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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Mukti, Bayu Krisna Novita, Mega Amirudin, Muhammad Singh, Sanjay Kumar Harjanto, Imadudin Bhardwaj, Priyanka Kusmantoro, Adhi Roy, Manidipa Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Electrical Engineering Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia ABES Engineering College Department of Electronics & Communication Engineering 19th KM Stone NH-09 Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

The Covid-19 pandemic has emphasized the critical role of mask-wearing in reducing virus transmission. However, declining public awareness necessitates effective monitoring solutions. This study explores the Single Shot Multibox Detector (SSD) approach, a Convolutional Neural Networks (CNN)-based object detection method, for mask detection. Specifically, we investigate the performance of the SSD model with the ResNet50 architecture as the base network. Through the analysis of a dataset comprising 1000 images of individuals wearing and not wearing masks, the SSD model with ResNet50 achieves an impressive accuracy of 98.23%, surpassing the VGG16-based model's accuracy of 93.56%. These findings underscore the superiority of the CNN-based SSD model with ResNet50 for mask detection. Moreover, they have significant implications for real-time monitoring and enforcing mask-wearing protocols, emphasizing the importance of public awareness and adherence. Leveraging advanced AI techniques, such as CNN-based object detection with SSD, strengthens public health initiatives. The development of robust and efficient mask detection systems contributes to creating a safer environment amid the ongoing Covid-19 pandemic. This research highlights the value of harnessing these advanced technologies to effectively address public health crises. By employing CNN-based SSD with ResNet50, society can enhance its ability to mitigate risks and ensure public safety. © 2023 IEEE.

关键词： Object detection

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Life cycle analysis of palm kernel shell gasification for supplying heat to an asphalt mixing plant

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Waste Disposal and Sustainable Energy 2020年第1期2卷 55-63页

作者： Sunu Herwi Pranolo Prabang Setyono Muhammad Akvis Fauzi Study Program of Chemical Engineering Faculty of EngineeringUniversitas Sebelas MaretSurakartaIndonesia Magister Study Program of Environmental Science PostgraduateUniversitas Sebelas MaretSurakartaIndonesia

The Government of the Republic of Indonesia states that the thermal energy for hot-mixed asphalt production shall be supplied by the direct combustion of fossil fuels in the form of diesel oil,natural gas,or fuel gas from coal gasification which may generate GHG *** are able to substitute the fossil fuels through gasification *** converts the biomass using limited air into gaseous fuel containing mainly CO and H_(2) that are subsequently combusted to produce heat,carbon dioxide,and *** is obvious that the CO_(2) is then absorbed by the plants for photosynthesis,main-taining a balanced closed *** study examines the level of global warming potential of this system for supplying heat based on the openLCA v1.9 *** analysis used a gate-to-gate approach to evaluate scenarios of shell gasification to produce 1 metric tonne of hot-mixed *** scope covers raw material supply and transportation,palm kernel shell gasification,and *** evaluation concludes that gasification could potentially reduce CO_(2) *** impact analysis and interpretation of the results using the openLCA database of Traci 2.1 recommend that greater CO_(2) emis-sion reduction is possible using palm kernel shell gasification,not only for supplying heat but also for electricity generation to operate all electrical equipments.

关键词： Global warming Gasification Palm kernel shell Life cycle analysis Hot-mixed asphalt

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Design and Development of a Mobile Goods Transfer Robot Using Waypoint GPS Navigation Method

Design and Development of a Mobile Goods Transfer Robot Usin...

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Wiliyanto, Danang Puji Supriyadi, Slamet Mukhtar, Agus Setyoadi, Yuris Novita, Mega Dixit, Ankur Singh, Prabhat Virmani, Rahul Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Mechanical Engineering Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia ABES Engineering College Department of Mechanical Engineering 19th KM Stone NH-09 Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

The use of automated goods transfer robots, capable of autonomously moving items from one point to another without the need for manual operation, is widely adopted in various industries. The Waypoint GPS navigation method can be employed in developing an automated goods transfer robot. This research focuses on the design and development of a robot using two Global Positioning System (GPS) coordinates for navigation and a smartphone as the user interface, equipped with ultrasonic sensors as input. The main components utilized in this robot include the Arduino Mega 2560 microcontroller, neo-7M GPS module, HC-06 Bluetooth module, SR-04 sensor, and omni-directional wheels. The position data is obtained by converting the two GPS coordinates into distance and direction values. These values are further translated into Pulse Width Modulation (PWM) signals, which are used to drive the robot's motors. To avoid collision, fuzzy logic is employed to regulate the PWM signals. The research results demonstrate that the robot can autonomously navigate from one point to another based on the provided coordinates while effectively avoiding obstacles. The findings of this study address a research gap in the application of the Waypoint GPS navigation method for goods transfer robots. The purpose of this research is to design and develop a robot that can autonomously transfer goods using the proposed method. The methodology involves the integration of GPS coordinates, smartphone interface, ultrasonic sensors, and motor control mechanisms. The results indicate successful navigation from the origin to the desired destination, following the specified coordinates, and obstacle avoidance capability. In conclusion, the developed robot utilizing the Waypoint GPS navigation method showcases promising potential for automated goods transfer applications. The ability to operate autonomously, guided by GPS coordinates, and the avoidance of obstacles enhances the efficiency and safety of goods transf

关键词： Navigation

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The Banking Industry is Undergoing a Digital Transformation as Part of Industrial 4.0 10

The Banking Industry is Undergoing a Digital Transformation ...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Sardjono, Wahyu Pranata, Dewi Sagita Ramdhana, Aditya Agung Dwi BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Mathematical & Engineering Sciences King's College London Cyber Security Studi Program Faculty of Natural Department of Informatics West Minster Strands WC2R 2LS United Kingdom University of Airlangga Master of Management Faculty of Economics and Business Surabaya60286 Indonesia

ISBN: (纸本)9798350363104

In the current day, digital transformation is imperative;both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One difficulty that has to be addressed is the desire from customers for quick and useful services. Traditional procedures need to be replaced with digital ones. Furthermore, banking organizations will have a competitive edge in the current market if they are successful in this digital transformation process. Successful transformation, however, does not happen by accident;in fact, the likelihood of completing this change is seen to be very low, necessitating rigorous planning for a company that is ready for the future. There are several components to the preparation in question, both internal and external. In this situation, the company's ability to combine and rearrange its resources quickly is essential for adapting to the ever-changing business environment. © 2024 IEEE.

关键词： Commerce

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The Effect of Vehicles Speed on the Performance of VANET Protocol

The Effect of Vehicles Speed on the Performance of VANET Pro...

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Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Osama A. Qasim Dania Mohammed Mahdi Mohammed S. Noori Rabei Raad Ali Christy Atika Sari Eko Hari Rachmawanto Department of Computer Engineering Technology Northern Technical University Mosul Iraq Department of Electrical and Electronics Engineering Uniersiti Tenaga Nasional Selangor Malaysaia Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia

At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-hoc network (VANET) differ in performance because each protocol has different variables, such as variable density, speed, and traffic scenarios. In this work, we proposed topology-based routing namely Ad hoc On Demand Distance Vector (AODV) protocol. The AODV protocol has been simulated in case of the movement of vehicles at a fixed velocity at 60km/h, and in case of randomly changing the vehicle's locations in the network. There are three parameters used to investigate the performance of the proposed AODV protocol which are packet delivery ratio, and overheads. The Simulation results show a significant decrease from 0.55 to 0.82 in the packet delivery ratio. On the other hand, the performance of the AODV protocol demonstrates effective communication for the VANETs.

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Classification Based on Texture Analysis for Synthetic Hazy Image from Mount Kelud Haze Image Density 8

Classification Based on Texture Analysis for Synthetic Hazy ...

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8th International Conference on Electrical, Electronics and Information engineering, ICEEIE 2023

作者： Nugroho, Fresy Basid, Puspa Miladin Safitri A. Arif, Yunifa Miftachul Diah, Norizan Mat Bahtiar, Firma Sahrul Nurhayati, Hani Kurniawan, Fachrul Priandani, Nurizal Dwi Dermawan, Dodik Arwin Universitas Islam Negeri Maulana Malik Ibrahim Informatics Engineering Faculty of Science and Technology Malang Indonesia School of Computing Sciences College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam Malaysia Library and Information Science Universitas Islam Negeri Maulana Malik Ibrahim Faculty of Science and Technology Malang Indonesia Manajemen Informatika Program Vokasi Universitas Negeri Surabaya Surabaya Indonesia

ISBN: (纸本)9798350340501

This paper classifies the simulations of homogeneous synthetic images, heterogeneous synthetic hazy images, and original hazy images taken from CCTV (Close Circuit Television) of Mt. Kelud crater using the GLCM (Gray Level Co-Occurrence Matrix) method. The average feature values obtained using the GLCM (Gray Level Co-Occurrence Matrix) method are used to compare the similarity of gray feature values of the three and then classify thin, medium, and thick images. The results for classifying thin haze, medium haze, and thick haze on the homogeneous synthetic hazy image test data obtained an accuracy value of 50%, a precision value of 46%, and a sensitivity value of 65%. As for the classification of thin, medium, and thick fog on heterogeneous synthetic hazy images, test data obtained an accuracy value of 42%, a precision value of 32%, and a sensitivity value of 48%. © 2023 IEEE.

关键词： Textures

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A Low Complexity ML-Based Methods for Malware Classification

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Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa Salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Understanding Motorcycle Rider Behavior in Indonesia Using Naturalistic Driving study

SSRN

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SSRN 2024年

作者： Halim, Winda Puspasari, Maya Arlini Prasetyo, Ridwan Aji Budi Ardiansyah, Yusuf Huda, Listiani Nurul Lahay, Idham Halid Lady, Lovely Didin, Fatin Saffanah Mahachandra, Manik Iridiastadi, Hardianto Department of Industrial Engineering and Management Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Industrial Engineering Program Study Faculty of Engineering Universitas Kristen Maranatha Bandung Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Indonesia Indonesia Departemet of Psychology Faculty of Social and Political Sciences Brawijaya University Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Sumatera Utara Indonesia Department of Industrial Engineering Faculty of Engineering Universitas Negeri Gorontalo Indonesia Industrial Engineering Departement University of Sultan Ageng Tirtayasa Indonesia Departement of Industrial Engineering Faculty of Industrial Technology Institut Teknologi Sumatera South Lampung Indonesia Industrial Engineering Department Engineering Faculty Diponegoro University Central Java Semarang Indonesia

In Indonesia, motorcycle is the most popular form of transportation because of their convenience and economical. Motorcycles dominate more than 85% of vehicles on the road. Ironically, the number of motorcycle-related accidents rise and now account for about 73% of all traffic accidents. Aim of this research is to understand motorcyclist behavior, other road user, and related traffic conditions. The Naturalistic Driving study (NDS) method is used to gather data. A camera was mounted to participant’s motorcycle to capture their driving behaviors and traffic condition. The participants of this study were drawn from 6 cities across 3 major islands in Indonesia. There were 79 participants with a total journey distance approximately 1036 km and a journey duration nearly 40 hours. The video recordings were then observed by observers in each city to determine the safety critical events (SCE). There was no significant difference in the number of SCEs that occur in each city, but there was a significant difference when it comes to the causes of SCEs. This research found that the largest number of violations (30-80%) occur due to factors related to other road user, such as near crash with other road users when overtaking vehicles in front of them, other road users from the opposite direction driving in the wrong lane/side or lane used by the driver, or near crash with other road users who suddenly change lanes in front of them. In this research, it was also found that the number of SCEs that occurred was not affected by the distance and driving duration. This study supports previous research that the main cause of violations is human error. However, the occurrence of SCE is not only caused by the driver himself but through this research it is found that other road users are a critical factor. © 2024, The Authors. All rights reserved.

关键词： Motorcycles

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Asynchronous Data Communication Architecture on Real-Time Face Recognition for Hybrid Laboratory System

Asynchronous Data Communication Architecture on Real-Time Fa...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Nina Lestari Trisna Purnama Slamet Risnanto Budi Fitriadi Ach Maulana Habibi Yusuf Ary Setijadi Prihatmanto Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Electrical Engineering Department Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Universitas Komputer Indonesia Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

The Internet of Things (IoT) and Artificial Intelligence (AI) have reshaped educational technology, increasing the chances of developing more effective and engaging learning environments. This study proposes an architecture for asynchronous data communication with real-time face recognition, a virtual and remote labs confluence. The architecture uses IoT hardware and software to comprise critical components such as IoT cameras, message brokers, FTP servers, and AI processing servers. The aim is to optimize resource usage and maximize response time efficiency. The architecture employs message queuing to manage high volumes of face image data, facilitating immediate verification and rapid access. Our findings demonstrate that the system can achieve face recognition with 91.7% accuracy and an average system communication latency of 2.631 seconds, effectively leveraging asynchronous communication to optimize resource usage and computational efficiency. The research comprehensively measures the data communication metrics and face recognition metrics. It also explains how asynchronous data communication can be strategically deployed in a hybrid lab environment to enhance educational and operational efficacy.

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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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