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International Conference on Application of Information and Communication Technologies (AICT)

作者： Rabei Raad Ali Wisam Subhi Al-Dayyeni Christy Atika Sari Eko Hari Rachmawanto Candra Irawan Omar M. Jihad Department of Computer Engineering Technology Northern Technical University Mosul Iraq School of Information Technologies and Engineering ADA University Baku Azerbaijan Study Program in Informatics Engineering Faculty of Computer Science University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems Faculty of Computer Science University of Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350387537

ISBN: (纸本)9798350387544

In today’s complex global environments, it is highly challenging to achieve effective healthcare management. The critical challenges faced by healthcare management are being met by the revolution of m-health where mobile cloud computing plays a major role. The taxonomy of mobile computing comprises operational aspects, end-user issues, and service quality and mobility management. The use of smartphone technologies and applications has become a highly significant approach to improving healthcare management. Mobile health services such as mobile pathology, mobile neurosurgery, cancer treatment, and behavioral/psychological disorders are gaining significance where smartphone applications are being used. Portability, flexibility, and convenience are major characteristics of mobile computing that have helped patients and doctors to develop better relationships through coordination and communication. The relationship between smartphone technologies and applications and healthcare management can be understood in several broad aspects. This article aims to analyze the current and future implications of these technologies on healthcare and disease management systems.

关键词： Pathology Cloud computing Taxonomy Cancer treatment Medical services Benchmark testing Neurosurgery Information and communication technology Mobile computing Diseases

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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

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4th International Conference on Electronics, Biomedical engineering, and Health Informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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Edible coating from VCO, iota-carrageenan and alginate blends for pindang fish preservation

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Green Materials 2023年第1期13卷 3-16页

作者： Iswahyuni, Hana Suyatma, Nugraha Edhi Wulandari, Nur Irianto, Hari Eko Dewi, Fera Roswita Nurhayati Sinurat, Ellya Nurbayasari, Rodiah Giyatmi Fransiska, Dina Analyst Ministry for Marine Affairs and Fisheries IPB University Bogor Indonesia Master of Food Technology Study Program Graduate School IPB University Bogor Indonesia Department of Food Science and Technology Faculty of Agricultural Engineering and Technology IPB University Bogor Indonesia Research Center for Marine and Land Bioindustry National Research and Innovation Agency of the Republic of Indonesia Lombok Indonesia Food Technology Study Program Faculty of Food Technology and Health Sahid University Jakarta Indonesia Research Center for Applied Microbiology National Research and Innovation Agency of the Republic of Indonesia Cibinong Indonesia

This study aims to develop an edible coating based on virgin coconut oil (VCO) nanoemulsion, iota-carrageenan and alginate to prolong the shelf life of pindang (mildly salted cooked) fish products. The research involved three stages: material preparation, characterization and determination of factors and responses for experimental design;parameter optimization to achieve optimal conditions;and application and analysis of pre- and post-coating characteristics of pindang fish. The parameter ranges were 0.5–1.5% for alginate concentration, 0.5–1.5% for iota-carrageenan concentration and 0.5–1.0% for VCO nanoemulsion concentration. The result of this study was an optimized food coating solution that was clear and bright white in color. Pindang fish coated with this layer showed improved quality in terms of water content (48.46%), weight loss (0.39%), pH (5.84), total volatile base (47.01%), salt content (2.9%), appearance (7), texture (7) and slime (7). At the same time, the total bacterial count remained unchanged (8 log colony-forming units (CFU)/g), the mold count remained unchanged (5 log CFU/g) and the aroma and taste received a score of 6. Thus, this study successfully produced an optimized edible coating that can enhance the quality and extend the shelf life of pindang fish, making it suitable for broader market distribution. © 2023 ICE Publishing. All rights reserved.

关键词： Fish

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LoRa Network Design for Monitoring Landslides on 150 KV Delivery Tower

LoRa Network Design for Monitoring Landslides on 150 KV Deli...

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International Conference on Smart Computing & Communications (ICSCC)

作者： I Wayan Dikse Pancane I Putu Gelgel Astika Putra I Wayan Gede Suarjana Agus Supranartha Electrical Engineering Study Program Universitas Pendidikan Nasional Denpasar Indonesia Department of Public Health Faculty of Sport Science and Public Health Universitas Negeri Manado Sulawesi Indonesia Electro Enginering Elektrical Engineering Program Study Politechnic Negeri Bali Badung Indonesia

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

The objective of this research is to design and develop an integrated landslide early detection system at Tower Number Eight, 150 kV Gianyar. The research is expected to result in the construction of a communication system based on LoRa technology that will serve to reduce the potential damage from landslides. In order to achieve this, several parameters must be considered as benchmarks. These include RSSI, SNR, BER and PDR. The device operates by monitoring changes in position, soil moisture and rainfall, and then transmitting the data via LoRa technology. At the sink, the data is recorded and monitored for RSSI, SNR, PDR and BER values. In the test, the source 1 node, situated 300 metres away, exhibited an RSSI value of −100 to −109 dBm and an SNR value of 6.75 to −6.7 in both sunny and rainy weather, with a PDR value of 100%. The source 2 node, situated 600 metres away, exhibited an RSSI value of −97 to −109 dBm and an SNR value of 8.5 to −11.75 dB, with a PDR value of 70 to 100%. It should be noted that the number of bits in the sensor data sent is always complete. This is evidenced by the bit error ratio (BER) value, which is always 0 on both source nodes.

关键词： Rain Electricity Poles and towers Soil moisture LoRa Terrain factors Reliability Monitoring Signal to noise ratio Meteorology

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Biosorption of chromium by live and dead cells of Bacillus nitratireducens isolated from textile effluent

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Chemosphere 2024年 359卷 142389页

作者： Imron, Muhammad Fauzul Setiawan, Wahyu Putranto, Trisnadi Widyaleksono Catur Abdullah, Siti Rozaimah Sheikh Kurniawan, Setyo Budi Study Program of Environmental Engineering Department of Biology Faculty of Science and Technology Universitas Airlangga Campus C UNAIR Jalan Mulyorejo Surabaya60115 Indonesia Department of Water Management Faculty of Civil Engineering and Geosciences Delft University of Technology Stevinweg 1 CN Delft2628 Netherlands Study Program of Environmental Science Postgraduate Program Sriwijaya University Palembang30139 Indonesia Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Bangi Selangor 43600 Malaysia

Bacillus nitratireducens was isolated from textile effluent and showed high tolerance to chromium (Cr), reaching up to a 1000 mg/L MIC value. This research was aimed at utilizing biosorbents from live and dead cells of B. nitratireducens to remove Cr from an aqueous solution. A batch biosorption test was performed, and mechanisms analysis was approached by an adsorption-desorption test, SEM-EDS, and FTIR analysis. Cr removal by dead cells in 25, 50, and 100 mg/L of Cr were 58.99 ± 0.7%, 69.8 ± 0.2%, and 82.87 ± 0.11%, respectively, while that by live cells was 73.08 ± 1.9%, 80.27 ± 6.33%, and 86.17 ± 1.93%, respectively. Live cells showed significantly higher Cr removal and adsorption capacities as compared to dead cells. In all concentrations, absorption contributed more than adsorption to the Cr removal by both live and dead cells. Absorption of Cr was subjected to occur due to passive mechanisms in dead cells while involving some active mechanisms in live cells. SEM-EDS confirmed the detection of Cr on the cell surface, while FTIR revealed the shifting of some peaks after the biosorption test, suggesting interactions between Cr and functional groups. Further TEM analysis is suggested to be conducted as a future approach to reveal the inner structure of cells and confirm the involvement of absorption mechanisms. © 2024 Elsevier Ltd

关键词： Heavy metals

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Analysis Geomorphic Flood Index in Determining Flood-Prone Areas in East Kalimantan Province, Indonesia

Analysis Geomorphic Flood Index in Determining Flood-Prone A...

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2024 Annual Conference, ASPRS 2024

作者： Virtriana, Riantini Amalia, Annisa Fitri Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Harto, Agung Budi Deliar, Albertus Geospatial Information Science and Technology Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung40132 Indonesia Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Universitas Pendidikan Indonesia Bandung40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung40132 Indonesia

In 2022, there are 1,524 flood events out of a total of 3,531 disasters occurring in Indonesia. East Kalimantan Province ranked 20th among the 35 provinces in Indonesia with 28 flood occurrences in 2022, resulting in two fatalities. This highlights the urgent need for addressing flood hazard to prevent future casualties. There are some methods that can be used to determine the flood hazard in a region. In this research aims to identify flood-prone areas in East Kalimantan Province and evaluate the effectiveness of different mapping methods. The methodology that compares are the Pairwise Comparison method and Geomorphic Flood Index (GFI). The study's results provide flood-prone area maps of East Kalimantan Province using both methods, recommend the more efficient method for flood-prone area identification, and offer mitigation strategies based on the findings. This research is intended to serve as a reference for selecting the best method for identifying flood-prone areas and for informing policy decisions to mitigate flood impacts in East Kalimantan Province. © Author(s) 2025.

关键词： Hazards

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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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Comparison of potential energy of solar radiation in rooftop modeling using different building levels of detail

Comparison of potential energy of solar radiation in rooftop...

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2023 Annual Conference, ASPRS 2023

作者： Ihsan, K.T.N. Sakti, A.D. Higuchi, A. Takenaka, H. Suwardhi, D. Wikantika, K. Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung Indonesia Graduate School of Science and Engineering Chiba University Chiba Japan Remote Sensing and Geographic Information Science Research Group Faculty of Earth Sciences and Technology Institut Teknologi Bandung Bandung40132 Indonesia Center for Remote Sensing Institut Teknologi Bandung Bandung40132 Indonesia Center for Environmental Remote Sensing Chiba University Chiba263-8522 Japan

The potential for future energy crises is a problem the world is currently facing. Many countries are switching from fossil to renewable energy to prevent an energy crisis. One of the most developed renewable energy today is solar energy. Easy installation makes solar energy installation not only on a large scale but also on a home scale. Urban areas will be very suitable for building solar photovoltaic (PV) roofs due to minimal open areas. In installing rooftop solar PV, sound planning is needed to predict the energy potential that can be provided by solar energy on the rooftop of a building. Spatial modeling can be done to determine the energy potential and suitable location for rooftop solar PV installation. In building rooftop solar PV modeling, the level of detail of the building will affect the results of the model. The rooftop's shape and the building's height will affect the amount of solar radiation going into the building. However, the higher the level of detail of the building, the higher the cost and processing time will be. This study will review the differences in modeling the potential of rooftop solar PV using different levels of detail. This research will integrate solar radiation data from remote sensing to determine the energy potential of solar radiation and digital surface model data from photogrammetry to create a level of detail for buildings. Integration of solar radiation data and the level of detail of the building will use hillshade analysis. Hillshade analysis can review the shadow effect on the rooftop of a building which will be directly related to the potential of solar energy on the rooftop of the building. This study determines the energy potential on the rooftop of the building with different levels of detail, namely 0, 1, and actual shape, to determine the difference in energy potential in the three scenarios. Hopefully, this research will determine the best level of detail for modeling rooftop solar PV. The best model that can sho

关键词： Remote sensing

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation Data models Classification algorithms Decision trees Data mining Information technology Diseases

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