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Development and standardization of an attitudinal assessment scale for virtual laboratory integration in science education

10.11591/ijere.v14i4.32272
Thiyagu Kaliappan , Mary Vineetha Thomas , Santhosh Thangan , Srinivasan Padmanaban
The escalating adoption of virtual laboratories (V-Labs) within science education highlights an urgent need for an established metric to evaluate student attitudes toward their implementation. This research introduces a detailed attitudinal assessment scale, specifically designed to measure various aspects of student perceptions such as perceived effectiveness, satisfaction, pedagogical impact, usability, and overall influence on educational outcomes. The development process involved an elaborate procedure for generating items based on a thorough review of existing literature and insights from subject matter experts, followed by a pilot test conducted on a select cohort of science students aimed at refining the items. Employing stringent empirical methods including detailed item analysis and factor analysis, the research confirmed the scale's high reliability, evidenced by a Cronbach’s alpha of .983. Factor analysis identified five principal components that collectively encompass technological, psychological, and educational factors shaping student attitudes toward virtual labs. This scale is crucial for educators and administrators for effectively assessing and enhancing virtual lab integrations. It provides valuable insights that can inform the enhancement of virtual lab configurations, curriculum integration, and teaching strategies, ultimately improving student engagement and learning outcomes. The creation of this scale addresses a critical void in academic research by offering a standardized method to assess student attitudes and also paves the way for future investigations into the extensive implications of virtual labs in diverse educational settings and disciplines.
Volume: 14
Issue: 4
Page: 2857-2868
Publish at: 2025-08-01

Explainable artificial intelligence and feature based technique for the classification of kidney ultrasound images

10.11591/ijece.v15i4.pp4148-4159
Fizhan Kausar , Ramamurthy Bojan
Millions of people worldwide are affected by chronic kidney disease (CKD), which is one of the main causes of death. Using machine learning (ML) models, this study attempts to create a computer-aided diagnostic (CAD) system that can autonomously detect chronic kidney disease (CKD) with improved interpretability. An online medical database provided 340 ultrasound images used in this study, which included both normal and abnormal instances. 94 texture and intensity attributes were obtained from these images using Pyrandiomics. Six machine learning methods were used for classification: According to the evaluation results, support vector machine (SVM), decision tree (DT), random forest (RF), k-nearest neighbors (k-NN), XG-Boost, and naïve Bayes (NB) models were considered. Among these models, the random forest model demonstrated the highest accuracy. Explainable artificial intelligence (XAI) methods, namely Shapley additive explanation (SHAP), were utilized to improve model transparency. Clinicians could be assisted in comprehending the reasoning behind the predictions using SHAP analysis, which identifies the most important features impacting the ML model and visualizes the ranking of each individual feature.
Volume: 15
Issue: 4
Page: 4148-4159
Publish at: 2025-08-01

Designing and implementing teachers’ professional development program on crafting brain-based lessons

10.11591/ijere.v14i4.32642
Vanjoreeh A. Madale , Jamaliah A. Casidar , Manuel B. Barquilla , Monera A. Salic-Hairulla , John Jr G. Adil , Arlyn R. Alcopra
The increasing emphasis on brain-based learning (BBL) underscores its potential to enhance educational practices by integrating the biological foundations of learning. This study, conducted at Mat-I National High School, sought to address the gap between theoretical understanding and practical application of BBL among science and mathematics educators. Using a descriptive research design, the study aimed to develop and implement a comprehensive training designed to elevate teachers' proficiency in BBL strategies, ultimately improving their instructional effectiveness in science and mathematics education. A pre-training needs assessment identified a superficial familiarity with BBL among teachers, underscoring the need for more targeted professional development. The training program incorporated lectures, workshops, interactive exercises, and the creation of lesson plans tailored to BBL principles. Post-training assessments demonstrated a marked improvement in participants' understanding and application of BBL, advancing from basic to proficient levels. These findings suggest that the program successfully enhanced teaching practices. The study concludes by recommending continuous professional development, the development of BBL-aligned teaching tools, and the adoption of varied training methodologies to sustain and further improve educational outcomes in mathematics and science education.
Volume: 14
Issue: 4
Page: 2790-2799
Publish at: 2025-08-01

Sensitivity factors based computationally efficient approach for evaluation and enhancement of available transfer capability

10.11591/ijece.v15i4.pp3556-3565
Manjula S. Sureban , Shekhappa G. Ankaliki
Available transfer capability (ATC) is an indication of the capability of the transmission system to efficiently increase power transmission for further commercial trading between two areas or two points. ATC plays an important role in operating power systems economically, reliably, and securely. As the deregulation in the power system can cause overload in the transmission system, ATC evaluation and enhancement are required for secure and reliable operation. The advancements in power generation techniques and switching from centralized generation to distributed generation (DG) with more emphasis on renewable sources have resulted in various approaches to enhance ATC. In this work, a computationally efficient sensitivity-based methodology for evaluating and improving ATC with the presence of renewable generation is proposed. The developed approach is implemented on the IEEE 30 bus system and the outcome is compared with the existing methods in the literature.
Volume: 15
Issue: 4
Page: 3556-3565
Publish at: 2025-08-01

High-speed dividing device with the formation of quotient and remainder

10.12928/telkomnika.v23i4.26306
Yevgeniya; Satbayev University Aitkhozhayeva , Khalicha; Satbayev University Yubuzova
Considered the possibility of accelerating the time-critical operation of division for multi-bit integers. This problem is significant since, so multi-bit integers are widely used in specialized devices, including cryptographic transformations. A method for high-speed quotient and remainder determination with optimal hardware costs is proposed. A preliminary increase in the divisor and its subsequent decrease by shifting it to the right are used. A structural diagram and functional diagram of the hardware implementation have been developed using high-speed combinational logic circuits. The device’s principle of operation, its step-by-step process, and specific examples illustrating its correct operation and resource efficiency are addressed. On average, it takes (k/2+1) clock cycles to obtain the result, where (k+1) bit capacity of the quotient. In most division schemes with optimal hardware costs, the number of clock cycles required to obtain the quotient (without remainder) is (k+1). High-speed division with simultaneous determination of several quotient bits requires (m/p) clock cycles for the division operation, where p- the number of simultaneously determined quotient bits, m-bit capacity of dividend. However, this approach will require additional hardware. The research will continue by modeling the device in Vivado Design Suite computer aided design (CAD) based on Artix-7 field programmable gate array (FPGA) from Xilinx.
Volume: 23
Issue: 4
Page: 943-953
Publish at: 2025-08-01

Developing a robust data integrity verification framework for cloud storage utilizing Boneh-Lynn-Shacham signatures

10.12928/telkomnika.v23i4.26709
Raed; Northern Technical University Abdulkareem Hasan , Mustafa; Imam Aadham University College M. Akawee , Enas; Northern Technical University Faek Aziz , Omar A.; Collage/Fallujah University Hammood , Tole; Universitas Ahmad Dahlan Sutikno
Cloud computing (CC) is a service that allows both data storage and data accessibility on the cloud through any on-demand service and application, without incurring the costs of local data storage and upkeep expenses. On the other hand, CC providers have to make sure good security among the consumers to inspire them to use the resources on the cloud as if it were their local storage, without bothering about the data quality. Therefore, data checking in the cloud gains much importance mostly at the demand of the customers for the data integrity that a third-party auditor (TPA) can be introduced to verify the data soundness. A present investigation introduced a secure and efficient auditing solution for cloud data under the Boneh-Lynn-Shacham (BLS) public identities to keep the information secure and at the same time perform auditing securely. this study restructured the public key equation with the signature equation in our proposed system so that there is an increment in complexity while quality execution speed is maintained, and the proposed system allows dynamic data processing in terms of insert, delete and modification. From the analysis of the system, which includes security and performance, the proposed system is very effective and safe.
Volume: 23
Issue: 4
Page: 1097-1107
Publish at: 2025-08-01

A compact five-band patch antenna covering WLAN, WiMAX, X, and Ku-bands

10.12928/telkomnika.v23i4.27017
Suthasinee; Rajamangala University of Technology Isan Khonkaen Campus Lamultree , Wutthipong; Rajamangala University of Technology Isan Khonkaen Campus Thanamalapong , Kanawat; Rajamangala University of Technology Isan Khonkaen Campus Nuangwongsa , Charinsak; Rajamangala University of Technology Isan Khonkaen Campus Saetiaw
This paper introduces a compact, low-profile, five-band antenna for wireless communication systems operating across 2.4/5 GHz WLAN, 3.5 GHz WiMax, and 7.5 GHz X- and Ku-band frequencies. The proposed antenna utilizes a novel configuration with a dual-overlapping rectangular patch coupled to a wide circular slot and an inverted L-shaped strip. Fabricated on a single-layer FR4 substrate (εr=4.3, thickness=1.6 mm), the antenna employs a 50-ohm coplanar waveguide feed, resulting in a compact footprint of 40×40×1.6 mm³. Experimental measurements and simulations demonstrate a bidirectional radiation pattern covering five distinct frequency bands: 2.4-2.485 GHz, 3.4-3.6 GHz, 5.15-5.825 GHz, 7.25-8.4 GHz, and 13.4-17.7 GHz. The antenna exhibits a return loss better than 10 dB across all bands and provides average gains of 1.78 dBi, 3.04 dBi, 3.4 dBi, 4.27 dBi, and 4.46 dBi, respectively. These results confirm the successful development of a five-band antenna with excellent performance characteristics, making it a promising candidate for 2.4/5 GHz WLAN, WiMax, and X- and Ku-band satellite communications, with automotive vehicles being one example.
Volume: 23
Issue: 4
Page: 906-917
Publish at: 2025-08-01

Integrating artificial bee colony and cauchy algorithms for distribution network reconfiguration with soft open points

10.12928/telkomnika.v23i4.26129
Nguyen; Electric Power University Tung Linh , Nguyen; Electric Power University Quynh Anh
Reconfiguring the distribution network by selecting open switch states is an effective approach to reduce power losses in the system. However, with the rise of distributed energy resources such as photovoltaic and wind turbines and dynamic loads such as electric vehicles, which introduce uncertainties, it has become necessary to integrate standard operating procedures (SOPs) to better control power flows. This study proposes an algorithm that combines the artificial bee colony (ABC) and Cauchy opposition-based learning (OBL) algorithms to solve the optimization problem of determining both the location and capacity of SOPs, alongside reconfiguring the distribution network. The primary objective is to minimize power losses while improving power quality and system reliability. The proposed methodology was validated on the IEEE 33-node and 69-node distribution networks under seven varied operational scenarios, evaluating outcomes both with and without the integration of SOPs. The findings demonstrate that installing SOPs optimally reduces power losses, enhances system reliability, and maintains voltage levels within acceptable limits. The integration of the two algorithms also accelerates the convergence process, increasing computational speed and avoiding local optimization issues. When compared with other methods, the proposed algorithm delivers similar performance but with faster computation times and fewer iterations, making it more efficient and reliable.
Volume: 23
Issue: 4
Page: 1069-1083
Publish at: 2025-08-01

Understanding e-book acceptance from a resource-based view perspective: an analysis among students at UiTM Melaka

10.11591/ijere.v14i4.32111
Zulkefli Muhamad Hanapiyah , Ahmad Fadhly Arham , Muhammad Syukri Abdullah , Muhammad Fairuz Jamil , Nor Sabrena Norizan , Wei-Loon Koe
The COVID-19 pandemic led to a shift in the Malaysian education system from traditional face-to-face teaching to online and open distance learning (ODL). This transition has impacted students, lecturers, and universities. E-books are one technology that supports online learning at the university level. This study aims to investigate the factors influencing e-book acceptance among students. Using quantitative research, a questionnaire was administered to 171 students at Universiti Teknologi MARA (UiTM), Melaka Campus, who are enrolled in strategic management course. The findings reveal a significant impact of course content, instructors, and university support on e-book acceptance. However, there was no significant effect observed for access ability, computer competency and infrastructure. These insights are crucial for universities to plan and implement e-books effectively for their students. As the study is specific to UiTM Melaka Campus, it is recommended that future research encompasses both public and private universities for a more comprehensive understanding.
Volume: 14
Issue: 4
Page: 2742-2748
Publish at: 2025-08-01

Design of a concurrent tri-band LNA based on composite right/left-handed transmission line resonators

10.12928/telkomnika.v23i4.26816
Faycal; Moulay Ismail University El Hardouzi , Mohammed; Moulay Ismail University Lahsaini , Mustapha; Moulay Ismail University Bahich , Badr; Moulay Ismail University Nasiri , Younes; Moulay Ismail University Achaoui
This article presents a three-band low noise amplifier (LNA) in microstrip technology based on composite right left handed transmmision line (CRLH TL) resonators for multi-band behavior, which has been designed to meet all the criteria that determine the quality of its operation. The transistor used is biased via a transmission line and matched by λ/4 transformer filters with CRLH-TL type resonators at the output to establish multiband behavior with improved band rejection to suppress unwanted frequencies and interference. The results demonstrate excellent performance at three frequencies: 900 MHz (15.03 dB gain), 2.1 GHz (13.58 dB gain), and 3.5 GHz (12.57 dB gain), with a noise figure below 2 dB and unconditional stability. The size of the proposed amplifier is 73×63 𝑚𝑚2 in area.
Volume: 23
Issue: 4
Page: 896-905
Publish at: 2025-08-01

Optimizing signal conversion in uniform FBGs with InGaAs photodetectors for medical sensors

10.12928/telkomnika.v23i4.26164
Tengku; Universitas Riau Emrinaldi , Bambang; National Research and Innovation Agency, KST BJ HABIBIE Widiyatmoko , Bunga; Universitas Riau Meyzia , Sumiaty; Universiti Teknologi Malaysia Ambran , Saktioto; Universitas Riau Saktioto , Mohamad; National Research and Innovation Agency, KST BJ HABIBIE Syahadi , Agitta; National Research and Innovation Agency, KST BJ HABIBIE Rianaris , Dwi; National Research and Innovation Agency, KST BJ HABIBIE Hanto
This study experimentally interrogates the spectral response of uniform fiber Bragg gratings (FBGs) with varying reflectivity levels of 30%, 50%, 70%, and 90% under controlled environmental stimuli. The objective is to elucidate the influence of reflectivity on the wavelength shift behavior of FBGs and to inform the optimal interrogation of these elements with indium gallium arsenide (InGaAs) photodetectors in high-performance sensing systems. Utilizing high-precision measurement procedures and specialized instrumentation, the experiments revealed that the magnitude and pattern of wavelength shifts are significantly influenced by FBG reflectivity. Specifically, lower reflectivity enhances sensitivity, while higher reflectivity contributes to greater spectral stability. These findings highlight the critical role of reflectivity in shaping the spectral modulation characteristics of FBGs, establishing a critical theoretical framework for precision optical sensor systems. The outcomes give significant contributions to the design and calibration of FBG-based sensors, particularly biomedical applications where precision and responsiveness are paramount.
Volume: 23
Issue: 4
Page: 1058-1068
Publish at: 2025-08-01

Automated rice leaf disease detection using artificial intelligence deep learning

10.11591/ijict.v14i2.pp405-415
Suhaila M. P. , Hemalatha S.
As one of the top five rice-producing countries, India relies heavily on rice for both economic management and food needs. To ensure healthy rice plant growth, early detection of diseases and timely treatment are essential. Since manual disease detection is time-consuming and labor-intensive, an automated approach is more practical. This work presents a deep neural network (DNN)-based artificial intelligence (AI) method for recognizing rice leaf diseases. The method detects three common diseases: leaf smut, bacterial leaf blight, and brown spot, as well as healthy images. The approach uses an AI-based attention network and semantic batch normalized DeepNet (AN-SBNDN) combined with a channel attention mechanism to improve disease detection accuracy. Experiments with rice leaf datasets and comparison with conventional networks like residual attention network (Res ATTEN) and dynamic speeded up robust features (DSURF) validate the effectiveness of the method. Key performance metrics include average accuracy, time, precision, and recall, achieved at 21%, 44%, 26%, and 31%, respectively.
Volume: 14
Issue: 2
Page: 405-415
Publish at: 2025-08-01

Energy scavenging-aided NOMA uplink communications: performance analysis

10.12928/telkomnika.v23i4.26822
Huu; Industrial University of Ho Chi Minh City Q. Tran , Khuong; Ho Chi Minh City University of Technology (HCMUT) Ho-Van
Energy scavenging-aided nonorthogonal multiple access (NOMA) networks significantly ameliorate energy-and-spectral efficiencies thanks to superimposing a multitude of user signals for concurrent transmission and harvesting radio frequency energy. Practically, energy harvesters possess non-linear characteristic and their efficiency is enhanced considerably with deployment of multiple antennas. Moreover, communication reliability and harvested energy are directly influenced by wireless propagation which induces simultaneous effects of shadowing, path loss, and fading. Accordingly, the current paper assesses analytically outage probability and throughput of energy scavenging (ES)-aided NOMA uplink communications (eNOMAu) taking into account the above-addressed realistic factors (κ − µ shadowed fading, multi-antenna deployment, ES nonlinearity). The results reveal considerable performance degradation caused by ES non-linearity and wireless propagation. Additionally, desired system performance can be reached flexibly with appropriate specification selection. In addition, accreting a quantity of antennas drastically mitigates the outage probability of eNOMAu, which can be minimized with optimal ES time selection. Furthermore, the proposed eNOMAu is considerably superior to its eOMAu counterpart.
Volume: 23
Issue: 4
Page: 918-931
Publish at: 2025-08-01

Grid search vs Bayesian optimization for intensity scoring classification and channel recommendation prediction

10.12928/telkomnika.v23i4.26341
Kelly; Universitas Multimedia Nusantara Mae , Dinar; Universitas Multimedia Nusantara Ajeng Kristiyanti
Technological advancement has spurred financial technology growth, transforming traditional financial operations into digital. Peer-to-peer (P2P) lending is a key fintech solution offering online loans, though it struggles with repayment issues due to customer financial instability. To overcome these challenges, XYZ is a startup that focuses on enhancing the efficiency of collections and communication with customers. XYZ necessitates the implementation of a collection intensity scoring (CIS) model and a prediction model for interaction on recommended communication channels in order to optimize the collection process. This study evaluates the performance of grid search and Bayesian optimization on random forest (RF) classification models and K-nearest neighbors (KNN) regressor prediction models. RF and KNN regressor algorithms optimization are necessary to enhance their performance in CIS classification and channel recommendation prediction. The research stages follow the cross industry standard process-data mining (CRISP-DM) framework, which consists of business understanding, data understanding, data preparation, modeling, and evaluation. The model performance is assessed by accuracy and mean absolute error (MAE). The results of this study show that Bayesian optimization surpasses grid search, enhancing the accuracy of the RF model to 98.34% and reducing the MAE of the KNN regressor model to 0.24530.
Volume: 23
Issue: 4
Page: 1020-1031
Publish at: 2025-08-01

Design of a soft circular patch antenna operating in the 60 GHz band for 5G/6G applications

10.12928/telkomnika.v23i4.26722
Salah-Eddine; Sidi Mohamed Ben Abdellah University Didi , Imane; LSEED Laboratory Halkhams , Abdelhafid; Sidi Mohamed Ben Abdellah University Es-Saqy , Mohammed; Sidi Mohamed Ben Abdellah University Fattah , Said; Sidi Mohamed Ben Abdellah University Mazer , Moulhime; Sidi Mohamed Ben Abdellah University El Bekkali
5G/6G technologies require higher-performance antennas in terms of bandwidth, gain, radiation, compact size, efficiency, and low cost. At the same time, fewer natural disturbances, such as rain and snow, and fewer non-natural disturbances. This is the challenge facing scientific research into antenna design and manufacture. In addition, in this paper we study and design a flexible circular microstrip patch antenna operating in the 60 GHz band for 5G/6G applications. This antenna is based on a biosourced substrate for industrial, scientific, and medical applications. For this study, we will use two techniques: one concerns the deformation of the ground plane deformation of the ground plane and substrate to improve the electrical performance of a proposed antenna. At the same time, the other is the parametric study of the appropriate position of a coaxial feed probe. This technique has the advantage of requiring no radiation contrition on the part of the coaxial probe. Next, specialized high-frequency structure simulator (HFSS) simulation software is used to design this antenna; it has a wide bandwidth above 3 GHz, a gain of 7.41 dB, a directivity of 7.53 dB, a radiated power of 13.55 dBm, an accepted power of 13.67 dBm, an incident power of 15.08 dBm, a radiation efficiency of 97.29 % and an efficiency of 98.4 %.
Volume: 23
Issue: 4
Page: 1120-1127
Publish at: 2025-08-01
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