2 10 27 https://repository.horizon.ac.id/files/original/7d62edd5e974112be779003c4bbcd6a2.pdf a4b9aea63d5581b3153ad75870811e8f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A high accuracy of deep learning based CNN architecture: classic, VGGNet, and RestNet50 for Covid-19 image classification Subject The topic of the resource Classic convolutional neural network Convolutional neural network Covid-19 RestNet-50 VGGNet Description An account of the resource This research paper provides a detailed examination of different convolutional neural network (CNN) structures used in Covid-19 image classification tasks. The study thoroughly investigates the performance of classic CNN, visual geometry group (VGG), and ResNet-50 architectures across a variety of datasets. The analysis focuses on evaluating the efficacy of each architecture by considering metrics such as accuracy, precision, recall, and F1-Score. The experimental results reveal that the ResNet-50 architecture achieves the highest performance with an accuracy rate of 96.63%, outperforming both VGG and classic CNN models. This finding emphasizes the importance of architectural choices and hyperparameter selection in achieving optimal performance in image classification tasks. The combination of the ResNet-50 architecture with the Adam optimizer demonstrates its effectiveness in improving classification accuracy. These findings contribute to the field of deep learning by providing valuable insights into the performance analysis of CNN architectures and highlighting the significance of selecting appropriate hyperparameters for optimal model performance. The selection of VGG and ResNet-50 architectures was based on their strong feature extraction capabilities, proven state-of-the-art performance, and their suitability for transfer learning. VGG and ResNet-50 also have widely available pre-trained models, facilitating their usage and experimentation. Creator An entity primarily responsible for making the resource Ibnu Utomo Wahyu Mulyono1, Eko Hari Rachmawanto1, Christy Atika Sari1, Md Kamruzzaman Sarker2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jul 12, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/813a1f45f8649eca490473a5ac58f0bb.pdf 2b19baa5bed9e998aecc32a43ed26655 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Navigating the digital shift: a service blueprint for coopetition technology-enabled networks Subject The topic of the resource Coopetition Networks SD logic Service blueprint Service science Description An account of the resource This study addresses the gap in applying traditional service blueprint methodologies to technology-enabled coopetition networks characterized by simultaneous collaboration and competition among actors. Leveraging service science insights, it proposes an enhanced service blueprint framework designed for the complexities of digital coopetition. This framework introduces the cyber. Frontstage lane, physical backstage lane, and support stage lane aim to provide a holistic view of interactions, value co-creation processes, and resource allocations. Empirical validation within the Portuguese stone sector-a key player in the national economy-demonstrates the framework’s effectiveness in identifying network dysfunctions and its ease of use by industry professionals. Feedback confirms its relevance in capturing today’s coopetition environments’ multifaceted engagements and digital nuances. The study emphasizes adapting service blueprint methodology to better manage and innovate service processes in digital ecosystems. Future research should extend this framework’s application across various sectors and explore the integration of emerging technologies to optimize service delivery and value co-creation. Creator An entity primarily responsible for making the resource Agostinho da Silva1,2, Antonio J. Marques Cardoso1 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jul 12, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/68d1db48a28d2a9d616883ac89272b78.pdf 5b7aaa29dc6b33e48103b6c2a3cd87d4 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A highly effective and simplified DPWM algorithm for NPC inverters for high power factor load applications Subject The topic of the resource High power factor Neutral point clamped Pulse width modulation Three phase neutral point clamped Zero-sequence function Description An account of the resource In recent years, high-power three-level neutral point clamped (NPC) inverters have significantly increased, particularly in the renewable energy sector and industries. These inverters are crucial in applications such as offshore wind farms and high-power motor drives, where reducing switching losses and improving the overall longevity, efficiency, and reliability of inverter systems are key. While conventional space vector pulse width modulation (SVPWM) has been used to reduce switching losses, it also increases the computational burden in the αβ coordinates. Our study introduces an effective and highly efficient carrier-based discontinuous pulse width modulation (DPWM) method specifically designed for high power factor loads to address this challenge. This approach significantly reduces computational execution time by adding the zero-sequence function into the fundamental signals. The efficiency of our new method is evident in the results: the proposed DPWM has successfully reduced switching losses, leading to a substantial enhancement of system efficiency. Our space vector analysis and simulation results, achieved using MATLAB and PLECS software, further validate the efficiency of our approach. Additionally, experimental results with a small-scale three-phase NPC inverter were conducted to validate the effectiveness and efficiency of the proposed DPWM. Creator An entity primarily responsible for making the resource Duc-Hung Nguyen1,2, Minh-Duc Pham1,2, Nho Van Nguyen1,2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jul 12, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT High power factor Neutral point clamped Pulse width modulation Three phase neutral point clamped Zero-sequence function https://repository.horizon.ac.id/files/original/05c096aff02a1197b3af5b9a07bf84d4.pdf 64e3094642f7b6db325647c9bfb998c5 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A contrived dataset of substation automation for cybersecurity research in the smart grid networks based on IEC61850 Subject The topic of the resource CyberGrid Cybersecurity research Datasets Deep learning IEC61850 Smart grid Substation automation system Description An account of the resource Relevant datasets that depict and/or emulate the smart grid networks (SGN) are key to developing cybersecurity models that can effectively provide security for mission-critical infrastructure. The difficulty in obtaining relevant SGN real-life datasets presents a considerable challenge for researchers in the field and, the existing datasets lack representation of the IEC61850 protocol for modelling substation automation processes for cybersecurity solutions. This paper presents a dataset simulated from a fully virtual testbed, intended to provide researchers with the necessary datasets for research and experiments that require massive amounts of data close to the real-world scenario. Experimentally, the dataset was used to develop an intrusion detection model based on gated recurrent unit (GRU), deep belief network (DBN), long-short term memory (LSTM), and evaluated using accuracy, precision, recall, F1-score, detection rate, false alarm rate (FAR), missed alarm rate (MAR), mean squared error (MSE), mean absolute error (MAE), and loss. Results show that the standalone deep learning (DL) algorithms outperformed the hybridized ones and are more suitable for developing models for securing substation automation systems that support generic object-oriented substation events (GOOSE), and manufacturing message specification (MMS) and run on IEC61850, distributed network protocol version 3 (DNP3), and Modbus-transmission control protocol (ModbusTCP). Creator An entity primarily responsible for making the resource John Edet Efiong1, Jide Ebenezer Taiwo Akinsola2, Bodunde Odunola Akinyemi3, Emmanuel Ajayi Olajubu4, Ganiyu Adesola Aderounmu1 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/fcac93a3c41141d9a0e6fb344678c031.pdf 5c582d0a68652a872627b9131c9c8185 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Class-G series audio power amplifier for subwoofer Subject The topic of the resource Audio power amplifier Class-AB Class-G Power efficiency Subwoofer Description An account of the resource An audio power amplifier is an electronic device used to amplify a small signal source power at the input into a large signal power at the output that is speaker. In general, audio power amplifiers use class-AB amplifiers. In the process of amplifying the signal power, there will be power losses in the amplifiers which results in relatively lower amplifier power efficiency because there is a difference between the supply and output voltage levels. In this paper a class-G series audio power amplifier for subwoofers is designed to minimize these power losses and increase the power efficiency of the amplifier. The designed amplifier voltage supply is 40 V with a maximum output power of 80 W at an 8 Ω load. The amplifier has frequency response from 20–200 Hz and gain twice. Realization of the power amplifier and measurements were carried out using the circuit maker simulator, and the measurement results of the class-G power amplifier were compared with the class-AB power amplifier. The measurement results show that both power amplifiers meet the design specifications. The proposed class-G amplifier has 0.14% larger total harmonic distortion (THD) but has 10.4% greater power efficiency advantages over the class-AB amplifier. Creator An entity primarily responsible for making the resource Class-G series audio power amplifier for subwoofer Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Audio power amplifier Class-AB Class-G Power efficiency Subwoofer https://repository.horizon.ac.id/files/original/12e843bd6352da6e174873efd9ce1717.pdf 348f168853c5a48ffd6e7ab30afb4d4d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Observer-based single-phase robustness sliding mode controller for the pitch control of a variable speed wind turbine Subject The topic of the resource Output feedback Pitch control Sliding mode control Variable speed wind turbine Without reaching phase Description An account of the resource In this paper, a new observer-based single-phase robustness sliding mode controller (SPRSMC) is proposed for the pitch control of a variable speed wind turbine (VSWT) systems. The finding of this research includes two tasks: i) to ensure a global stability of the VSWT plant, the reaching phase in traditional sliding mode control (TSMC) technique is eliminated and ii) to guess the immeasurable variables of VSWT plants, a novel pitch angle output feedback controller is constructed based on the estimator tool and output information only. Firstly, a single-phase switching function is determined to eject the reaching phase in TSMC. Moreover, an immeasurable variable of the VSWT system is estimated by employing the suggested estimator tool. Next, a SPRSMC for VSWT plant is built based on the support of the estimator instrument and output data only. Furthermore, an appropriate requirement is founded by utilizing the linear matrix inequality (LMI) method for ensuring the robust stability of motion dynamics in sliding mode. Finally, the solution of the suggested control is confirmed the three-blade wind turbine with a 5-MW utilizing the wind turbine simulator fatigue, aerodynamics, structures, and turbulence (FAST) code and the National Renewable Energy Laboratory (NREL). Creator An entity primarily responsible for making the resource Cong-Trang Nguyen1, Chiem Trong Hien2, Van-Duc Phan3 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Output feedback Pitch control Sliding mode control Variable speed wind turbine Without reaching phase https://repository.horizon.ac.id/files/original/16b6719a94f8a4dc961e6a0c264594de.pdf 0c620bdda4e0a30dde4407de4cab3858 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Progressive energy management technique for smart load control Subject The topic of the resource Demand-side management Energy consumption Load control Microprocessor Web application Description An account of the resource Electricity demand is rapidly increasing in many countries especially because of the increase in smart appliances, smart cities, and communities. The use of electricity ranges from agricultural load, to commercial and industrial load, and also residential load which account for the largest contributor to the increase in peak demand. Thus, residential consumers play a massive role in the national demand for electrical energy and power. The increased demand puts increasing pressure on the energy suppliers who force consumers to cope with short peaks. The need arises for an energy management technique to reduce energy consumption by allowing for consumer load control. The method explores using a Raspberry Pi to collect and evaluate the energy consumed over time and allow consumers access to directly control their home appliances. A more accurate load curve is deduced using the new readings gotten from the end-users. The data obtained from the proposed system is sent to a progressive web application that allows users manage their energy consumption. Creator An entity primarily responsible for making the resource Timilehin Sanni, Mobolade Olawale, Amarachi Attah, Anthony Adoghe, Ayokunle Awelewa Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jul 12, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Demand-side management Energy consumption Load control Microprocessor Web application https://repository.horizon.ac.id/files/original/89cd16c503b35f087c5f41c621233444.pdf 10cc90a655ad834366207c9a0c8c5291 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Smart hydroponic agriculture using genetic algorithm based k-nearest neighbors Subject The topic of the resource Genetic algorithms Internet of things K-nearest neighbor Machine learning Raspberry Pi Description An account of the resource In this research, researcher has implemented supervised machine learning, namely k-nearest neighbor (k-NN) which is optimized using genetic algorithms, and the internet of things (IoT) on the nutrient film technique (NFT) hydroponic system. The aim of this research is to improve the accuracy of classification of nutrient and light conditions in NFT system, and evaluating the harvest of hydroponic farming. The dataset was obtained by observing and recording nutritional and light conditions using sensors for 35 days during the growing period of lettuce in the NFT system, thus obtaining 1,680 data. Then, a training dataset is created based on that dataset. The system architecture is divided into 3 parts, namely the sensor system, data processing, and actuator system. The conclusion of this research is the IoT can be used to monitor the nutritional and light conditions of NFT system in real time and automatic control actions can be carried out using actuators controlled by the Raspberry Pi, the impact of applying the k-NN algorithm and the genetic algorithms is the accuracy of classifying nutritional and light conditions is 92%, the lettuce in a NFT system controlled by the system grow better than the lettuce in a NFT system controlled manually. Creator An entity primarily responsible for making the resource Budi Sutrisno1, Nico Surantha1,2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Genetic algorithms Internet of things K-nearest neighbor Machine learning Raspberry Pi https://repository.horizon.ac.id/files/original/3a12c08a5c7f829ec034dbc5a106bcc0.pdf 6107285ee8e57371a5c64c55663f9f0c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Study of ISFET sensitivity to pH variations using Silvaco TCAD Subject The topic of the resource Electrolyte High-k materials Ion-sensitive field-effect transistor pH sensitivity Silvaco technology computer-aided design Description An account of the resource Chemical sensors are increasingly used in healthcare because of their small size, durability, low resistance, and quick reaction time. This research aims to develop a pH biosensor utilizing an ion-sensitive field-effect transistor (ISFET) simulated with Silvaco technology computer-aided design (TCAD) software. The pH range of operation for the ISFET is 2 to 12. Sensitivity was evaluated based on the critical pH value and threshold voltage (Vth) parameters across different gate channel lengths (250 nm, 200 nm, and 50 nm) and sensing membrane thicknesses (3 nm, 10 nm, and 20 nm). The sensitivity of different materials to pH levels was measured. Titanium dioxide (TiO2) had the highest sensitivity at 57.98 mV/pH, followed by hafnium (IV) oxide (HfO2) at 57.46 mV/pH, tantalum pentoxide (Ta2O5) at 57.36 mV/pH, aluminium oxide (Al2O3) at 55.05 mV/pH, and silicon nitride (Si3N4) at 54.75 mV/pH. Notably, TiO2 with a 200 nm gate channel length and a 3 nm sensing membrane thickness demonstrated the highest sensitivity. These findings highlight the potential of ISFETs, particularly those with TiO2 sensing membranes, as robust and precise pH monitoring platforms in the biomedical industry. Creator An entity primarily responsible for making the resource Nur Afiqah Hani Senin1, Anis Suhaila Mohd Zain1, Fauziyah Salehuddin1, Hazura Haroon1, Ahmed Musa Dinar2, Norwahidah Abdul Karim3 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Electrolyte High-k materials Ion-sensitive field-effect transistor pH sensitivity Silvaco technology computer-aided design https://repository.horizon.ac.id/files/original/5623766ccf3db8c76de74296255dd4ff.pdf f0d58eb136421708b6d4207751f949ed Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.5 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource SYNDIAG: an expert system for disease syndrome diagnosis of traditional Vietnamese medicine Subject The topic of the resource Abelian group operations Disease syndrome diagnosis Expert systems Fuzzy systems MYCIN-like systems Traditional Vietnamese medicine Description An account of the resource Vietnam medicine consists of traditional Vietnam medicine and Western medicine. There is a lack of experienced traditional medicine practitioners, therefore, it needs to develop an expert system supporting medical practitioners in diagnosis. In this paper, we present an overview of syndrome diagnosis (SYNDIAG), a rule-based expert system for disease syndrome diagnosis in traditional Vietnamese medicine. The system consists of five components: knowledge base, inference engine, knowledge acquisition, explanation, and user interface. The paper focuses on how the rule base is constructed, managed, and used. At present, this knowledge base contains more than 1,000 rules used for the diagnosis of 50 disease syndromes of traditional Vietnamese medicine. The inference engine of the system applies the knowledge propagation and the algebra structure of MYCIN-like systems. We also present here the first evaluation of SYNDIAG by the practitioners of traditional medicine, who have been playing a very important role by providing the system with their knowledge. Creator An entity primarily responsible for making the resource Truong Hong Thuy1, Ha Manh Toan2, Vu Tung Lam3, Nguyen Hoang Phuong4 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Abelian group operations Disease syndrome diagnosis Expert systems Fuzzy systems MYCIN-like systems Traditional Vietnamese medicine