TELKOMNIKA JOURNAL | Ahmad Dahlan University (original) (raw)

Papers by TELKOMNIKA JOURNAL

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

The growing popularity of chip-based devices has spurred interest in developing on-chip antennas ... more The growing popularity of chip-based devices has spurred interest in developing on-chip antennas (OCAs). However, low gain and poor radiation characteristics have been significant challenges. Integrating an artificial magnetic conductor (AMC) into the oxide layer is an alternative. This article presents a new AMC model that improves the performance of 28 GHz OCA using dual-rectangular-patch (DRP) as unit cells. The DRP parameters, patch width (Pw), patch gap (Pg), and substrate height (hs) were used to control the AMC characteristic. Two numerical equations for gain (G) and efficiency (η) have been developed to evaluate the new model’s performance. The impact of parameters on the antenna’s gain and radiation efficiency was equally analyzed. A prototype antenna was fabricated and tested to validate the model. It demonstrated a peak gain of 3.69 dB and radiation efficiency of 67.18%, with an achieved impedance bandwidth of 1.27 GHz, making it well-suited for 28 GHz device applications. Furthermore, the equations formulated provide the research community with a straightforward method to calculate the gain and efficiency of a 28 GHz antenna. This method is not limited to OCA but can also be applied to off-chip antennas if DRP-AMC is implemented.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Grid-integrated photovoltaic (PV)systems are currently undergoing explosive growth in Malaysia. H... more Grid-integrated photovoltaic (PV)systems are currently undergoing explosive growth in Malaysia. However, as more PV systems are installed close to transmission lines, there are concerns about the impact of electromagnetic (EM) properties affecting the performance and operation of the PV systems if they are exposed to lightning strikes, particularly indirect ones. Therefore, this study aims to model the impact of indirect lightning strikes on PV systems installed in proximity to transmission lines. The model involves developing a 3D model of the PV system together with a sample transmission line and creating an artificial lightning event to study the EM activity within the area. The results are compared to the IEC 61000 standard to determine its level of r\hazard. From the simulation results, it was found that the current intensity, H, of the disturbance, can reach up to 63% more than the standard limit stipulated in the standards. The significance of the study ensures that PV systems installed within the vicinity of power lines or substations have adequate lightning protection systems (LPS) as well as proper earthing systems.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This paper investigates the effectiveness of traditional machine learning techniques, namely line... more This paper investigates the effectiveness of traditional machine learning techniques, namely linear regression and random forest (RF), in enhancing the detection of money laundering (ML) activities within financial systems. As ML schemes evolve in complexity, traditional rule-based methods struggle with high false favorable rates and a lack of adaptability, prompting the need for more sophisticated analytical approaches. In contrast to the complexities of deep learning models, this study explores the potential of these more accessible machine learning methods in identifying and analyzing suspicious transactional patterns. We apply linear regression and RF models to transactional data to detect anomalous activities that could indicate ML. Our research thoroughly compares these models based on key performance metrics such as accuracy, precision, and recall. The findings suggest that while less complex than deep learning frameworks, linear regression, and RF models offer substantial benefits. They provide a more streamlined, interpretable, and efficient alternative to conventional rule-based systems in the context of ML detection. This study contributes to the ongoing discourse on the application of machine learning in financial crime detection, demonstrating the practicality and effectiveness of these methods in a critical area of financial security

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Constant current-constant voltage (CC-CV) is one of the battery charging methods that is commonly... more Constant current-constant voltage (CC-CV) is one of the battery charging methods that is commonly used. However, this method has several drawbacks, including the charging current in constant current (CC) mode, which can only be set to a maximum of 0.3 C on lead acid batteries, resulting in a relatively long charging duration. Therefore, in this research, the multi-step constant current-constant voltage (MCC-CV) method of battery charging system is developed where this method can use a greater charging current, resulting in a significant reduction in charging duration by using multiple current setpoints in MCC mode, with the initial setpoint current can be set beyond 0.3 C, which is 0.34 C in this system. This system uses a DC-DC single-ended primary inductance converter (SEPIC) converter as a battery charging control system, equipped with a power cut-off relay when the charging current reaches 0.05 C in constant voltage (CV) mode. From the test results obtained, the MCC-CV method can charge the battery to its full capacity faster than the CC-CV method with a difference of 15.34 minutes and the relay on the system can work properly.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This article presents the design of an active down-conversion mixer for the superheterodyne recei... more This article presents the design of an active down-conversion mixer for the superheterodyne receiver system for 6G wireless communications. This mixer is developed based on the Gilbert cell in the terahertz frequency band, using the 𝑃𝐻15 transistor from United Monolithic Semiconductors (UMS) Foundry in monolithic microwave integrated circuit (MMIC) technology. We used the charge injection method to increase our mixer’s conversion gain. In addition, we integrated a buffer stage at the mixer outputs to facilitate impedance matching and improve linearity. The power dividers used in this chapter are based on transmission lines from Agilent's advanced design system (ADS) tool, connected to the input and output ports of the circuit. The proposed architecture offers a high conversion gain of 15.2 dB, with a low local oscillator (LO) power of 0 dBm, a low double sideband (DSB) noise figure (NF) of around 7.1 dB, a 1 𝑑𝐵 compression point of -16 dBm, and good radio frequency (𝑅𝐹) − 𝐿𝑂 port isolation of 63.2 dB, at a RF of 0.14 THz.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Biomedical antennas play a crucial role in implantable medical telemetry, improving patient monit... more Biomedical antennas play a crucial role in implantable medical telemetry, improving patient monitoring and overall well-being. This study presents a compact antenna designed for a lead-free pacemaker, with dimensions of 3.3×4×0.5 mm³. Miniaturization required open cuts in the ground plane and radiating patch, as well as a localized resistance element. The antenna features an exceptional bandwidth of 1646.8 MHz (1.0602-2.7070) GHz, guaranteeing constant performance in the human body. It covers the industrial, scientific and medical bands (ISM, 2.4-2.48 GHz) and ultra-high frequencies (UHF, 0.3-13 GHz). Simulation in a phantom produced a gain of -19.78 dBi at 2.45 GHz and -34.44 dBi at 1.2 GHz. Safety was confirmed by a specific absorption rate (SAR) study using a cardiac model. The antenna’s low SAR (10 g-Avg) enabled maximum input powers to be established: 20.2 mW at 1.2 GHz and 21.23 mW at 2.45 GHz. Comparative simulations using high-frequency structure simulator (HFSS) and computer simulation technology (CST) highlighted the antenna’s superiority over recent systems, demonstrating its effectiveness in the human heart. This antenna represents an advanced solution for improving patient care. Consequently, this antenna emerges as an advanced solution for addressing infectious diseases and cardiovascular conditions in the realm of medical advancements.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Image encryption is a critical process aimed at securing digital images, safeguarding them from u... more Image encryption is a critical process aimed at securing digital images, safeguarding them from unauthorized access, tampering, or viewing to ensure the confidentiality and integrity of sensitive visual information. In this research, we integrate polynomial Chebyshev, fractal Tromino, and substitution S-box methods into a comprehensive image encryption approach. Our evaluation focuses on standardized 256×256-pixel images of Lena, Peppers, and Baboon, assessing key performance metrics like mean squared error (MSE), peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel changes rate (NPCR), and entropy. The results reveal varying encryption quality across images, with Lena exhibiting the highest MSE (4702) and the lowest PSNR (12.89 dB). However, UACI, NPCR, and entropy values remain consistent across all images, indicating the proposed method’s stability concerning changing intensity, pixel alterations, and entropy levels. These findings contribute valuable insights into the effectiveness of the proposed encryption method, providing a foundation for further exploration and optimization in the field of cryptographic research. For future research direction, it is recommended to explore the impact of varying image sizes and types on the proposed method’s performance. Additionally, by focusing on the area of cryptographic threats, further analysis of the algorithm’s resistance against advanced attacks and its computational efficiency would be beneficial.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Image encryption is a vital field ensuring the secure transmission of digital images. In this stu... more Image encryption is a vital field ensuring the secure transmission of digital images. In this study, encryption is the core process, employing complex mathematical algorithms and cryptographic keys to transform the original image into a secure format, shielding visual data from unauthorized access during transmission. To enhance security, the research integrates Fibonacci and advanced encryption standard (AES)–least significant bit (LSB) methodologies for a complex key generation system. This mechanism introduces intricate transformations within the image data, creating patterns challenging for potential attackers to decipher. Evaluation of the algorithm’s performance reveals efficiency in terms of mean squared error (MSE) and peak signal-to-noise ratio (PSNR). The RGB cover image achieves the lowest MSE of 0.0001 and the highest PSNR values ranging from 44.31 to 49.27. Integration of the Fibonacci sequence notably improves visual quality, enhancing both MSE and PSNR metrics. Unified average changing intensity (UACI) and normalized pixel change rate (NPCR) assessments consistently show the effectiveness of the algorithm, with the RGB cover image presenting the highest UACI and NPCR values. Future research directions involve exploring advanced encryption algorithms, optimizing techniques for highdimensional datasets, and addressing ethical implications in image encryption, contributing to the development of adaptable and secure solutions.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Clouds play a crucial role in precipitation and weather prediction. Identifying and differentiati... more Clouds play a crucial role in precipitation and weather prediction. Identifying and differentiating clouds accurately poses a significant challenge. In this paper, we present a novel approach that utilizes the local binary patterns (LBP) feature descriptor to extract color cloud images. We employ feature fusion to combine LBP features from the independent channels of the RGB color space. Furthermore, we apply five well-known feature selection methods, namely ReliefF, Ilfs, correlation-based feature selection (CFS), Fisher, and Lasso, to select relevant and useful features. These selected features are then fed into a support vector machine (SVM) classifier. Experimental results demonstrate that our proposed approach achieves superior performance by significantly reducing the number of features while maintaining prediction accuracy.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Potato (Solanum tuberosum L.) is a key crop and a major source of livelihood for a vast populatio... more Potato (Solanum tuberosum L.) is a key crop and a major source of livelihood for a vast population of the world after wheat and rice. However, diseases have diverse effects on potato fields, leading to damage to crops and reducing crop production. The two major diseases that afflict potato plants are referred to as early blight and late blight. Protection of this crop yield from blight diseases is one of the foremost challenges. Therefore, detection of these leaf diseases at appropriate time is very essential to prevent the damage. This study intends an internet of things (IoT)-based smart potato leaf diseases monitoring and control system that combines IoT technology with eco-sensing and image processing to identify and categorize these diseases. Studies have found that blight diseases are directly related to temperature and humidity of the planted area. This study measures environmental information using a sensor network installed in the planted area. After sensing and measuring environmental information, acquired values are displayed and farmers get these acquired values via message notification. The system obtains a 97% accuracy rate in recognizing these diseases by using our fine-tuned model of ResNet-50 for image processing.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Modern aeroponic systems leverage internet of things (IoT) technology for automated control of cl... more Modern aeroponic systems leverage internet of things (IoT) technology for automated control of climate, lighting, and nutrient delivery, rendering them susceptible to unauthorized access and network attacks. Such disruptions can lead to financial losses and impair agricultural productivity by altering essential growth conditions. To mitigate these risks, robust security measures including encryption and firewalls are essential, alongside continuous monitoring and updates to combat evolving threats. Addressing cyber threats in urban aeroponic systems, implementing quantum encryption emerges as a promising solution. Quantum key distribution (QKD) ensures highly secure encryption keys using quantum states that change upon eavesdropping, thereby thwarting intrusion attempts effectively. Integrating quantum encryption in aeroponic control systems safeguards data integrity and operational continuity against cyber threats, bolstering urban agriculture resilience. Our findings demonstrate the efficacy of quantum BB84 protocol integrated with application programming interface (API) for Eve’s security. Quantum bit error rate (QBER) measurements revealed minimal interference (0.015) for Alice and Bob, contrasting with higher initial QBER (up to 1.0) for Eve, indicative of intrusion attempts. Histogram analysis further underscored quantum security’s effectiveness in identifying and mitigating breaches. For future research, enhancing quantum encryption protocols and integrating advanced detection mechanisms will be essential.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Each and every living thing needs fresh water to survive. Fresh water is becoming a precious reso... more Each and every living thing needs fresh water to survive. Fresh water is becoming a precious resource as a result of the combined risks of rapid urbanization, pollution, and climatic changes. The quality of the water we drink every day has an impact on our lives, either directly or indirectly. Maintaining the sustainability and health of the environment requires constant attention to water quality. Modern technology makes it possible to gather and analyze data from water distribution networks in order to maximize resources and enhance decision-making for all parties. Despite the enormous global growth of the internet of things (IoT) and blockchain in recent years, their integration is still in its early stages. In this research contains a technological framework that combines blockchain and IoT called B-IoT and aims to reward and incentivize more sustainable water quality management with real-time monitoring and security. IoT is used to monitor water quality in water resources and find any violations. By using blockchain, it is possible to retain the accuracy, reliability, and transparency of the records of breaches. This system will be able to gauge the water’s quality in real-time and allow for the quick identification of any infractions necessary to commit the crime.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This study provides a systematic review of the literature on the fourth industrial revolution (IR... more This study provides a systematic review of the literature on the fourth industrial revolution (IR4.0) and the internet of things (IoT) in genetics, informatics, and biotechnology, as well as their many rapidly evolving applications, which often overlap with various aspects of life. The study reviews the latest research, books, scientific theses, and official websites in this field, placing them in a coherent context for researchers. It covers innovations that have driven the continuous development of IR4.0 and its challenges. The study highlights numerous fields and modern technologies expected to bring about tangible and radical changes in health, agriculture, and industry. It addresses key aspects of IR4.0 and the significant advancements brought by smart cities, and most importantly, artificial intelligence (AI), including robots, autonomous cars, 3D printing, big data, IoT, nanotechnology, biotechnology, energy storage, and quantum computing. By applying cutting-edge technology across various disciplines to boost productivity and foster development, technology plays a crucial role in linking the physical, digital, and biological realms. This revolution is built on multiple axes, including the convergence of biotechnology, digital media, and physical systems.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Normal people’s interaction and communication are easier than those with disabilities such as he... more Normal people’s interaction and communication are easier than those with disabilities such as hearing and speech, which are very complicated; hence, the use of sign language plays a crucial role in bridging this gap in communication. While previous attempts have been made to solve this problem using deep learning techniques, including convolutional neural networks (CNNs), support vector machine (SVM), and K-nearest neighbours (KNN), these have low accuracy or may not be employed in real time. This work addresses both issues: improving upon prior limitations and extending the challenge of classifying characters in Indian sign language (ISL). Our system, which can recognize 23 hand gestures of ISL through a purely camera-based approach, eliminates expensive hardware like hand gloves, thus making it economical. The system yields an accuracy of 97.5% on the training dataset, utilizing a pre-trained VGG16 CNN optimized by the Adam optimizer and cross-entropy loss function. These results clearly show how effective transfer learning is in classifying ISL and its possible real-world applications.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

In the highly competitive landscape of Malaysian internet service providers (ISPs), users seek ef... more In the highly competitive landscape of Malaysian internet service providers (ISPs), users seek efficient ways to assess service quality. While various websites allow visual comparisons of fiber ISPs, a direct side-by-side evaluation remains elusive. A survey of 101 respondents revealed that 92.1% found researching a company’s reputation time-consuming. Additionally, relying on English-centric online ratings may lead to skewed outcomes, disregarding reviews in diverse languages. In response, we developed a webbased dashboard utilizing Twitter sentiment analysis (SA) and the naïve Bayes (NB) algorithm to classify Malaysia’s best fiber ISPs. The SA focused on four key factors: package price, internet speed, coverage area, and customer service, simplifying the comparison process. The system’s usability and functionality tests showed that both the English and Malay models could classify scraped Twitter data with an accuracy of 80%. The system’s remarkable usability score of 94.58% on the system usability scale (SUS) confirms its acceptability and excellent performance in achieving research goals.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Life test data analysis is a statistical method used to analyze time data until a certain event o... more Life test data analysis is a statistical method used to analyze time data until a certain event occurs. If the life test data is produced after the experiment has been running for a set amount of time, the life time data may be type I censored data. When conducting observations for survival analysis, it is anticipated that the data would conform to a specific probability distribution. Meanwhile, to determine the characteristics of a population, parameter estimation is carried out. The purpose of this study is to use the linear exponential loss function method to derive parameter estimators from the exponential distribution of two parameters on type I censored data. The prior distribution used is a non-informative prior with the determination technique using the Jeffrey’s method. Based on the research results that have been obtained, application is carried out on real data. This data is data on the length of time employees have worked before they experienced attrition with a censorship limit based on age, namely 58 years, obtained from the Kaggle.com website. Based on the estimation results, the average length of work for employees is 6.29427 years. This shows that employees tend to experience attrition after working for a relatively long period of time.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Floods damage ecosystem of the affected area resulting in destruction, loss of asset and life. Th... more Floods damage ecosystem of the affected area resulting in destruction, loss of asset and life. The paper proposes a novel k-FVI, (k stands for Kerala and FVI for flood vulnerability index) to aid the decision makers reduce flood vulnerability of 14 districts of Kerala. Instead of usual classification of flood vulnerability indicators under exposure (𝔼), sensitivity (𝕊), and adaptive capacity (𝔸ℂ), k-FVI proposes that, indicators reflecting 𝕊 and preparedness (ℙ) govern pre-flood vulnerability, whereas those of 𝔼 and rehabilitation (ℝ) affects post-flood vulnerability. The division of 𝔸ℂ indicator into ℙ and ℝ indicators and clubbing them into pre-flood and post-flood vulnerability respectively results into reduced errors. The importance of high dimensional flood indicators is realized by measuring the entropy of affected areas. Use of technique for order preference by similarity to ideal solution (TOPSIS) and entropy-based weights to score flood affected area results in formulating robust k-FVI. The paper also compares k-FVI with existing FVIs in literature. It uses data of 2018 Kerala floods and assesses the flood vulnerability of its 14 districts. The results prove that k-FVI is an effective flood vulnerability score estimator. Variant of k-FVI can be used to obtain vulnerability for any other flood prone areas.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

The objective of this paper is to detect tomato leaf disease using Faster region-based convolutio... more The objective of this paper is to detect tomato leaf disease using Faster region-based convolutional neural network (R-CNN). The tomato leaf disease recognition system utilizes a dataset consisting of healthy tomato leaves and eight leaf diseases, including early blight, late blight, leaf mold, mosaic virus, septoria, spider mites, yellow leaf curl virus, and leaf miner. The dataset is obtained from various sources, such as Kaggle, Google Images, Bing Images, and Roboflow Universe. Pre-processing techniques, including collage, tile, static crop, and resize, are applied to prepare the dataset for training. Data augmentation methods, such as flipping, 90° rotation, exposure adjustment, and hue modification, are applied to enhance the model’s robustness and generalize its performance. Specifically, we implemented Faster R-CNN as part of Detectron2 using its base models and configurations. The results demonstrate that the X101-FPN base model for Faster R-CNN with the default configurations of Detectron2 is efficient and general enough to be applied to defect detection. This approach results in an average precision (AP) detection score of 87.01% for validation results.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Illegal, unreported, and unregulated (IUU) fishing poses a significant threat by depleting fish s... more Illegal, unreported, and unregulated (IUU) fishing poses a significant threat by depleting fish stocks, damaging marine ecosystems, jeopardizing economic livelihoods, and undermining long-term environmental sustainability. To address this, the government has implemented a public policy of measured fishing within the blue economy framework. Given the involvement of numerous stakeholders, it is crucial for the government to gauge public sentiment through tweets on social media platforms to evaluate and refine the policy’s implementation for greater effectiveness. While the long short-term memory (LSTM) method for sentiment analysis is adept at handling text sequences and context, it struggles with capturing contextual semantic correlations. Conversely, the latent Dirichlet allocation (LDA) method excels in identifying these correlations and uncovering dominant topics. This study shows that integrating LDA for topic modeling with LSTM for sentiment analysis enhances overall performance, providing more accurate and comprehensive insights into public responses and identifying key topics discussed in social media tweets.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

The growing popularity of chip-based devices has spurred interest in developing on-chip antennas ... more The growing popularity of chip-based devices has spurred interest in developing on-chip antennas (OCAs). However, low gain and poor radiation characteristics have been significant challenges. Integrating an artificial magnetic conductor (AMC) into the oxide layer is an alternative. This article presents a new AMC model that improves the performance of 28 GHz OCA using dual-rectangular-patch (DRP) as unit cells. The DRP parameters, patch width (Pw), patch gap (Pg), and substrate height (hs) were used to control the AMC characteristic. Two numerical equations for gain (G) and efficiency (η) have been developed to evaluate the new model’s performance. The impact of parameters on the antenna’s gain and radiation efficiency was equally analyzed. A prototype antenna was fabricated and tested to validate the model. It demonstrated a peak gain of 3.69 dB and radiation efficiency of 67.18%, with an achieved impedance bandwidth of 1.27 GHz, making it well-suited for 28 GHz device applications. Furthermore, the equations formulated provide the research community with a straightforward method to calculate the gain and efficiency of a 28 GHz antenna. This method is not limited to OCA but can also be applied to off-chip antennas if DRP-AMC is implemented.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Grid-integrated photovoltaic (PV)systems are currently undergoing explosive growth in Malaysia. H... more Grid-integrated photovoltaic (PV)systems are currently undergoing explosive growth in Malaysia. However, as more PV systems are installed close to transmission lines, there are concerns about the impact of electromagnetic (EM) properties affecting the performance and operation of the PV systems if they are exposed to lightning strikes, particularly indirect ones. Therefore, this study aims to model the impact of indirect lightning strikes on PV systems installed in proximity to transmission lines. The model involves developing a 3D model of the PV system together with a sample transmission line and creating an artificial lightning event to study the EM activity within the area. The results are compared to the IEC 61000 standard to determine its level of r\hazard. From the simulation results, it was found that the current intensity, H, of the disturbance, can reach up to 63% more than the standard limit stipulated in the standards. The significance of the study ensures that PV systems installed within the vicinity of power lines or substations have adequate lightning protection systems (LPS) as well as proper earthing systems.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This paper investigates the effectiveness of traditional machine learning techniques, namely line... more This paper investigates the effectiveness of traditional machine learning techniques, namely linear regression and random forest (RF), in enhancing the detection of money laundering (ML) activities within financial systems. As ML schemes evolve in complexity, traditional rule-based methods struggle with high false favorable rates and a lack of adaptability, prompting the need for more sophisticated analytical approaches. In contrast to the complexities of deep learning models, this study explores the potential of these more accessible machine learning methods in identifying and analyzing suspicious transactional patterns. We apply linear regression and RF models to transactional data to detect anomalous activities that could indicate ML. Our research thoroughly compares these models based on key performance metrics such as accuracy, precision, and recall. The findings suggest that while less complex than deep learning frameworks, linear regression, and RF models offer substantial benefits. They provide a more streamlined, interpretable, and efficient alternative to conventional rule-based systems in the context of ML detection. This study contributes to the ongoing discourse on the application of machine learning in financial crime detection, demonstrating the practicality and effectiveness of these methods in a critical area of financial security

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Constant current-constant voltage (CC-CV) is one of the battery charging methods that is commonly... more Constant current-constant voltage (CC-CV) is one of the battery charging methods that is commonly used. However, this method has several drawbacks, including the charging current in constant current (CC) mode, which can only be set to a maximum of 0.3 C on lead acid batteries, resulting in a relatively long charging duration. Therefore, in this research, the multi-step constant current-constant voltage (MCC-CV) method of battery charging system is developed where this method can use a greater charging current, resulting in a significant reduction in charging duration by using multiple current setpoints in MCC mode, with the initial setpoint current can be set beyond 0.3 C, which is 0.34 C in this system. This system uses a DC-DC single-ended primary inductance converter (SEPIC) converter as a battery charging control system, equipped with a power cut-off relay when the charging current reaches 0.05 C in constant voltage (CV) mode. From the test results obtained, the MCC-CV method can charge the battery to its full capacity faster than the CC-CV method with a difference of 15.34 minutes and the relay on the system can work properly.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This article presents the design of an active down-conversion mixer for the superheterodyne recei... more This article presents the design of an active down-conversion mixer for the superheterodyne receiver system for 6G wireless communications. This mixer is developed based on the Gilbert cell in the terahertz frequency band, using the 𝑃𝐻15 transistor from United Monolithic Semiconductors (UMS) Foundry in monolithic microwave integrated circuit (MMIC) technology. We used the charge injection method to increase our mixer’s conversion gain. In addition, we integrated a buffer stage at the mixer outputs to facilitate impedance matching and improve linearity. The power dividers used in this chapter are based on transmission lines from Agilent's advanced design system (ADS) tool, connected to the input and output ports of the circuit. The proposed architecture offers a high conversion gain of 15.2 dB, with a low local oscillator (LO) power of 0 dBm, a low double sideband (DSB) noise figure (NF) of around 7.1 dB, a 1 𝑑𝐵 compression point of -16 dBm, and good radio frequency (𝑅𝐹) − 𝐿𝑂 port isolation of 63.2 dB, at a RF of 0.14 THz.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Biomedical antennas play a crucial role in implantable medical telemetry, improving patient monit... more Biomedical antennas play a crucial role in implantable medical telemetry, improving patient monitoring and overall well-being. This study presents a compact antenna designed for a lead-free pacemaker, with dimensions of 3.3×4×0.5 mm³. Miniaturization required open cuts in the ground plane and radiating patch, as well as a localized resistance element. The antenna features an exceptional bandwidth of 1646.8 MHz (1.0602-2.7070) GHz, guaranteeing constant performance in the human body. It covers the industrial, scientific and medical bands (ISM, 2.4-2.48 GHz) and ultra-high frequencies (UHF, 0.3-13 GHz). Simulation in a phantom produced a gain of -19.78 dBi at 2.45 GHz and -34.44 dBi at 1.2 GHz. Safety was confirmed by a specific absorption rate (SAR) study using a cardiac model. The antenna’s low SAR (10 g-Avg) enabled maximum input powers to be established: 20.2 mW at 1.2 GHz and 21.23 mW at 2.45 GHz. Comparative simulations using high-frequency structure simulator (HFSS) and computer simulation technology (CST) highlighted the antenna’s superiority over recent systems, demonstrating its effectiveness in the human heart. This antenna represents an advanced solution for improving patient care. Consequently, this antenna emerges as an advanced solution for addressing infectious diseases and cardiovascular conditions in the realm of medical advancements.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Image encryption is a critical process aimed at securing digital images, safeguarding them from u... more Image encryption is a critical process aimed at securing digital images, safeguarding them from unauthorized access, tampering, or viewing to ensure the confidentiality and integrity of sensitive visual information. In this research, we integrate polynomial Chebyshev, fractal Tromino, and substitution S-box methods into a comprehensive image encryption approach. Our evaluation focuses on standardized 256×256-pixel images of Lena, Peppers, and Baboon, assessing key performance metrics like mean squared error (MSE), peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel changes rate (NPCR), and entropy. The results reveal varying encryption quality across images, with Lena exhibiting the highest MSE (4702) and the lowest PSNR (12.89 dB). However, UACI, NPCR, and entropy values remain consistent across all images, indicating the proposed method’s stability concerning changing intensity, pixel alterations, and entropy levels. These findings contribute valuable insights into the effectiveness of the proposed encryption method, providing a foundation for further exploration and optimization in the field of cryptographic research. For future research direction, it is recommended to explore the impact of varying image sizes and types on the proposed method’s performance. Additionally, by focusing on the area of cryptographic threats, further analysis of the algorithm’s resistance against advanced attacks and its computational efficiency would be beneficial.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Image encryption is a vital field ensuring the secure transmission of digital images. In this stu... more Image encryption is a vital field ensuring the secure transmission of digital images. In this study, encryption is the core process, employing complex mathematical algorithms and cryptographic keys to transform the original image into a secure format, shielding visual data from unauthorized access during transmission. To enhance security, the research integrates Fibonacci and advanced encryption standard (AES)–least significant bit (LSB) methodologies for a complex key generation system. This mechanism introduces intricate transformations within the image data, creating patterns challenging for potential attackers to decipher. Evaluation of the algorithm’s performance reveals efficiency in terms of mean squared error (MSE) and peak signal-to-noise ratio (PSNR). The RGB cover image achieves the lowest MSE of 0.0001 and the highest PSNR values ranging from 44.31 to 49.27. Integration of the Fibonacci sequence notably improves visual quality, enhancing both MSE and PSNR metrics. Unified average changing intensity (UACI) and normalized pixel change rate (NPCR) assessments consistently show the effectiveness of the algorithm, with the RGB cover image presenting the highest UACI and NPCR values. Future research directions involve exploring advanced encryption algorithms, optimizing techniques for highdimensional datasets, and addressing ethical implications in image encryption, contributing to the development of adaptable and secure solutions.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Clouds play a crucial role in precipitation and weather prediction. Identifying and differentiati... more Clouds play a crucial role in precipitation and weather prediction. Identifying and differentiating clouds accurately poses a significant challenge. In this paper, we present a novel approach that utilizes the local binary patterns (LBP) feature descriptor to extract color cloud images. We employ feature fusion to combine LBP features from the independent channels of the RGB color space. Furthermore, we apply five well-known feature selection methods, namely ReliefF, Ilfs, correlation-based feature selection (CFS), Fisher, and Lasso, to select relevant and useful features. These selected features are then fed into a support vector machine (SVM) classifier. Experimental results demonstrate that our proposed approach achieves superior performance by significantly reducing the number of features while maintaining prediction accuracy.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Potato (Solanum tuberosum L.) is a key crop and a major source of livelihood for a vast populatio... more Potato (Solanum tuberosum L.) is a key crop and a major source of livelihood for a vast population of the world after wheat and rice. However, diseases have diverse effects on potato fields, leading to damage to crops and reducing crop production. The two major diseases that afflict potato plants are referred to as early blight and late blight. Protection of this crop yield from blight diseases is one of the foremost challenges. Therefore, detection of these leaf diseases at appropriate time is very essential to prevent the damage. This study intends an internet of things (IoT)-based smart potato leaf diseases monitoring and control system that combines IoT technology with eco-sensing and image processing to identify and categorize these diseases. Studies have found that blight diseases are directly related to temperature and humidity of the planted area. This study measures environmental information using a sensor network installed in the planted area. After sensing and measuring environmental information, acquired values are displayed and farmers get these acquired values via message notification. The system obtains a 97% accuracy rate in recognizing these diseases by using our fine-tuned model of ResNet-50 for image processing.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Modern aeroponic systems leverage internet of things (IoT) technology for automated control of cl... more Modern aeroponic systems leverage internet of things (IoT) technology for automated control of climate, lighting, and nutrient delivery, rendering them susceptible to unauthorized access and network attacks. Such disruptions can lead to financial losses and impair agricultural productivity by altering essential growth conditions. To mitigate these risks, robust security measures including encryption and firewalls are essential, alongside continuous monitoring and updates to combat evolving threats. Addressing cyber threats in urban aeroponic systems, implementing quantum encryption emerges as a promising solution. Quantum key distribution (QKD) ensures highly secure encryption keys using quantum states that change upon eavesdropping, thereby thwarting intrusion attempts effectively. Integrating quantum encryption in aeroponic control systems safeguards data integrity and operational continuity against cyber threats, bolstering urban agriculture resilience. Our findings demonstrate the efficacy of quantum BB84 protocol integrated with application programming interface (API) for Eve’s security. Quantum bit error rate (QBER) measurements revealed minimal interference (0.015) for Alice and Bob, contrasting with higher initial QBER (up to 1.0) for Eve, indicative of intrusion attempts. Histogram analysis further underscored quantum security’s effectiveness in identifying and mitigating breaches. For future research, enhancing quantum encryption protocols and integrating advanced detection mechanisms will be essential.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Each and every living thing needs fresh water to survive. Fresh water is becoming a precious reso... more Each and every living thing needs fresh water to survive. Fresh water is becoming a precious resource as a result of the combined risks of rapid urbanization, pollution, and climatic changes. The quality of the water we drink every day has an impact on our lives, either directly or indirectly. Maintaining the sustainability and health of the environment requires constant attention to water quality. Modern technology makes it possible to gather and analyze data from water distribution networks in order to maximize resources and enhance decision-making for all parties. Despite the enormous global growth of the internet of things (IoT) and blockchain in recent years, their integration is still in its early stages. In this research contains a technological framework that combines blockchain and IoT called B-IoT and aims to reward and incentivize more sustainable water quality management with real-time monitoring and security. IoT is used to monitor water quality in water resources and find any violations. By using blockchain, it is possible to retain the accuracy, reliability, and transparency of the records of breaches. This system will be able to gauge the water’s quality in real-time and allow for the quick identification of any infractions necessary to commit the crime.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

This study provides a systematic review of the literature on the fourth industrial revolution (IR... more This study provides a systematic review of the literature on the fourth industrial revolution (IR4.0) and the internet of things (IoT) in genetics, informatics, and biotechnology, as well as their many rapidly evolving applications, which often overlap with various aspects of life. The study reviews the latest research, books, scientific theses, and official websites in this field, placing them in a coherent context for researchers. It covers innovations that have driven the continuous development of IR4.0 and its challenges. The study highlights numerous fields and modern technologies expected to bring about tangible and radical changes in health, agriculture, and industry. It addresses key aspects of IR4.0 and the significant advancements brought by smart cities, and most importantly, artificial intelligence (AI), including robots, autonomous cars, 3D printing, big data, IoT, nanotechnology, biotechnology, energy storage, and quantum computing. By applying cutting-edge technology across various disciplines to boost productivity and foster development, technology plays a crucial role in linking the physical, digital, and biological realms. This revolution is built on multiple axes, including the convergence of biotechnology, digital media, and physical systems.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Normal people’s interaction and communication are easier than those with disabilities such as he... more Normal people’s interaction and communication are easier than those with disabilities such as hearing and speech, which are very complicated; hence, the use of sign language plays a crucial role in bridging this gap in communication. While previous attempts have been made to solve this problem using deep learning techniques, including convolutional neural networks (CNNs), support vector machine (SVM), and K-nearest neighbours (KNN), these have low accuracy or may not be employed in real time. This work addresses both issues: improving upon prior limitations and extending the challenge of classifying characters in Indian sign language (ISL). Our system, which can recognize 23 hand gestures of ISL through a purely camera-based approach, eliminates expensive hardware like hand gloves, thus making it economical. The system yields an accuracy of 97.5% on the training dataset, utilizing a pre-trained VGG16 CNN optimized by the Adam optimizer and cross-entropy loss function. These results clearly show how effective transfer learning is in classifying ISL and its possible real-world applications.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

In the highly competitive landscape of Malaysian internet service providers (ISPs), users seek ef... more In the highly competitive landscape of Malaysian internet service providers (ISPs), users seek efficient ways to assess service quality. While various websites allow visual comparisons of fiber ISPs, a direct side-by-side evaluation remains elusive. A survey of 101 respondents revealed that 92.1% found researching a company’s reputation time-consuming. Additionally, relying on English-centric online ratings may lead to skewed outcomes, disregarding reviews in diverse languages. In response, we developed a webbased dashboard utilizing Twitter sentiment analysis (SA) and the naïve Bayes (NB) algorithm to classify Malaysia’s best fiber ISPs. The SA focused on four key factors: package price, internet speed, coverage area, and customer service, simplifying the comparison process. The system’s usability and functionality tests showed that both the English and Malay models could classify scraped Twitter data with an accuracy of 80%. The system’s remarkable usability score of 94.58% on the system usability scale (SUS) confirms its acceptability and excellent performance in achieving research goals.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Life test data analysis is a statistical method used to analyze time data until a certain event o... more Life test data analysis is a statistical method used to analyze time data until a certain event occurs. If the life test data is produced after the experiment has been running for a set amount of time, the life time data may be type I censored data. When conducting observations for survival analysis, it is anticipated that the data would conform to a specific probability distribution. Meanwhile, to determine the characteristics of a population, parameter estimation is carried out. The purpose of this study is to use the linear exponential loss function method to derive parameter estimators from the exponential distribution of two parameters on type I censored data. The prior distribution used is a non-informative prior with the determination technique using the Jeffrey’s method. Based on the research results that have been obtained, application is carried out on real data. This data is data on the length of time employees have worked before they experienced attrition with a censorship limit based on age, namely 58 years, obtained from the Kaggle.com website. Based on the estimation results, the average length of work for employees is 6.29427 years. This shows that employees tend to experience attrition after working for a relatively long period of time.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Floods damage ecosystem of the affected area resulting in destruction, loss of asset and life. Th... more Floods damage ecosystem of the affected area resulting in destruction, loss of asset and life. The paper proposes a novel k-FVI, (k stands for Kerala and FVI for flood vulnerability index) to aid the decision makers reduce flood vulnerability of 14 districts of Kerala. Instead of usual classification of flood vulnerability indicators under exposure (𝔼), sensitivity (𝕊), and adaptive capacity (𝔸ℂ), k-FVI proposes that, indicators reflecting 𝕊 and preparedness (ℙ) govern pre-flood vulnerability, whereas those of 𝔼 and rehabilitation (ℝ) affects post-flood vulnerability. The division of 𝔸ℂ indicator into ℙ and ℝ indicators and clubbing them into pre-flood and post-flood vulnerability respectively results into reduced errors. The importance of high dimensional flood indicators is realized by measuring the entropy of affected areas. Use of technique for order preference by similarity to ideal solution (TOPSIS) and entropy-based weights to score flood affected area results in formulating robust k-FVI. The paper also compares k-FVI with existing FVIs in literature. It uses data of 2018 Kerala floods and assesses the flood vulnerability of its 14 districts. The results prove that k-FVI is an effective flood vulnerability score estimator. Variant of k-FVI can be used to obtain vulnerability for any other flood prone areas.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

The objective of this paper is to detect tomato leaf disease using Faster region-based convolutio... more The objective of this paper is to detect tomato leaf disease using Faster region-based convolutional neural network (R-CNN). The tomato leaf disease recognition system utilizes a dataset consisting of healthy tomato leaves and eight leaf diseases, including early blight, late blight, leaf mold, mosaic virus, septoria, spider mites, yellow leaf curl virus, and leaf miner. The dataset is obtained from various sources, such as Kaggle, Google Images, Bing Images, and Roboflow Universe. Pre-processing techniques, including collage, tile, static crop, and resize, are applied to prepare the dataset for training. Data augmentation methods, such as flipping, 90° rotation, exposure adjustment, and hue modification, are applied to enhance the model’s robustness and generalize its performance. Specifically, we implemented Faster R-CNN as part of Detectron2 using its base models and configurations. The results demonstrate that the X101-FPN base model for Faster R-CNN with the default configurations of Detectron2 is efficient and general enough to be applied to defect detection. This approach results in an average precision (AP) detection score of 87.01% for validation results.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2024

Illegal, unreported, and unregulated (IUU) fishing poses a significant threat by depleting fish s... more Illegal, unreported, and unregulated (IUU) fishing poses a significant threat by depleting fish stocks, damaging marine ecosystems, jeopardizing economic livelihoods, and undermining long-term environmental sustainability. To address this, the government has implemented a public policy of measured fishing within the blue economy framework. Given the involvement of numerous stakeholders, it is crucial for the government to gauge public sentiment through tweets on social media platforms to evaluate and refine the policy’s implementation for greater effectiveness. While the long short-term memory (LSTM) method for sentiment analysis is adept at handling text sequences and context, it struggles with capturing contextual semantic correlations. Conversely, the latent Dirichlet allocation (LDA) method excels in identifying these correlations and uncovering dominant topics. This study shows that integrating LDA for topic modeling with LSTM for sentiment analysis enhances overall performance, providing more accurate and comprehensive insights into public responses and identifying key topics discussed in social media tweets.