Learning technique. The regression model extracts the grid overload variable from MV distribution system, where connected load (MVA) divided by the number of MV customers. The model constructs the Linear Regression function, where the slope and intercept values found from the correlation between predicted response and actual response. After confronting the function f(x) and the coefficient of determination (R2), the test results for the MTTF prediction values for Java-Bali’s region shows the higher accuracy when the R2 shows highest value.

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Diaminoethane-crosslinked polyetherimide nanofiltration membrane for textile wastewater dye removal 3

Diaminoethane-crosslinked polyetherimide nanofiltration memb...

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3rd International Conference on Eco engineering Development, ICEED 2019

作者： Mangindaan, Dave Kasih, Tota Pirdo Professional Engineer Program Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia

In this work, diaminoethane (DAE) is applied to improve the properties of polyetherimide (PEI) nanofiltration (NF) membranes via crosslinking process with the core objective of removal of textile dye from wastewater. The membranes were fabricated by phase inversion thin film casting technique, from PEI/acetone/NMP (n-methyl pyrollidone) dope solution, crosslinked with DAE 2.5 % v/v in methanol. The novelty of this study is that DAE has never been utilized to crosslink PEI NF membrane for removal of dye from textile wastewater. In this study, the parameters of composition of polyetherimide dope solution having acetone as non-solvent content are investigated to obtain a potential membrane for clarifying wastewater, which is one of major problems in Indonesia. A model dye was utilized, namely Reactive Red 120 (RR120) as a synthetic wastewater. It is found that the rejection of dye is increased along with the acetone content, and also by the crosslinking duration. The crosslinking between PEI and DAE is analyzed from the physical and chemical aspects, by using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR), respectively. A good performance in nanofiltration of RR120 synthetic dye wastewater is demonstrated with 92-98% dye rejection, which is quite reasonable compared to previous researches. This PEI-DAE NF is therefore promising not just for sustainable waste management, but also for the innovation and development in the ecology and environment of Indonesia. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Acetone

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