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Combustion Profile of Bio-pellet Produced from Sawdust Using Wet Torrefaction Method with Various Concentrations of Acetic Acid 4

Combustion Profile of Bio-pellet Produced from Sawdust Using...

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4th International Symposium on Advances and Innovation in Mechanical engineering, ISAIME 2023

作者： Pertiwi, Indah Ayu Muhammad Abubakar Setiawan, Adi Iskandar, Rizky Magister Program in Renewable Energy Engineering Faculty of Engineering Universitas Malikusssaleh Jalan Batam Bukit Indah Lhokseumawe24352 Indonesia Chemical Engineering Department Faculty of Engineering Universitas Malikussaleh Kampus Bukit Indah Muara Satu Lhokseumawe24352 Indonesia Mechanical Engineering Vocational Education Study Program Faculty of Teaching and Educational Science Universitas Malikussaleh Cot Teungku Nie Reuleut Muara Batu Aceh Utara24355 Indonesia Mechanical Engineering Department Faculty of Engineering Universitas Malikusssaleh Jalan Batam Bukit Indah Lhokseumawe24352 Indonesia

Sawdust is one of the industrial wastes which naturally contains low energy density. An effective method is needed to utilize this biomass as a solid fuel product. This work aimed to investigate the physical and combustion properties of bio-pellets produced from sawdust under the wet torrefaction method. To prepare sawdust bio-pellet a number of steps were carried out including the wet torrefaction process, dough preparation, pelletizing, and drying. Wet torrefaction was performed by hydrothermally treating the sample in an autoclave at a temperature of 130°C and pressure of 2 atm (g) for 80 minutes. For the hydrothermal process, the used acetic acid solution was varied with variations of 1.3 M, 1.8 M, and 2.3 M. Properties of the product were analyzed under proximate and bomb calorimetry analyses. To evaluate the combustion properties a purposely built test apparatus was developed equipped with a data logger system. Based on the results it can be observed that increases in torrefaction temperature and acetic acid concentration resulted in an increase in the calorific value as well as decreases in the ash content. The highest calorific value was 4745 kcal/kg obtained from sawdust torrefied in acetic acid with a concentration of 2.3 M at a temperature of 130?. This sample also exhibits the lowest ash content which is only 1.97%. The combustion test disclosed a maximum combustion temperature of 589? with a burning rate of 0.711 g/min. Overall, the wet torrefaction applied in this investigation was beneficially enhanced the properties of bio-pellet products. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Sawdust

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Effect of High-Flow Nasal Cannula on Capnogram Waveform for studying Non-Invasive Human Ventilation 2

Effect of High-Flow Nasal Cannula on Capnogram Waveform for ...

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2nd IEEE National Biomedical engineering Conference, NBEC 2023

作者： Tirta Nindhia, Tjokorda Gde Aqila Mohammed, Nursyasa Jamaludin, Julia Jais Devandran, Pagupathi Angel Bhaswara, Nabiel Rafa Hutajulu, Thalitakum Malarvili, M.B. Udayana University Jimbaran Study Program of Mechanical Engineering Engineering Faculty Bali Indonesia Universiti Teknologi Malaysia School of Biomedical and Health Science Engineering Johor Malaysia

ISBN: (纸本)9798350338546

This study is conducted to compare three different cannulas;all purpose nasal cannula with 2 prongs, nasal pressure cannula with 2 prongs and single port nasal cannula which are commonly used for capnography device. These cannulas or sometimes called as nasal prong is connected to the device via nose of subjects studied. This procedure is a part of respiratory study to monitor lungs condition and breathing pattern. This study involves 47 subject where the exhaled breath was recorded to make comparison and choose the most suitable and effective for capnography waveform analysis. Utilizing Statistical Package for the Social Sciences (SPSS) to find the normality of all the nasal cannula data based on capnogram waveform. The result from the analysis shows that the frequency distribution for type 1 nasal cannula which is also known as all-purpose nasal cannula had the feature values closer to the standard value. Our study proofs that all purpose nasal cannula sampling is the most suitable to capture exhaled breath for monitoring respiratory conditions. © 2023 IEEE.

关键词： capnography CO2 monitoring, feature extraction nasal cannula

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Designing knowledge sharing systems to support integrated eco-city planning and management 5

Designing knowledge sharing systems to support integrated ec...

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5th International Seminar on Sustainable Urban Development, ISoSUD 2020

作者： Supriana, C.E. Informatics Engineering Study Program Faculty of Engineering Pasundan University Bandung Indonesia

The local government of a city as an organization depends on decision makers in government management to support the vision and mission of the city to achieve eco-city goals based on data and information from several knowledge domains. Knowledge management is seen as an increasingly important scientific discipline that encourages the creation, sharing and utilization of knowledge in an organization. Knowledge management is also related to the concept of intellectual capital, the most valuable organizational resource. Knowledge sharing systems are designed to help decision makers and stakeholders share their knowledge. Most knowledge management systems in organizations are designed to share the explicit knowledge of individuals, organizations and finally distributed to the community. This research is the approach in the development model that can be used in the governance to achieve eco-city goals. Complex knowledge about eco-cities requires policies that are based on current knowledge and can be implemented immediately with a thorough understanding of all aspects. The results of this study are understanding the problem of knowledge sharing as a valuable organizational asset, designing a knowledge sharing systems model, and improving systems to improve the quality of knowledge. © Published under licence by IOP Publishing Ltd.

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Convolutional Neural Network for Cataract Clasification Using Primary Dataset

Convolutional Neural Network for Cataract Clasification Usin...

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International Conference on Business and Industrial Research (ICBIR)

作者： I Gede Totok Suryawan I Wayan Murmayasa Adi Putra Informatics Engineering Study Program Faculty of Technology and Informatics Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

Cataracts are the main factor causing blindness in Indonesia. Traditional diagnostic methods involving clinical examination by an ophthalmologist using a slit-lamp and visual tests have many challenges such as limited resources, time, and medical expertise may not be available in all locations, especially in less developed areas. Utilizing medical image technology is a wise choice because it allows early detection and monitoring of the development of this cataract disease Technology is needed to identify medical images that have valuable information so that early detection or monitoring of cataract development can be carried out. CNN as a part of deep learning has the ability to perform automatic feature extraction so that it can identify eye images. A CNN model for recognizing cataracts in eye images taken directly from Bhayangkara Hospital in Denpasar Bali has been developed in this research. The model developed is equipped with a dropout layer technique to prevent overfitting. The test results show that the CNN developed in this research produces very good performance with an average accuracy level of 92% on public dataset images, and 94% on primary dataset images. Tested using the primary dataset and public dataset, this CNN model shows very good performance because it can correctly identify an average of 94% of eye images in the primary dataset, and 92% of eye images in the public dataset..

关键词： Cataracts Training Visualization Image recognition Accuracy Convolutional neural networks Medical diagnostic imaging Monitoring Testing Overfitting

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Building a Simple COVID-19 Knowledge Graph in Bahasa Indonesia: A Preliminary study 3

Building a Simple COVID-19 Knowledge Graph in Bahasa Indones...

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3rd IEEE International Biomedical Instrumentation and Technology Conference, IBITeC 2023

作者： Muharram, Arief Purnama Taufikulhakim, Farhan Hilmi Purwarianti, Ayu Universitas Indonesia Faculty of Medicine Jakarta Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Master Program of Informatics Bandung Indonesia

ISBN: (纸本)9798350302424

COVID-19 is an acute respiratory disease that has become a pandemic worldwide. Many studies have been conducted to enhance our understanding of COVID-19. However, the abundance of information obtained from these studies has resulted in information overload. In this study, we purposed a simple COVID-19 Knowledge Graph in Bahasa Indonesia as a way to reconstruct knowledge to combat this information overload. We used Bahasa Indonesia in our study to explore its potential for constructing a Knowledge Graph (KG). The construction of our KG involved manual curation of medical literatures and annotation of entities and relationships by the domain experts. The KG was implemented using Neo4J version 5. We successfully demonstrated our COVID-19 KG, which consists of 240 nodes and 276 relationships with 15 and 14 node and relationship labels, respectively. Accessing the information within the KG is made effortless through the use of Cypher queries in Neo4J. Further research is still needed to develop the KG into a larger and better one. However, our COVID-19 KG can serve as a basis for further development. © 2023 IEEE.

关键词： COVID-19

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Hybrid Encryption Based on Fernet and Rivest Shamir Adleman (RSA)

Hybrid Encryption Based on Fernet and Rivest Shamir Adleman ...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Hisbullah, Muhammad Dafi Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Umam, Chaerul Isinkaye, Folasade University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria

ISBN: (纸本)9798350339215

RSA is an asymmetric encryption algorithm that uses two different keys, a public key to encrypt the plain text and a private key to decrypt the cipher text. Fernet is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. This study uses Fernet and RSA which is the combination of symmetric and asymmetric encryption called hybrid encryption. In addition, the cipher text will be hidden inside an image using Stepic. Hybrid Encryption uses asymmetric encryption to encrypt the symmetric encryption secret key, it will secure the symmetric encryption. The result of this study is the lowest error that we got as the MSE is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche (AVA) with 79.00% and 42.34% in order. Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 46.48% for UACI and 99.86% for the NPCR. © 2023 IEEE.

关键词： Signal to noise ratio

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Developing Organizational Resilience Model to Sustain Business Performance

Developing Organizational Resilience Model to Sustain Busine...

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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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Performance Evaluation of Coverage Prediction in 4G Networks Using Machine Learning Classification Algorithm 10

Performance Evaluation of Coverage Prediction in 4G Networks...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Yuliana, Hajiar Iskandar Hendrawan Ridwan, Azwar Mudzakkir Charisma, Atik Somantri, Nivika Tiffany Universitas Jenderal Achmad Yani Faculty of Engineering Department of Electrical Engineering Indonesia Institut Teknologi Bandung Doctoral Program of School of Elecrtical Engineering and Informatics Indonesia Bandung Indonesia UIN Sunan Gunung Djati Bandung Department of Electrical Engineering Indonesia

ISBN: (纸本)9798350377057

Network coverage prediction is an important aspect of 4G network planning and optimization. In this study, we conducted a comprehensive analysis of the performance of various machine learning algorithms in predicting 4G network coverage. The data collected includes information on location, signal intensity, topography, and other important variables. Data pre-processing is performed to clean, normalize, and select relevant features. Next, we compared the performance of several machine learning algorithms, including Logistic Regression, KNN, Naïve Bayes, Decision Tree, SVM, XGBoost, AdaBoost, and Bayesian Network Classifier. The model training process is performed using subsets of training, validation, and testing data, with evaluation performed using various evaluation metrics such as accuracy, precision, recall, F1-score, RMSE, MAE, and R-squared. The experimental results show that Random Forest stands out with excellent performance, while Naïve Bayes tends to produce lower performance. The conclusion of this study provides valuable insights into the potential applications of machine learning algorithms in predicting 4G network coverage with accuracy and reliability. © 2024 IEEE.

关键词： Adversarial machine learning

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Initial Exploration and Understanding of Parameters for Successful Enterprise Architecture Implementation 11

Initial Exploration and Understanding of Parameters for Succ...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Khairina, Dyna Marisa Purwanto, Purwanto Nugraheni, Dinar Mutiara Kusumo School of Postgraduate Studies Universitas Diponegoro Program in Information Systems Semarang Indonesia Universitas Diponegoro Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389654

This study provides an initial exploration and further understanding of the factors that are parameters in evaluating the success of Enterprise Architecture (EA) implementation. An evaluation process is needed to ensure that the EA project implementation provides effectiveness, efficiency, and feasibility of the EA information system as well as assessing previous project experience to avoid future EA project risks. The research aims to present a Systematic Literature Review based on the stages of identification, screening, eligibility, and inclusion so that 14 main articles are selected for review with strong actual relevance. The study results provide insights and references that can be used to further explore key factors in evaluating the success of EA implementation in the future. It was found that there were ten factors that most influenced the evaluation of the success of EA implementation and it was concluded that two potential factors were the most influential and required further exploration in evaluating the success of EA implementation which could be applied in various sectors/dimensions. This study contributes as an initial reference for overcoming problems in investigating and exploring the factors that influence the success of EA implementation as an effort to assess the success of achieving future organizational goals. © 2024 IEEE.

关键词： Enterprise Architecture Parameters Success Factors Systematic Literature Review

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IoT: Monitoring Temperature, Water pH, and Automatic Water Drainage Systems for Gurami Cultivation

IoT: Monitoring Temperature, Water pH, and Automatic Water D...

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2023 International Conference on Networking, Electrical engineering, Computer Science, and Technology, IConNECT 2023

作者： Sulistiani, Heni Saputra, Wijaya Darwis, Dedi Isnain, Auliya Rahman Rimanda Putra, Ardy Khairunisa, Yosi Universitas Teknokrat Indonesia Study Program of Accounting Information System Lampung Indonesia Universitas Teknokrat Indonesia Study Program of Computer Engineering Lampung Indonesia Universitas Teknokrat Indonesia Study Program of Informatics Lampung Indonesia Regional Research and Development Agency Lampung Indonesia

ISBN: (纸本)9798350331172

Gurami is a native fish from Indonesian waters that is much-loved by Indonesian people for daily food consumption. The gurami inhabits still waters such as swamps, lakes, and ponds. Besides that, carp cannot live in a water content that is too alkaline or acidic, the oxygen content in the water must be stable. Water quality is a very important factor and can affect the survival of cultivated fish. Several parameters must be considered in improving the development of carp, one of which is the temperature and pH of the water and automatic drainage of water. In this paper, we conduct IoT-based research that focuses on controlling water temperature and pH and automatically draining pool water. Water temperature and pH control such as a pH sensor temperature sensor and a water turbidity sensor will later be connected to the ESP 32 microcontroller which already has a wi-fi module. A system that is linked to electrical power and the internet then the sensor will read the water quality including the pH temperature value and water turbidity from inside the fish pond, after getting the data, the data will go to ESP 32. This research can help gurami cultivating farmers to make it easy to control the pH temperature and perform automatic pool water draining. The results of sensor testing with actual data are pretty accurate with the average error value of the ds18b20 sensor being 0.05% while the value of the pH sensor itself is 0.07%. © 2023 IEEE.

关键词： Temperature sensors

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