1 10 26 https://repository.horizon.ac.id/files/original/34473ca65faa329392be22da1184d7c7.pdf 543a4f30066c5886aced16382e3164a3 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. 23, NO.1 2025 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 Prediction of heart disease using random forest algorithm, support vector machine, and neural network Subject The topic of the resource Heart disease Neural network Prediction Random forest Support vector machine Description An account of the resource The heart is a vital organ responsible for pumping blood throughout the human body. Machine learning has become an increasingly important tool in medical forecasting, improving diagnostic accuracy and reducing human errors. This study focuses on detecting heart disease using machine learning algorithms. It aims to compare the performance of three key algorithms random forest (RF), support vector machine (SVM), and neural networks (NN), in predicting heart disease. Using a patient dataset with both nominal and numeric attributes, record mining techniques were applied through Orange software. The target classes indicated the absence (0) or presence (1) of heart disorders. The evaluation was based on the prediction accuracy of each algorithm. Results show that SVM achieved the highest accuracy, with a rate of 85%, outperforming RF and NN. The findings suggest that the SVM algorithm is a reliable tool for heart disease prediction, helping reduce diagnostic errors and improve medical decision-making. Creator An entity primarily responsible for making the resource Didik Setiyadi1, Henderi2, Anrie Suryaningrat3, Rulin Swastika4, Saludin5, Muhamad Malik Mutoffar6, Imam Yunianto7 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 Sep 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 https://repository.horizon.ac.id/files/original/98e9ff407140f71c76df5affc95c22fb.pdf 7f3f4bbba08f43e696c4ba6136e62760 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. 23, NO.1 2025 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 Effects of atmospheric turbulence and reconfigurable intelligent surfaces on near terrestrial optical link for internet of things Subject The topic of the resource Atmospheric turbulence Average channel capacity Optical communication Quadrature amplitude modulation Reconfigurable intelligent surfaces Description An account of the resource Near terrestrial free-space optical (NT-FSO) communication refers to the use of light to transmit data wirelessly through the atmosphere over relatively short distances, typically within the earth’s atmosphere. It is an alternative to traditional radio frequency (RF) communication and fiber optics, providing high-speed data transmission without the need for physical cables. NT-FSO is an attractive solution for high-speed, short-distance wireless communications where physical infrastructure like fiber is impractical. Reconfigurable intelligent surfaces (RIS) are a cutting-edge technology that enhances wireless communication systems by dynamically controlling how electromagnetic waves propagate through an environment. RIS technology is increasingly relevant in modern communication systems like 5G and beyond, aiming to improve the efficiency, coverage, and energy usage of wireless networks. This study investigates the effects of atmospheric turbulence and RIS on near terrestrial optical link for internet of things. Several numerical outcomes obtained for different link distance and average electrical signal signal-to-noise ratio (SNR) are shown to quantitatively illustrate the average spectral efficiency. Creator An entity primarily responsible for making the resource Duong Huu Ai1, Hoang Huu Duc2, Khanh Ty Luong3, Ngoc Dat Vo3 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 Nov 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 Atmospheric turbulence Average channel capacity Optical communication Quadrature amplitude modulation Reconfigurable intelligent surfaces https://repository.horizon.ac.id/files/original/b2b594ee34fb54bff01274d8b50588de.pdf d0da7f6ab1846bb1c6c07f456cc28fad 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. 23, NO.1 2025 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 Identification of working memory status in children from EEG signal features using discrete wavelet transform Subject The topic of the resource Brain signals Feature extraction Power spectral density Wavelet Working memory assessment Description An account of the resource The conventional method for assessing the working memory performance of children is time-consuming and potentially inaccurate, especially when dealing with many samples. Therefore, an automated system that can produce swift and accurate results is required. Electroencephalograms (EEG) can be used to analyse the working memory status of children by extracting specific features from the EEG signal, which can be incorporated into an automatic system to reduce manpower and processing time for analysis. This project used EEG recording to identify children’s working memory status while they were performing working memory tasks. EEG signals were acquired from both children and adults using an automated computer-based working memory assessment tool, processed, and analyzed. The discrete wavelet transform (DWT) was then employed to identify five distinct working memory statuses: distracted, confused, daydreaming, losing focus, and active. DWT was also used to extract features that demonstrate these various statuses. The results showed that DWT could accurately identify the working memory status of both children and adults from their EEGs. This work has thus provided a more efficient method for extracting features from EEG signals to identify working memory statuses in both children and adults. Creator An entity primarily responsible for making the resource Muhammad Hilmi Khairul Azlan1,2, Wahidah Mansor1,2, Ahmad Ihsan Mohd Yassin1,2, Nabila Ameera Zainal Abidin1,2, Mirsa Nurfarhan Mohd Azhan1,2, Aisyah Hartini Jahidin3, Muhammad Fakharul Radzy Mohd Rozlan4, Zulkifli Mahmoodin5,6, Megat Syahirul Amin Megat Ali1,2 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 Oct 27, 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 Brain signals Feature extraction Power spectral density Wavelet Working memory assessment https://repository.horizon.ac.id/files/original/4d6e0f2e421d3a20fcd7524748743233.pdf bd2036aff8dab1a3f7645989b5b044d6 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. 23, NO.1 2025 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 NAT64 vs SIIT: performance and scalability study for VoIP services Subject The topic of the resource Graphical network simulator 3 Internet protocol version 6 Internet protocol service level agreement Network address translation 64 Scalability Stateless IP/ICMP translation Voice over internet protocol Description An account of the resource The growing demand for IP addresses, driven by the proliferation of devices, has depleted the internet protocol (IP) version 6 (IPv6) reserves of some regional internet registries (RIRs). It is imperative to migrate to IPv6, offering an extended addressing space. This transition is no longer a choice but a necessity due to the exhaustion of IP version 4 (IPv4) addresses. The internet engineering task force (IETF) has implemented various transition strategies, such as the use of dual stack, IPv6-in-IPv4 tunnels, and address translation, due to the inconsistency between the two versions of the IP (IPv4 and IPv6). IPv4/IPv6 address translation mechanisms are crucial for the coexistence of networks using both protocols, with scalability playing a central role. Although these mechanisms offer advantages such as optimizing addressing space, their ability to scale effectively must be evaluated, especially in demanding scenarios such as voice over IP (VoIP). This article examines the scalability of two mechanisms, network address translation 64 (NAT64) and stateless IP/internet control message protocol (ICMP) translation (SIIT), in terms of VoIP clients in the graphical network simulator 3 (GNS3) environment. The results indicate that the SIIT mechanism is more performant and scalable than NAT64 in all measured parameters. Creator An entity primarily responsible for making the resource Khalid El Khadiri2, Samir Elouaham1, Najib El Kamoun2, Boujemaa Nassiri3, Ali El Ksimi4, Said Amrane2, Said Dlimi2 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 Graphical network simulator 3 Internet protocol version 6 Internet protocol service level agreement Network address translation 64 Scalability Stateless IP/ICMP translation Voice over internet protocol https://repository.horizon.ac.id/files/original/77ee1cbbd871efdf991e7a23c4c87308.pdf 4bb6daabbfc199928b444d8bb8032fb3 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. 23, NO.1 2025 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 Swarm intelligence for intrusion detection systems in internet of things environments Subject The topic of the resource Internet of things Intrusion detection systems Network security Pigeon inspired optimization Swarm intelligence Description An account of the resource The rise of the internet of things (IoT) technology has brought new security challenges, necessitating robust intrusion detection systems (IDS). This research applies swarm intelligence (SI) principles, specifically the pigeon inspired optimization (PIO) algorithm, to enhance IDS effectiveness in IoT environments. Drawing on the behavior of social species, SI fosters decentralized control and emergent behavior from simple rules. These principles guide the PIO algorithm, making it apt for optimizing IDS. We utilize two comprehensive IoT datasets – the Canadian Institute for Cybersecurity (CIC) IoT dataset 2023 and the IoT dataset for IDS, aiming to boost the IDS’s capability to detect illicit attacks. By adapting the PIO algorithm, our IDS learns from the environment, adapts to evolving threats, and mitigates false-positive rates. Preliminary tests show that our SI-based IDS outperforms traditional systems’ accuracy, speed, and adaptability. This research advances SI applications in IoT security, contributing to developing more resilient IDS and ultimately enhancing IoT network security against a range of cyber threats. Creator An entity primarily responsible for making the resource Apri Siswanto1, Akmar Efendi1, Jaroji2, Fajar Ratnawati2 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 Nov 6, 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/a6691fc9f5dc46fa65e782a6d58ed270.pdf 8bdfd0f57a93a0d1ccc1821f9e1d387c 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. 23, NO.1 2025 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 Simple RNN-LSTM hybrid deep learning model for Bitcoin and EUR_USD forecasting Subject The topic of the resource Bitcoin Deep learning Gated recurrent unit Long short term memory Simple recurrent neural network Time series forecasting Description An account of the resource The popularity of deep learning in time series prediction has significantly increased compared to the past. In this article, we utilize deep learning methods, which encompass long short term memory (LSTM) networks, simple recurrent neural network (SimpleRNN) networks, and gated recurrent units (GRU) networks. This research introduces a hybrid foundational model for forecasting future closing prices of EUR_USD in financial time series and Bitcoin, combining SimpleRNN with LSTM, referred to as SimpleRNN-LSTM. To improve the precisions of our hybrid model, we incorporate twenty-one technical indicators into the training data. Then, we compute four measures to evaluate the performance of various prediction models. When predicting currency pairs EUR_USD and Bitcoin, our hybrid foundational model outperforms SimpleRNN, LSTM, and GRU models. Creator An entity primarily responsible for making the resource Mohamed EL Mahjouby1, Khalid El Fahssi2, Mohamed Taj Bennani1, Mohamed Lamrini1, Mohamed El Far1 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 Nov 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 Bitcoin Deep learning Gated recurrent unit Long short term memory Simple recurrent neural network Time series forecasting https://repository.horizon.ac.id/files/original/1bb6d2d6a37d70c6e87de0755d18d499.pdf b2e4f8ebe5c680b07772c614a710628d 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. 23, NO.1 2025 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 Electroencephalography-based wheelchair navigation control using convolutional neural network method Subject The topic of the resource Classification Convolutional neural network Deep learning Electroencephalograph Wheelchair Description An account of the resource Artificial intelligence refers to a computer-based system capable of learning human activities. For instance, in medical technology, AI can be used for a thought-controlled wheelchair. This study discusses the use of deep learning, specifically convolutional neural network (CNN), in predictiong of the user intention to navigate a wheelchair. The training data was collected from an EEG sensor and included the wheelchair’s movements - turning right, turning left, moving forward, moving backward, and idle. The signals were then sampled and feature-extracted using root mean square (RMS). In CNN classification, both raw and RMS data were used. This study compared two different CNN architectures. The first architecture has three convolutional layers and three pooling layers, while the second has two of each. The research compares the accuracy and loss values of CNN predictions using architecture 1 and 2 on both raw and RMS data. The experimental results indicate that when using raw data, the first CNN architecture achieved an accuracy of 85.12%, and the second model achieved 91.04%. However, when using RMS data, the first architecture achieved an accuracy of 76.47%, and the second achieved 73.74%. The study concludes that the movement of the wheelchair is better in real-time when using raw data compared to using RMS data. Creator An entity primarily responsible for making the resource Khairul Anam1,2, Satrio Marta Wicaksono1,2, Muchamad Arif Hana Sasono1,2, Bima Wahyu Maulana1,2, Fatkhul Mubarok1,2, Ananta Pinsentius Rahmat Pamungkas1,2, Moch. Rijal Fatoni1,2 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 Nov 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 Classification Convolutional neural network Deep learning Electroencephalograph Wheelchair https://repository.horizon.ac.id/files/original/9b8185484aae247db2346a73e34551b0.pdf 0d6a8728ed2bc36f1c6344e94a5ccc0b 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. 23, NO.1 2025 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 The bending effects on the performance of a flexible circular microstrip antenna on rubber-carbon substrates at 2.45 GHz Subject The topic of the resource Bending effects Flexible microstrip antenna Industrial, scientific and medical band Rubber-carbon substrate Wearable antenna Description An account of the resource In this paper, we studied the effects of bending on the performance of a flexible circular microstrip antenna on rubber-carbon substrates at the 2.45 GHz industrial, scientific, and medical (ISM) band. Several rubber compositions are analyzed which include natural rubber (no carbon filler), rubber with 20% carbon filler, rubber with 25% carbon filler, and rubber with 50% carbon filler. Four types of bending directions are applied in this work i.e., side-inward, side-outward, top-inward, and top-outward with bending radius ranging from 100-500 mm. It is observed that even though the resonant frequency of the antenna shifted a bit when bending is applied, the S11 at the intended frequency remains below -10 dB. The bandwidth and gain also maintain an acceptable performance despite all the directions and radius of the bending, due to the wide bandwidth characteristics of the antenna. With these results, the proposed antenna is shown to be usable for wearable applications at 2.45 GHz, in both flat and bent conditions. We also show that it is essential to design a flexible antenna with a wide bandwidth to guarantee that the antenna maintains optimal performance even under curved conditions. Creator An entity primarily responsible for making the resource Ahmad Alhadi Ruslan1,2, Sarah Yasmin Mohamad1,2, Norun Farihah Abdul Malek1,2, Siti Hajar Yusoff1, Siti Noorjannah Ibrahim1 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 Sep 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 Bending effects Flexible microstrip antenna Industrial, scientific and medical band Rubber-carbon substrate Wearable antenna https://repository.horizon.ac.id/files/original/3d17c8a043348cd3274ee9a718db9000.pdf ca8c05c5795cec30f8baee67945e8cd0 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. 23, NO.1 2025 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 BER performance in NOMA downlink transmission using AWGN, Rayleigh, and Rician fading channels Subject The topic of the resource Additive white gaussian noise Bit error rate Fifth generation Non-orthogonal multiple access Signal-to-noise ratio Successive interference cancellation Description An account of the resource 5G wireless technology is accessible to a much larger user base compared to previous cellular networks. Users can connect to base stations (BSs) in a variety of methods, including of frequency division multiplexing (FDM), orthogonal frequency division multiplexing (OFDM), orthogonal multiple access (OMA), and non-orthogonal multiple access (NOMA). NOMA is considered to be the best one for 5G. Additionally, NOMA employs radio resource optimization and interference control techniques to enhance spectrum network efficiency and support extremely large connections, such as successive interference cancellation (SIC). Users can be divided into two categories: strong and weak. While weak users may experience a low data rate, strong users need a high one. In this paper, we examine the two users in relation to transmit power, the indicative bit error rate (BER), outage probability (OP), and rate attainable capacity using additive white gaussian noise (AWGN) channel. Moreover, we compare the BER and signal-to-noise ratio (SNR) per bit for two users, showing that the Rician fading channel performs better than the Rayleigh fading channel. The use of NOMA technology is the optimal choice and indicates an improvement in the precision of data transmission within the communication system, particularly in the presence of noise and interference. Creator An entity primarily responsible for making the resource Abdelbari Falloun, Abdessalam Ait Madi 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 Nov 16, 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/b8c8f55af849f47e54a3ebeec0ff1a29.pdf 7c5313c8e5bbf64f97930b261e57e99a 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. 23, NO.1 2025 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 PV solar anomaly detection using low-cost data logger and ANN algorithm Subject The topic of the resource Artificial intelligence Edge device Energy management system Energy monitoring Predictive maintenance Renewable energy Solar energy Description An account of the resource This paper presents an innovative edge device architecture that significantly enhances solar energy management systems. By integrating advanced functionalities such as generation prediction, maintenance alerts, and solar anomaly detection, this architecture transforms solar energy management. Through edge computing, it enables real-time analysis and decision-making at the network edge. Leveraging machine learning algorithms and accurate predictive models, these edge devices provide precise energy generation forecasts, facilitating optimal energy utilization and strategic planning for stakeholders. Additionally, the architecture incorporates anomaly detection techniques to proactively identify deviations from normal operation, minimizing downtime, and enabling timely maintenance. This approach ensures uninterrupted energy generation, enhancing the reliability and efficiency of the entire monitoring system. The integration of these features within edge devices improves the performance and reliability of energy monitoring systems. Implementing this cutting-edge architecture empowers stakeholders to achieve superior energy management, substantial cost reductions, and unparalleled system reliability. Creator An entity primarily responsible for making the resource Younes Ledmaoui1, Adila El Maghraoui2, Mohamed El Aroussi1, Rachid Saadane1, Abdellah Chehri3, Ahmed Chebak2 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 Nov 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 Artificial intelligence Edge device Energy management system Energy monitoring Predictive maintenance Renewable energy Solar energy