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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Reagentless iron detection in water based on unclad fiber optical sensor</text>
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                <text>Fiber optical sensor&#13;
Iron detection&#13;
Unclad fiber</text>
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                <text>A simple and low-cost fiber based optical sensor for iron detection is&#13;
demonstrated in this paper. The sensor head consist of an unclad optical&#13;
fiber with the unclad length of 1 cm and it has a straight structure. Results&#13;
obtained shows a linear relationship between the output light intensity and&#13;
iron concentration, illustrating the functionality of this iron optical sensor.&#13;
Based on the experimental results, the sensitivity and linearity are achieved&#13;
at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With&#13;
the same wavelength, other performance parameters are also studied.&#13;
Resolution and limit of detection (LOD) are found to be 0.3049 ppm and&#13;
0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not&#13;
require any reagent for detection, enabling it to be simpler and cost-effective in&#13;
the implementation of the iron sensing.</text>
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                <text>Nurul Atika Nabila Jaharudin, Noran Azizan Cholan, Nurfatihah Che Abd Rashid, Nazrah Ilyana Sulaiman, Kim Gaik Tay, Nor Hafizah Ngajikin</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Intrusion detection system for imbalance ratio class using weighted XGBoost classifier</text>
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                <text>Imbalanced ratio class&#13;
Intrusion detection&#13;
Weighted XGBoost</text>
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                <text>The rapid development of the internet of things (IoT) has taken an important&#13;
role in daily activities. As it develops, IoT is very vulnerable to attacks and&#13;
creates IoT for users. Intrusion detection system (IDS) can work efficiently&#13;
and look for activity in the network. Many data sets have already been&#13;
collected, however, when dealing with problems involving big data and&#13;
hight data imbalances. This article proposes, using the dataset used by&#13;
BotIoT to evaluate the system framework to be created, the XGBoost model&#13;
to improve the detection performance of all types of attacks, to control&#13;
unbalanced data using the imbalance ratio of each class weight (CW).&#13;
The experimental results show that the proposed approach greatly increases&#13;
the detection rate for infrequent disturbances.</text>
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                <text>Januar Al Amien, Hadhrami Ab Ghani, Nurul Izrin Md Saleh, Edi Ismanto, Rahmad Gunawan</text>
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                  <text>VOL. 21, NO. 5 2023</text>
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Design and implementation of a LoRa-based system for warning of forest fire</text>
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                <text>Forest fire&#13;
Infrared photos&#13;
Internet of things&#13;
LoRa technology&#13;
Wireless sensor networks</text>
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                <text>This paper presents the design and implementation of a forest fire monitoring&#13;
and warning system based on long range (LoRa) technology, a novel ultra-low&#13;
power consumption and long-range wireless communication technology for&#13;
remote sensing applications. The proposed system includes a wireless sensor&#13;
network that records environmental parameters such as temperature,&#13;
humidity, wind speed, and carbon dioxide (CO2) concentration in the air,&#13;
as well as taking infrared photos. The data collected at each sensor node will&#13;
be transmitted to the gateway via LoRa wireless transmission. Data will be&#13;
collected, processed, and uploaded to a cloud database at the gateway.&#13;
An Android smartphone application that allows anyone to easily view the&#13;
recorded data has been developed. When a fire is detected, the system will&#13;
sound a siren and send a warning message to the responsible personnel,&#13;
instructing them to take appropriate action. Experiments in Tram Chim Park,&#13;
Vietnam, have been conducted to verify and evaluate the operation of the&#13;
system.</text>
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                <text>Tuyen Phong Truong, Quang Thien Tran, Phat Tan Le</text>
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                <text>http://telkomnika.uad.ac.id</text>
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                <text>Apr 30, 2023</text>
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                <text>peri irawan</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Blockchain-IoT supply chain: systematic literature review</text>
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                <text>Authentication&#13;
Blockchain&#13;
IoT&#13;
Supply chain</text>
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                <text>Since 2016, the implementation of blockchain in the supply chain has attracted&#13;
wide interest among researchers. The creation and study of blockchain&#13;
technology have grown at an exponential rate in the last decade. The supply&#13;
chain would be a massive technological leap with the combination of&#13;
blockchain technology that brings major changes to different facets of the&#13;
industry, such as record immutability, improved traceability, quality&#13;
assurance, improved knowledge flows, decentralized power structure, and&#13;
decreased chances of fraud. With the growth in blockchain Internet-of-Thing&#13;
(IoT) supply chain technologies, the security risk of implementing such&#13;
technologies and methods to counter it has been largely discussed among&#13;
researchers. This study analyses peer-reviewed literature attempting to use&#13;
authentication in the blockchain-IoT supply chain to counter security risks in&#13;
the technologies and provides a comprehensive analysis of the important&#13;
feature when creating an authentication technique for the blockchain-IoT&#13;
supply chain. Finally, the study discusses some of the problems and research&#13;
objectives in the realm of authentication in the blockchain-IoT supply chain.</text>
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                <text>Umi Nabilah Badrol Said, Mohd Rizuan Baharon, Mohd Zaki Mas’ud, Ariff Idris, Noor Azurati Ahmad Salleh</text>
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                <text>peri irawan</text>
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Wavelet-based sensing technique in cognitive radio network</text>
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                <text>Cognitive radio&#13;
Empirical data&#13;
Spectrum holes&#13;
Spectrum sensing&#13;
Wavelet detection</text>
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                <text>Cognitive radio is a smart radio that can change its transmitter parameter&#13;
based on interaction with the environment in which it operates. The demand&#13;
for frequency spectrum is growing due to a big data issue as many Internet&#13;
of Things (IoT) devices are in the network. Based on previous research, most&#13;
frequency spectrum was used, but some spectrums were not used, called&#13;
spectrum hole. Energy detection is one of the spectrum sensing methods that&#13;
has been frequently used since it is easy to use and does not require license&#13;
users to have any prior signal understanding. But this technique is incapable&#13;
of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the&#13;
wavelet-based sensing is proposed to overcome this issue and detect&#13;
spectrum holes. The main objective of this work is to evaluate the&#13;
performance of wavelet-based sensing and compare it with the energy&#13;
detection technique. The findings show that the percentage of detection in&#13;
wavelet-based sensing is 83% higher than energy detection performance.&#13;
This result indicates that the wavelet-based sensing has higher precision in&#13;
detection and the interference towards primary user can be decreased.</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Conceptual model of internet banking adoption with perceived risk and trust factors</text>
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                <text>Internet banking&#13;
Perceived risk&#13;
Technology acceptance model&#13;
Technology adoption&#13;
Trust</text>
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                <text>Understanding the primary factors of internet banking (IB) acceptance is&#13;
critical for both banks and users; nevertheless, our knowledge of the role of&#13;
users’ perceived risk and trust in IB adoption is limited. As a result, we&#13;
develop a conceptual model by incorporating perceived risk and trust into&#13;
the technology acceptance model (TAM) theory toward the IB. The proper&#13;
research emphasized that the most essential component in explaining IB&#13;
adoption behavior is behavioral intention to use IB adoption. TAM is helpful&#13;
for figuring out how elements that affect IB adoption are connected to one&#13;
another. According to previous literature on IB and the use of such&#13;
technology in Iraq, one has to choose a theoretical foundation that may&#13;
justify the acceptance of IB from the customer’s perspective. The conceptual&#13;
model was therefore constructed using the TAM as a foundation.&#13;
Furthermore, perceived risk and trust were added to the TAM dimensions as&#13;
external factors. The key objective of this work was to extend the TAM to&#13;
construct a conceptual model for IB adoption and to get sufficient theoretical&#13;
support from the existing literature for the essential elements and their&#13;
relationships in order to unearth new insights about factors responsible for&#13;
IB adoption.</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
A progressive learning for structural tolerance online sequential extreme learning machine</text>
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                <text>Extreme learning machine&#13;
Progressive learning&#13;
Sequential learning&#13;
Stable sequential learning</text>
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                <text>This article discusses the progressive learning for structural tolerance online&#13;
sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save&#13;
robust accuracy while updating the new data and the new class data on the online&#13;
training situation. The robustness accuracy arises from using the householder&#13;
block exact QR decomposition recursive least squares (HBQRD-RLS) of the&#13;
PSTOS-ELM. This method is suitable for applications that have data&#13;
streaming and often have new class data. Our experiment compares the&#13;
PSTOS-ELM accuracy and accuracy robustness while data is updating with&#13;
the batch-extreme learning machine (ELM) and structural tolerance online&#13;
sequential extreme learning machine (STOS-ELM) that both must retrain the&#13;
data in a new class data case. The experimental results show that PSTOS-ELM&#13;
has accuracy and robustness comparable to ELM and STOS-ELM while also&#13;
can update new class data immediately.</text>
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                <text>Sarutte Atsawaraungsuk, Wasaya Boonphairote, Kritsanapong Somsuk, Chanwit Suwannapong, Suchart Khummanee</text>
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                <text>http://telkomnika.uad.ac.id</text>
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                <text>peri irawan</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
ResNet-n/DR: Automated diagnosis of diabetic retinopathy using a residual neural network</text>
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                <text>Convolutional neural networks&#13;
Deep learning&#13;
Diabetic retinopathy&#13;
Residual neural network</text>
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                <text>Diabetic retinopathy (DR) is a progressive eye disease associated with&#13;
diabetes, resulting in blindness or blurred vision. The risk of vision loss was&#13;
dramatically decreased with early diagnosis and treatment. Doctors diagnose&#13;
DR by examining the fundus retinal images to develop lesions associated with&#13;
the disease. However, this diagnosis is a tedious and challenging task due to&#13;
growing undiagnosed and untreated DR cases and the variability of retinal&#13;
changes across disease stages. Manually analyzing the images has become an&#13;
expensive and time-consuming task, not to mention that training new&#13;
specialists takes time and requires daily practice. Our work investigates deep&#13;
learning methods, particularly convolutional neural network (CNN), for DR&#13;
diagnosis in the disease’s five stages. A pre-trained residual neural network&#13;
(ResNet-34) was trained and tested for DR. Then, we develop computationally&#13;
efficient and scalable methods after modifying a ResNet-34 with three additional&#13;
residual units as a novel ResNet-n/DR. The Asia Pacific Tele-Ophthalmology&#13;
Society (APTOS) 2019 dataset was used to evaluate the performance of&#13;
models after applying multiple pre-processing steps to eliminate image noise&#13;
and improve color contrast, thereby increasing efficiency. Our findings&#13;
achieved state-of-the-art results compared to previous studies that used the&#13;
same dataset. It had 90.7% sensitivity, 93.5% accuracy, 98.2% specificity,&#13;
89.5% precision, and 90.1% F1 score.</text>
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                <text>Noor M. Al-Moosawi, Raidah S. Khudeyer</text>
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                <text>http://telkomnika.uad.ac.id</text>
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                  <text>VOL. 21, NO. 5 2023</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Efficient combined fuzzy logic and LMS algorithm for smart antenna</text>
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                <text>Fuzzy logic&#13;
LMS algorithm&#13;
Smart antenna</text>
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            <description>An account of the resource</description>
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                <text>The smart antennas are broadly used in wireless communication. The least&#13;
mean square (LMS) algorithm is a procedure that is concerned in controlling&#13;
the smart antenna pattern to accommodate specified requirements such as&#13;
steering the beam toward the desired signal, in addition to placing the deep&#13;
nulls in the direction of unwanted signals. The conventional LMS (C-LMS)&#13;
has some drawbacks like slow convergence speed besides high steady state&#13;
fluctuation error. To overcome these shortcomings, the present paper adopts&#13;
an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to&#13;
adjust its step size. Computer simulation outcomes illustrate that the given&#13;
model has fast convergence rate as well as low mean square error steady state.</text>
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                <text>Mohammed Hussein Miry, Ali Hussien Mary</text>
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                <text>http://telkomnika.uad.ac.id</text>
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                <text>peri irawan</text>
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                  <text>VOL. 21, NO. 5 2023</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Implementation of FinFET technology based low power 4×4 Wallace tree multiplier using hybrid full adder</text>
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                <text>Binary to excess -1 convertor&#13;
Energy delay product&#13;
First zero finding logic&#13;
Low-power multiplier&#13;
Power delay product</text>
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                <text>Many systems, including digital signal processors, finite impulse response&#13;
(FIR) filters, application-specific integrated circuits, and microprocessors,&#13;
use multipliers. The demand for low power multipliers is gradually rising&#13;
day by day in the current technological trend. In this study, we describe a&#13;
4×4 Wallace multiplier based on a carry select adder (CSA) that uses less&#13;
power and has a better power delay product than existing multipliers.&#13;
HSPICE tool at 16 nm technology is used to simulate the results.&#13;
In comparison to the traditional CSA-based multiplier, which has a power&#13;
consumption of 1.7 μW and power delay product (PDP) of 57.3 fJ,&#13;
the results demonstrate that the Wallace multiplier design employing CSA&#13;
with first zero finding logic (FZF) logic has the lowest power consumption&#13;
of 1.4 μW and PDP of 27.5 fJ.</text>
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                <text>Shikha Singh, Yagnesh B. Shukla</text>
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