1 10 27 https://repository.horizon.ac.id/files/original/3aba67938c758a5a05337a7068621023.pdf 337e13f602e8802a85aa3f19848a79a1 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.4 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 ANN-based performance estimation of a slotted inverted F-shaped tri-band antenna for satellite/mm-wave 5G application Subject The topic of the resource 5G Antenna Artificial neural network Industrial and innovation Satellite Tri-band Description An account of the resource In this research, we explain comprehensive industrial and innovation results on using an artificial neural network (ANN) method to improve the performance of microstrip patch antennas for 5G, indoor-outdoor, and Ku band uses. To determine if an antenna is appropriate, this article discusses multiple methods, one of which is to do a simulation using validating software like high frequency structure simulator (HFSS) and Altair Feko. Based on the Rogers RT 5880 substrate, the antenna is constructed. There is a loss tangent of 0.0009 and its dimensions are 17.1053 mm in length and 16 mm in width. Its dielectric constant is 2.2. Despite its small size, it boasts an impressive maximum efficiency of almost 90% and a gain of approximately 8 dB. As an indicator of ANN model performance, we may look at the R-squared value (99%), the mean square error (MSE), which is approximately 0.0015, and the confidence interval (99%). The ANN models are the most accurate and have the lowest error rate when it comes to predicting efficiency and gain. The suggested antenna is a promising contender for the targeted Ku band, indoor/outdoor, and 5G uses, as verified by the clustering of computer simulation technology (CST), HFSS, and Altair Feko simulated results with the measured and predicted outcomes of ANN approach. Creator An entity primarily responsible for making the resource Md. Kawsar Ahmed1, Kamal Hossain Nahin1, Md. Sharif Ahammed1, Md. Ashraful Haque1, Narinderjit Singh Sawaran Singh2, Redwan Al Mahmud Asad Ananta1, Jamal Hossain Nirob1, Mirajul Islam3, Liton Chandra Paul4 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 29, 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 5G Antenna Artificial neural network Industrial and innovation Satellite Tri-band https://repository.horizon.ac.id/files/original/638a3f6850acd19ac3e5eefd58688467.pdf 65d2664ca075908f647969958e8c71b7 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.4 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 Applying artificial neural network on heart rate variability and electroencephalogram signals to determine stress Subject The topic of the resource Artificial neural network Electrocardiogram Electroencephalography stratified K-fold Health Stress detection Description An account of the resource Emotions are mental states, categorizes them into positive and negative feelings, and uses stress as an example of a negative emotion. Research demonstrated that acute and chronic stress can change physiological variables, such as heart rate variability (HRV) and electroencephalography (EEG). This research aims to early prevention and management of stress that is comfortable to use, reliable and accurate for stress detection. The Einthoven triangle rule was used to gather electrocardiogram (ECG) signals, while EEG signals were obtained from Fp1 and F3 connected to mikromedia 7 with the STM32F746ZG chipset. Various parameters were examined, including ECG signals in the time domain, frequency domain, non-linear analysis, and EEG signals in the frequency domain. Healthy subjects aged 18-23 undergoing different stress-inducing stages, with stress levels validated through the STAI-Y1 questionnaire. To process the HRV and EEG features, Pearson’s correlation function (PCF) was employed to select appropriated features into classification method. The proposed classification method in this research is the artificial neural network (ANN) with stratified K-fold, which yielded a stress level output accuracy of 95%. Additionally, the STAI-Y1 questionnaire results evaluation indicated a similarity score of 90.91%. This research has potential applications for individuals experiencing stress, providing a valuable tool for stress detection. Creator An entity primarily responsible for making the resource Steven Matthew Gondowijoyo, Rachmad Setiawan, Nada Fitrieyatul Hikmah 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 Jan 20, 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 Artificial neural network Electrocardiogram Electroencephalography stratified K-fold Health Stress detection https://repository.horizon.ac.id/files/original/e36777fa2c6ee2f8f5cc86367ef0c7ac.pdf 5f95d039d078bb1e0462cb57fb785c37 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.4 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 Automated classification of diseased cauliflower: a feature-driven machine learning approach Subject The topic of the resource Analysis of variance Bagging classifier Cauliflower Image processing Machine learning Description An account of the resource Cauliflower is a popular winter crop in Bangladesh. However, cauliflower plants are vulnerable to several diseases that can reduce the cauliflowers’ productivity and degrade their quality. The manual monitoring of these diseases takes a lot of effort and time. Therefore, automatic classification of the diseased cauliflower through computer vision techniques is essential. This study has retrieved ten different statistical and gray-level co-occurrence matrix (GLCM)-based features from the cauliflower image dataset by implementing a variety of image processing techniques. Afterwards, the SelectKBest method with the analysis of variance f-value (ANOVA F-value) has been used to identify the most important attributes for classification of the diseased cauliflower. Based on the ANOVA F-value, the top N (5≤N ≤9) most dominant attributes is used to train and test five machine learning (ML) models for classification of diseased cauliflower. Finally, different performance metrics have been used for evaluating the effectiveness of the employed ML models. The bagging classifier achieved the highest accuracy of 82.35%. Moreover, this model has outperformed other ML classifiers in terms of other performance metrics also. Creator An entity primarily responsible for making the resource Mala Rani Barman1, Al Amin Biswas2, Marjia Sultana3, Aditya Rajbongshi4, Md. Sabab Zulfiker2, Tasnim Tabassum5 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 Dec 27, 2023 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 Analysis of variance Bagging classifier Cauliflower Image processing Machine learning https://repository.horizon.ac.id/files/original/addfd3e01a214a95771cfbe37929bfa3.pdf 73bb7fe4e64eabd30f4c2aa6d2ba7ec9 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.4 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 Big data in the hospitality industry: a methodical review Subject The topic of the resource Big data Business intelligence Data mining Hospitality Machine learning Description An account of the resource This study intends to identify research gaps and future trends and provide a framework for the next generation of research to assess how much big data (BD) is employed in hospitality and tourist research. The study is based on a comprehensive quantitative evaluation of the relevant literature: Scopus and Web of Science (WoS)-listed academic works. The following criteria were used to assess the submissions: those who have the following traits an overview of the study’s subject matter, including its theoretical and conceptual framework, data sources, data kind and quantity, data collection methods, and data analysis methodologies. Research shows that the usage of books on hospitality and tourism management has increased in recent years. Massive volumes of data are analyzed using analytical methods. However, the scope of this investigation is really wide. Furthermore, this research contributes to an in-depth and systematic assessment of the extent to which scholars in hospitality/tourism know and work on business intelligence and BD. This is the first complete survey of the literature on the topic of hospitality and tourism. Creator An entity primarily responsible for making the resource Omar Jawabreh1, Rami Mahmoud1, Basel J. A. Ali2 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 29, 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 Big data Business intelligence Data mining Hospitality Machine learning https://repository.horizon.ac.id/files/original/22d1498b83bf29253228e7d71cb84b64.pdf e530b12181663b729c04a4a7b0fa4a37 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.4 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 Classifying date fruits using the transfer learning model Subject The topic of the resource Date fruit Educational technology Image classification Malaysia Mobile application Transfer learning Description An account of the resource Date palm trees originate in many tropical regions of the world and produce dates. Each variety can be differentiated through the shape, texture, size, and colour of the fruits. People have difficulties visualising and recognising the types of date fruits because they have many varieties and species. An Android-based mobile application is being proposed to help users quickly identify the dates based on their images and expand their knowledge of dates. The date fruit species classification mobile application categorises nine different varieties of date fruits, namely Ajwa, Medjool, Rutab, Nabtat Ali, Meneifi, Galaxy, Sugaey, Shaishe, and Sokari. The classification, which is based on a transfer learning technique from a pre-trained neural network, achieved a 94.2% accuracy rate. The mobile application features a user-friendly graphical interface that makes it easy to use and understand. Users can learn about different date fruit varieties and improve knowledge retention through a mini game. The application’s usability, usefulness, and interface design were confirmed through the user acceptance survey. Creator An entity primarily responsible for making the resource Alia Nadzirah Mohd Adnan1, Nurul Amelina Nasharuddin1,2 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 Mar 29, 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/086931ea311ee297f52f9821b3b10a9b.pdf 57ef4de4b357051cc5b27767c3024bbb 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.4 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 Convolutional neural network enhancement for mobile application of offline handwritten signature verification Subject The topic of the resource Convolutional neural network Genuine Image classification Mobile Signature Description An account of the resource The increase in signature forgery cases can be attributed to the escape of forged signatures from manual signature verification systems. Researchers have developed various machine learning and deep learning methods to verify the authenticity of signatures, one of which uses convolutional neural networks (CNNs). This research aims to develop a mobile application for handwritten signature verification using CNN architecture by adding a batch normalization technique to its layer. The performance of our proposed method achieved a verification accuracy of 86.36%, with a 0.061 false acceptance rate (FAR), 0.303 false rejection rate (FRR), and 0.182 equal error rate (EER), which is compatible to be embedded in smartphones. However, there is still a need for further development of the CNN model and its integration with mobile applications. Creator An entity primarily responsible for making the resource Wifda Muna Fatihia, Arna Fariza, Tita Karlita 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 29, 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 Genuine Image classification Mobile Signature https://repository.horizon.ac.id/files/original/444f0a60555ad786a5a2524e644fc7b2.pdf 2486f3102265f017d60fde9961f512db 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.4 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 Design monopole antenna of ultra-wideband high bandwidth and high efficiency for ground penetrating radar application Subject The topic of the resource Antenna Bandwidth Computer simulation technology Ground penetrating radar Monopole Ultra-wideband Description An account of the resource Over the past years, remote sensing, radar, and imaging applications have all made use of ultra-wideband (UWB) technology. This study undertakes an extensive analysis of tree-shaped monopole antennas tailored for UWB systems. The intended antenna has an incomplete ground plane and a circular radiating patch. To increase bandwidth, two ears have been added to the circular structure. Possessing a dielectric constant of 4.3. The antenna substrate consists of FR-4 material with a dielectric constant of 4.3. To achieve optimal impedance matching for UWB systems, the antenna is fed via a coplanar waveguide (CPW). Design antenna is a simple structure, small size, easy design, and simple integration with the substrate with dimensions of 54 mm ×36 mm ×1.6 mm. All simulation results presented in this article were generated using computer simulation technology (CST) software. He monopole antenna exhibits an impressive impedance bandwidth of 9.6 GHz (146.68%), spanning from 1.99 GHz to 11.56 GHz. Furthermore, the simulated UWB circular monopole antenna exhibits omnidirectional radiation characteristics, boasting a peak gain of 8 dB, and a directivity of 8.2 dBi at the frequency of 5 GHz, and a remarkable radiation efficiency of 97%. With these attributes, the suggested monopole UWB antenna shows significant potential for ground penetrating radar (GPR) applications. Creator An entity primarily responsible for making the resource Fatehi ALtalqi, Sara Fennane, Hamza Mabchour, Houda Kacimi, Adil Echchelh 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 29, 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 Antenna Bandwidth Computer simulation technology Ground penetrating radar Monopole Ultra-wideband https://repository.horizon.ac.id/files/original/4b439b64ed1f3ac507b33c34fddd7639.pdf ba05720930c8e88911f6ef07b463cd9e 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.4 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 Effectiveness of Bluetooth communication of digital stethoscope using quality of service method Subject The topic of the resource HC-05 Heart sound Quality of service Stethoscope Wireless Description An account of the resource This study aims to design and evaluate a wireless electronic stethoscope that can transmit heart sound using Bluetooth HC-05 and Bluetooth 5.0 transmitter. This novel design contributes to the remote diagnosis and monitoring of heart conditions, especially for patients with infectious diseases. The heart sound signals are captured using a mic condenser mic, amplified, filtered, and converted to digital data by a microcontroller. The data are then transmitted by Bluetooth HC-05 to a module and by Bluetooth 5.0 transmitter to a headset. The quality-of-service parameters such as throughput, delay, and packet loss ratio (PLR) of the data transmission at different distances are measured. The results show that the wireless electronic stethoscope can transmit heart sound data with a small PLR of 0.10% and a throughput of 1002.5 bps. The study concludes that the wireless electronic stethoscope is an effective and useful device for examining heart conditions remotely, without compromising the functionality of the device. Creator An entity primarily responsible for making the resource Endang Dian Setyoningsih, Sumber, Triwiyanto, Farid Amrinsani 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 Feb 29, 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 HC-05 Heart sound Quality of service Stethoscope Wireless https://repository.horizon.ac.id/files/original/cc269b98bf6759cbc9113bdea1ae3ac5.pdf 54a738c6e3ec77beafebe3d1b016ebec 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.4 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 Electro-optic MMI coupler as wavelength demultiplexer for advanced SDM wireless-WDM optical signal converter Subject The topic of the resource Electro-optic modulator LiNbO3 Multimode interference coupler SDM-WDM converter Wavelength demultiplexer Description An account of the resource We report the design, fabrication, and experimental results of an optical wavelength demultiplexer for a new wireless-optical signal converter for Beyond-5G/6G mobile communication system. This optical wavelength demultiplexer is based on a lithium niobate (LiNbO3) multimode interference (MMI) coupler and is intended to be applied in an advanced electro-optics modulator (EOM) with ability in converting the space division multiplexing (SDM) wireless-wavelength division multiplexing (WDM) optical signals. The designed MMI coupler displays a high splitting ratio over -13 dB in both O and L bands. The results from the experiments align well with the simulation. The utilization of the MMI coupler in EOM enables the direct conversion of SDM wireless signals to WDM optical signals, without any additional power supply. The modification of the characteristic of a constructed MMI coupler can be achieved by controlling of the applied voltage of the device. Creator An entity primarily responsible for making the resource Mefina Yulias Rofianingrum1,2, Yui Otagaki1, Hiroshi Murata1 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 29, 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 Electro-optic modulator LiNbO3 Multimode interference coupler SDM-WDM converter Wavelength demultiplexer https://repository.horizon.ac.id/files/original/c4169bc862b43f2ad629fa24c1921b9c.pdf f07ff051410b8676e2edd0cdd3cfe469 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.4 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 End-fire multibeam radial line slot array antennas Subject The topic of the resource End-fire High beamsquint Multibeam Radial line slot array Wi-Fi Description An account of the resource This research proposed and verified a novel method in realizing end-fire radial line slot array (RLSA) antennas. This method involved the use of high beamsquint values in the design of slot pairs, which aimed to shift the antenna’s beam toward the end-fire direction. Furthermore, identical slot pairs were also placed in the antenna’s background to further squint the beam in the end-fire direction. By using this method, forty multibeam end-fire RLSA antennas were modeled and simulated to determine the most efficient model to be fabricated. The accuracy of the simulations was confirmed through measurements taken from the fabricated prototype, which demonstrate good agreement with the simulation results and confirm the validity of the proposed method. The result showed that it is possible to design four end-fire beam antennas with a gain of 8 dBi, directions of 0°, 90°, 180°, and 270° in the azimuth direction, and a beamwidth of about 20°. The antenna also showed low reflection and bandwidth of about 500 MHz, which is suitable for Wi-Fi applications. Creator An entity primarily responsible for making the resource Teddy Purnamirza1, Junisbekov M. Shardarbekovich2, Riza A. Jaya1, Imran Mohd Ibrahim3, Kabanbayev A. Batyrbekovich2, Depriwana Rahmi4 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 Feb 13, 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