1 10 27 https://repository.horizon.ac.id/files/original/361a80b737b1e0d203aec5c48636cbcb.pdf 694d30b0eb6aa6cbd6c7dc62fe9a24b6 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 Feature selection to improve distributed denial of service detection accuracy using hybrid N-Gram heuristic techniques Subject The topic of the resource Chi-square distance Distributed denial of service Malware N-Grams Payload Description An account of the resource Distributed denial of service (DDoS) attacks servers and computers in various ways, such as flooding traffic. There are three DDoS detection methods, namely anomaly-based, pattern-based and heuristic-based. However, pattern-based methods cannot detect recent attacks, while anomaly-based methods have low accuracy and relatively high false positives. This research proposes increasing accuracy using a heuristic-based DDoS detection method and a new feature. The combination of CSDPayload+N-Gram and CSPayload+N-Gram features is called hybrid N-Gram, which is analysed on four datasets: CIC2017, CIC2019, MIB-2016, and H2NPayload. Next, calculate Chi-square distance (CSD) and cosine similarity (CS) using the N-Gram frequency value results. Subsequently, compute Pearson Chi-square using the N-Gram frequency value results. Compare the CSDPayload+N-Gram and CSPayload+N-Gram, along with the Pearson Chi-square value, to classify it as either DDoS or not. Finally, feature selection based on weight correlation and payload classification employs machine learning algorithms: support vector machine (SVM), K-nearest neighbors (KNN), and neural network (NN). The average accuracy rate for detecting DDoS attacks across four datasets, utilising the CSDPayload+4-Gram and CSPayload+4-Gram features with the SVM algorithm, is 99.71%, which surpasses the accuracy achieved by using KNN (96.22%) and NNs (99.50%) imitation. Thus, the best algorithm for detecting DDoS is SVM with hybrid 4-Gram. Creator An entity primarily responsible for making the resource Andi Maslan1, Abdul Hamid2, Dedy Fitriawan3, Anggia Dasa Putri1, Tukino1 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/f5e284ccf77929cddd4e7ccc0fa6cb99.pdf 3aca7aa845475b03dcafb3d668c5772d 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 Increasing the perovskite cell performance using comparative layering method between PTAA and PEDOT: PSS layers Subject The topic of the resource Efficiency Instability Materials Nanocrystals Perovskite Description An account of the resource Today, perovskite solar cells are introduced and used as a suitable alternative with high efficiency for silicon solar cells. The main problem of this type of cells until now has been mostly about their instability, because these materials that are used in perovskite solar cells are rapidly destroyed in reaction with air or their efficiency is greatly reduced. In this article, we increase the productivity to an acceptable amount and also increase its stability by using new high-quality synthesized materials and also by changing the manufacturing method of perovskite solar cells. Using the hole transport layers (HTLs), in the inverse planar perovskite solar cell structure, the effect of two layers of poly (triarylamine) (PTAA) and poly (3,4-ethylenedioxythiophene) (PEDOT): PSS as the bottom layer of the perovskite film on the morphology of the nanoparticles, the crystallinity of the perovskite layer and the photovoltaic parameters affecting the efficiency of the solar cell made in a single-step method were investigated. The result shows the PTAA layer has been very effective in controlling the morphology of the perovskite layer, so the efficiency reached to 23.9% while the maximum efficiency per solar cell based on PEDOT: PSS is 11.37%. Creator An entity primarily responsible for making the resource Vahdat Nazerian1, Mehran Hosseinzadeh Dizaj2, Amir Assari3, Shahed Chehrdoust Shishvan2, Fatemeh Shahnavaz4, Tole Sutikno5,6 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 Efficiency Instability Materials Nanocrystals Perovskite https://repository.horizon.ac.id/files/original/fa3008cc2df9681371d32f6f06c9e40a.pdf eaf175d874dfe2fc3e7834fa866fd64c 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 Video semantic segmentation with low latency Subject The topic of the resource Convolutional neural network Decision network FlowNet Latency Object detection SegNet Semantic segmentation Description An account of the resource Recent advances in computer vision and deep learning algorithms have yielded intriguing results. It can perform tasks previously requiring human eyes and brains. Semantic video segmentation for autonomous cars is difficult due to the high cost, low latency, and performance requirements of convolutional neural networks (CNNs). Deep learning architectures like SegNet and FlowNet 2.0 on the Cambridge-driving labeled video database (CamVid) dataset enable low-latency pixel-wise semantic segmentation of video features. Because it uses SegNet and FlowNet topologies, it is ideal for practical applications. The decision network chooses an optical flow or segmentation network for an image frame based on the expected confidence score. Combining this decision-making method with adaptive scheduling of the key frame approach can speed up the process. ResNet50 SegNet has a “54.27%” mean intersection over union (MIoU) and a “19.57” average FPS. In addition to decision network and adaptive key frame sequencing, FlowNet2.0 increased graphics processing unit (GPU) frame processing per second to “30.19” with a MIoU of “47.65%”. The GPU is used “47.65%” of the time. This performance gain illustrates that the video semantic segmentation network is faster without sacrificing quality. Creator An entity primarily responsible for making the resource Channappa Gowda D. V., Kanagavalli R. 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 Mar 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 Convolutional neural network Decision network FlowNet Latency Object detection SegNet Semantic segmentation https://repository.horizon.ac.id/files/original/eb0a10ee3f316080a94712256f9b7591.pdf f6d20c1004766cab2dbdd50f63154767 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 Effective capacity analysis of full-duplex-cooperative non-orthogonal multiple access systems Subject The topic of the resource Effective capacity Full-duplex Multi-reconfigurable intelligent surfaces Non-orthogonal multiple access Outage probability Description An account of the resource This study explores a dual-user full-duplex cooperative non-orthogonal multiple access (FD-CNOMA) network, presenting closed-form expressions for the outage probability (OP) and effective capacity (EC) of both users. The analytical results indicate that an increased signal-to-noise ratio (SNR) corresponds to a reduced OP and heightened EC, signifying enhanced communication quality. We analyze the OP and EC under two cases: R1=2R2 and R1=R2. Our analytical expressions reveal that both θ and ρ significantly impact the effective capacities. To validate these analytical findings, Monte Carlo simulations are performed, demonstrating alignment between theoretical insights and practical outcomes. The results underscore the critical role of SNR in influencing network performance, providing valuable insights into optimizing communication quality in FD-CNOMA systems. Creator An entity primarily responsible for making the resource Huu Q. Tran1, Samarendra Nath Sur2 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 Effective capacity Full-duplex Multi-reconfigurable intelligent surfaces Non-orthogonal multiple access Outage probability https://repository.horizon.ac.id/files/original/403207a23fdec4b85542edaa7735a9dc.pdf dfeb990d25a828905f34a3913e68e789 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 Enhanced matrix-based error correction coding techniques for embedded memories Subject The topic of the resource Correction masking technique Error correction code H-matrix Memories single bit upsets Multiple bit upsets Description An account of the resource Memories play a very important role in computing systems due to the continuous advancements in technology. They are used to store data that is used for proper system operations. Memory architectures that are more intricately designed are more prone to radiation-induced errors such as single bit upsets (SBU) and multiple bit upsets (MBU). Error correction codes (ECC) are used to recover the corrupted data that are stored in memories. H-matrix-based ECC is the commonly used ECC for memories. On the other side, the correction masking (CM) technique was added to ECC to mask the correctable error patterns. CM technique protects the error-free bits while correcting erroneous bits. In this paper, optimized H-matrices are presented. These matrices are used to design an ECC with the CM technique to correct 2-bit to 7-bit adjacent errors. The result shows there is a reduction in the power of 2, 3, and 4 adjacent bit errors by 19.009%, 4.615%, and 27.934% respectively. Creator An entity primarily responsible for making the resource Jammula Shivani, Mandadi Shankar Teja, Manickaraj Vinodhini 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 https://repository.horizon.ac.id/files/original/651f49c79c34a4e252b6f8bdb1c5e287.pdf 7d52c21b65906dc0f4a3db646db738ae 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 Analysis comparison, calibration, and application of low-cost soil moisture in smart agriculture based on internet of things Subject The topic of the resource Calibration Capacitive sensor Internet of things Resistive sensor Soil moisture Description An account of the resource The gravimetric method is one of the most accurate for determining soil water content (SWC). Several low-cost sensors have been developed to simplify measuring water content in soil by measuring soil moisture. However, the sensor must be calibrated to determine soil moisture parameters accurately. In this research, comparative analysis, and calibration of resistive and capacitive low-cost sensors were carried out. The calibration method for each sensor uses the gravimetric water content (GWC) and volumetric water content (VWC) methods. Measuring changes in SWC using sensors is performed in real time based on internet of things (IoT). Based on the measurements of the capacitive, resistive type 1, and resistive type 2 sensors with three repetitions, the linear regression R2 values were obtained at 0.980, 0.827, and 0.942, respectively. Furthermore, a stability test is carried out to see how stable the sensor is when making measurements over a long period. The result is that the capacitive, resistive type 1, and resistive type 2 sensors have errors 1.971×10-4, 7.001×10-4, and 6.270×10-4. Based on the results obtained, capacitive sensors have the highest level of accuracy and stability. Furthermore, capacitive sensors are applied to IoT-based agriculture with long range (LoRa) as communication data. Creator An entity primarily responsible for making the resource Beny Agustirandi1, Inayatul Inayah1,2, Nina Siti Aminah1, Maman Budiman1 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 Calibration Capacitive sensor Internet of things Resistive sensor Soil moisture https://repository.horizon.ac.id/files/original/66bf0f5f5c81e159cf77fc893dec3775.pdf 0f6bd1d084ed6cf5d2f324b3b0b96465 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 Performance analysis of circular polarization X-band microstrip patch antenna combined with conical horn Subject The topic of the resource Circular polarization Conical horn Microstrip antenna Parabolic reflector Satellite X-band Description An account of the resource A ground station antenna system features a conical horn attached to a microstrip antenna as an alternate receiving feed antenna. The proposed microstrip antenna has circular polarization and operates in the X-band. The far-field parameters of the antenna are measured after developing and simulating the combination of a conical horn and a microstrip antenna. The modeling results for a microstrip antenna with a conical horn offer a working bandwidth of 930 MHz, spanning frequencies 7.44 GHz to 8.37 GHz. The axial ratio measurements for a microstrip antenna joined with a conical horn produce a working bandwidth of 150 MHz, covering frequencies ranging from 7.72 GHz to 7.87 GHz. The conical horn is attached to a microstrip antenna and has a gain of 15.1 dB. The proposed antenna is designed to meet ground station antenna requirements by pairing it with a parabolic reflector with a diameter of 3.7 meters. The primary focus antenna of the proposed design was chosen. The feed antenna and parabolic reflector should be positioned at a focus point distance of 1110 mm for a total gain of 38.9 dB at 7.8 GHz frequency. The proposed antenna can be applied on X-band remote sensing ground stations as a receiving antenna. Creator An entity primarily responsible for making the resource B. Pratiknyo Adi Mahatmanto1, Dedi Irawadi1, Hidayat Gunawan1, Nugroho Widi Jatmiko1, Dinari Nikken Sulastrie Sirin1, Supriyono1, Suhermanto1, Bambang Dewandaru2, Catur Apriono3 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/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 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/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