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Arobust blind signcryption scheme for secure internet of drones communication

10.12928/telkomnika.v24i3.27677
Tahri; Hassan First University Rachid , Abdellah; Hassan First University Ouammou , Abdellatif; Sultan Moulay Slimane University Lasbahani , Hibat; Hassan First University Eallah Mohtadi
The rapid deployment of the internet of drones (IoD) exposes aerial networks to authentication failures, eavesdropping, data theft, and impersonation attacks due to open wireless communication. This paper presents a lightweight identity based blind signcryption scheme for secure IoD communication. The scheme leverages hyper-elliptic curve cryptography to provide strong security with reduced computational overhead, making it suitable for resource-constrained drones. The blind signcryption mechanism enhances privacy by preventing the signer from accessing message content. Informal analysis shows that the scheme achieves confidentiality, authentication, anonymity, forward secrecy, and resis tance to common protocol-level attacks. Formal verification using the Scyther tool confirms secrecy, agreement, and authentication properties under a stan dard symbolic adversary model. Analytical and simulation-based evaluations demonstrate average reductions of 59.60% in computational cost, 48.86% in communication overhead, and 55.75% in energy consumption compared with existing schemes. While the results confirm protocol-level efficiency, real-world implementation and testbed validation remain future work.
Volume: 24
Issue: 3
Page: 991-1002
Publish at: 2026-06-01

Design and development of WIKIN: an interactive nuclear community website for Indonesia using Laravel framework

10.12928/telkomnika.v24i3.27447
Abdelilah; Abdelmalek Essaadi University Mhamedi , Mohammed; Abdelmalek Essaadi University Mghari , Abdelaaziz; Abdelmalek Essaadi University El Hibaoui
Despite its significant contributions to health, agriculture, and energy, the public perception of nuclear technology in Indonesia remains cautious and fragmented. Existing communication channels are largely one-way and regulatory, offering limited opportunities for public interaction and collaborative learning. This study investigates how an interactive web-based platform can enhance public engagement and knowledge sharing in nuclear science and technology. To address this challenge, a Nuclear Community Interactive Website (WIKIN) for Indonesia was designed and developed using the Laravel framework, following a structured waterfall methodology. The system integrates role-based access control, modular architecture, and responsive design to support community participation through the sharing of news, discussions, and documentation of service activities. The evaluation was conducted through black-box functional testing of 27 features (all passed) and a system usability scale (SUS) survey involving 51 users, which produced an average score of 74.8 (“Good”), indicating satisfactory usability and acceptance. These results demonstrate that WIKIN provides an effective model for fostering two-way communication, improving transparency, and strengthening public literacy regarding nuclear issues. This study contributes to digital public engagement research by demonstrating how user-centered design principles can be effectively applied to enhance trust, transparency, and community participation in nuclear science communication.
Volume: 24
Issue: 3
Page: 840-851
Publish at: 2026-06-01

A study of constrained Bézier fitting curve with tangent continuity for quadruped walking robot gaits

10.12928/telkomnika.v24i3.27620
Hung T.; Thai Nguyen University of Technology Nguyen , Minh T.; Thai Nguyen University of Technology Nguyen , Mui D.; Thai Nguyen University of Technology Nguyen , Long Q.; Thai Nguyen University of Information and Communication Technology Dinh , Dung T.; Thai Nguyen University of Information and Communication Technology Nguyen
Smooth and stable gait generation is critical for quadruped robots operating in unstructured environments. This paper introduces a constrained Bézier fitting framework. It enforces tangent continuity (𝐶1 continuity) at the gait cycle junction. This continuity addresses the tangential discontinuities that commonly arise in unconstrained Bézier trajectories. The method formulates foot-trajectory design as a constrained least-squares problem solved via Lagrange multipliers, enabling the control points to simultaneously satisfy interpolation targets and matched-tangent conditions. The resulting curves retain the geometric flexibility of classical Bézier parametrizations while producing well-behaved velocity profiles suitable for legged locomotion. These trajectories are integrated into an impedance-controlled leg model and evaluated in the MuJoCo simulator. Simulation results indicate noticeable reductions in torque spikes and improvements in tracking accuracy when compared to unconstrained Bézier and spline baselines, with representative trials showing reductions on the order of 40% and tracking improvements of approximately 25%. The proposed approach combines mathematical rigor with practical applicability, providing an efficient and reliable solution for high-performance quadruped gait planning.
Volume: 24
Issue: 3
Page: 1048-1057
Publish at: 2026-06-01

Stochastic Resonance-Aided Energy Detection for RF-Powered Cognitive Radio Networks

10.12928/telkomnika.v24i3.27596
Henry Onyemauche; Nigeria Maritime University Osuagwu , Mamilus A.; University of Nigeria Ahaneku , Vincent C.; University of Nigeria Chijindu , Obinna M.; University of Nigeria Ezeja
Conventional stochastic resonance (SR) techniques often face challenges with higher-frequency signals and parameter optimization for real-time applications, as observed in practical orthogonal frequency-division multiplexing (OFDM) systems that are vulnerable to noise uncertainty (NU). In this study, we present a novel SR-aided energy detection (ED) method that incorporates multi-taper spectrum estimation technique to improve spectrum estimation precision and Gauss-Seidel-like iteration method to accurately adjust the SR parameters for real-time adaptation. This combined strategy enhances weak signal detection, prevents signal distortion, and increases robustness against fluctuating noise conditions. Results from 5,000 Monte Carlo simulations showed that, at 0 dB NU, SR-aided ED attained 90% detection probability at -11 dB, outperforming conventional ED with an SNR gain of 12.5 dB. At 3 dB NU, the conventional ED accuracy degraded by 5.5 dB, resulting in a false alarm probability of 77%, while SR-aided ED demonstrated robustness to NU. At 10 dB NU, ED failed to distinguish the differences between noise and signal power, giving rise to 99% false alarm probability. In contrast, despite a 6 dB degradation, the developed SR-aided ED approach still guarantees a 1% false alarm probability. In clipping-prone systems, conventional ED is vulnerable to signal clipping. Conversely, SR-aided ED remains unaffected.
Volume: 24
Issue: 3
Page: 786-800
Publish at: 2026-06-01

Enhancing image security through nonlinear preprocessing and double random phase encoding using fractional fourier transform

10.12928/telkomnika.v24i3.27650
Fayçal; University of Setif 1 Radjah , Nacira; University of Mohamed El Bachir El Ibrahimi Diffellah , Tewfik; University of Setif 1 Bekkouche , Lahcene; University of Setif 1 Ziet
Image encryption is crucial for secure data transmission in fields such as IoT, medical imaging, and biometrics. This paper proposes an enhanced encryption framework that combines nonlinear preprocessing with double random phase encoding (DRPE) using the fractional fourier transform (FrFT). The diffusion process replaces the conventional XOR operation with a nonlinear hyperbolic tangent (tanh) function, improving confusion diffusion complexity and resistance to cryptanalytic attacks. Experimental results show a reduction in peak signal-to-noise ratio (PSNR) from 9.03 dB to 7.25 dB and a mean squared error (MSE) increase to 10×10³, indicating stronger encryption and lower correlation with the original image. The proposed method also enhances robustness against histogram and key sensitivity attacks. Statistical analyses, including entropy and number of pixels change rate (NPCR) metrics, demonstrate that the approach outperforms conventional DRPE methods while maintaining computational efficiency. This hybrid nonlinear and FrFT-based framework provides a practical and scalable solution for secure image transmission in sensitive and real-time applications.
Volume: 24
Issue: 3
Page: 1003-1013
Publish at: 2026-06-01

Neural network approaches for quality-of-service optimization in software-defined networking environments

10.12928/telkomnika.v24i3.27766
Muqamuddin; Jawaharlal Nehru Technological University Hyderabad Muhib , Rangu; Jawaharlal Nehru Technological University Hyderabad Sridevi
Software-defined networking (SDN) enables centralized and programmable control of network behavior; however, conventional routing strategies remain largely reactive and struggle to adapt to rapidly changing traffic dynamics. To address this limitation, this study proposes a learning-based SDN routing framework that integrates a long short-term memory (LSTM) model to predict traffic patterns and proactively optimize routing decisions. The proposed approach is implemented and evaluated in an SDN testbed using realistic traffic scenarios. Experimental results are averaged over multiple independent runs to ensure robustness and reproducibility. Compared with static shortest-path routing and classical machine learning (ML) baselines, the proposed model demonstrates consistent improvements in latency, packet loss, and throughput under the evaluated conditions. In particular, the ablation study reports a 95% confidence interval for end-to-end latency ranging from 51.8 to 55.6 ms, confirming the statistical stability of the observed gains. Additional analyses show that the framework maintains low inference latency and modest control overhead, making it suitable for real-time SDN environments. Overall, the findings indicate that temporal learning models can effectively enhance SDN routing performance when evaluated within controlled experimental settings, offering a practical pathway toward more adaptive and intelligent network control.
Volume: 24
Issue: 3
Page: 825-839
Publish at: 2026-06-01

Efficient IoT-based smart irrigation system using LoRaWAN for resource optimization in agriculture

10.12928/telkomnika.v24i3.27326
Faten; University of Tunis El Manar Ben Aicha , Imen; University of Tunis El Manar Ayachi
The global agricultural sector faces critical challenges such as climate change, water scarcity, and inefficient irrigation practices. This paper presents an internet of things (IoT)-based smart irrigation system designed to optimize water usage and enhance agricultural productivity in Tunisia’s semi-arid regions. The proposed system integrates sensors (YL-69 soil moisture, DHT22 temperature-humidity, FC-37 rain), a STM32L072Z LRWAN1 board, and long-range wide area network (LoRaWAN) communication to transmit real-time data to a ThingPark server and MongoDB database. A mobile application developed in Flutter enables monitoring and control through manual, automated, and event-driven modes. Experimental validation demonstrates water savings and improved irrigation efficiency compared to conventional systems. Quantitative results, benchmarking, and cost-benefit analysis confirm the system’s affordability, energy sustainability, and scalability. This solution contributes to sustainable agriculture in resource-constrained environments.
Volume: 24
Issue: 3
Page: 957-965
Publish at: 2026-06-01

Network traffic analysis and bandwidth forecasting for using Meta’s Prophet: a case study

10.12928/telkomnika.v24i3.27609
Yusuf Onimisi; Landmark University Isaac , Ayodeji James; Tshwane University of Technology Bamisaye , Ijagbemi; Landmark University Adedotun , Theophilus Olusegun; Landmark University Dada , Onyemenam Obiajulu; Landmark University John
This study created a forward-looking bandwidth prediction system for students’ halls of residence at Landmark University. The system uses Meta’s Prophet, a method for analyzing patterns in data over time, and was trained on past internet traffic data from October to December 2024. The system was able to predict future bandwidth usage with over 90% accuracy. To assess how well the system worked, several common metrics were used, including mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). The MAE was calculated as 10,099,863.10 bits per second (bps), and the RMSE was 13,570,959.58 bps. While the mean squared error (MSE) appears large numerically, this is anticipated due to the size of the bandwidth data involved in its calculation. Importantly, the prediction errors are considered reasonable when considered in relation to the actual peak bandwidth usage, which fluctuated between 47 and 50 megabits per second (Mbps). These findings suggest that machine learning can be a valuable tool for refining network infrastructure and improving the user experience quality of service (QoS) in environments with many users, such as university residences.
Volume: 24
Issue: 3
Page: 751-764
Publish at: 2026-06-01

Design of 7-level cascade asymmetric multilevel inverter for renewable energy applications using FPGA

10.11591/ijpeds.v17.i2.pp1231-1242
Afarulrazi Abu Bakar , Hazwaj Mhd Poad , Benjamin Ho Hao Xian , Tharnisha Sithananthan , Wahyu Mulyo Utomo , Triyanto Pangaribowo
The increasing focus on renewable energy has driven the need for efficient and reliable power converters. Multilevel inverters offer low harmonic distortion and high-quality output but often suffer from design complexity and excessive component count. This study presents the design and implementation of a 7-level cascaded asymmetric multilevel inverter optimized for renewable energy applications. The proposed topology utilizes a cascade structure with asymmetric DC voltage sources to generate seven voltage levels, providing a practical balance between performance and simplicity. The design was first validated through MATLAB/Simulink software to analyze circuit operation and evaluate the total harmonic distortion (THD) performance. Experimental evaluation was then conducted using a hardware prototype to verify simulation results. Without a filter, the THD from the simulation was 21.31%, while the experimental setup recorded a slightly higher value of 21.61%, indicating a marginal difference of 0.21%. With a filter, the simulation achieved a THD of 3.81%, whereas the experimental setup outperformed with a THD of 1.5%, showing a notable reduction of 2.31%. These findings confirm the proposed inverter’s capability to deliver superior power quality and operational efficiency. The combination of simulation and experimental validation demonstrates the practicality and reliability of the 7-level cascade asymmetric multilevel inverter for renewable energy applications.
Volume: 17
Issue: 2
Page: 1231-1242
Publish at: 2026-06-01

Real-time classification of Pasaman oranges using Mamdani fuzzy inference system and ESP32 microcontroller

10.12928/telkomnika.v24i3.27407
Fahmi; Andalas University Fitrio Fauzi , Ifmalinda; Andalas University Ifmalinda , Azrifirwan; Andalas University Azrifirwan
Manual classification of Pasaman oranges based on visual assessment of size and color often produces inconsistent results due to human subjectivity. This study develops an automatic classification system using a Mamdani fuzzy inference system (FIS) implemented on an ESP32 microcontroller. Fruit diameter is measured using a high-frequency sound wave ranging module (HC-SR04) ultrasonic sensor, while surface color is detected using a TAOS color sensor 3200 (TCS3200) color sensor. The obtained data are processed through fuzzification, inference, and defuzzification to classify oranges into three quality grades (A, B, and C). System performance evaluation shows strong agreement between the developed system and matrix laboratory (MATLAB) simulation, with a coefficient of determination (R²) value of 0.9855, indicating reliable and consistent classification performance for automated agricultural grading applications.
Volume: 24
Issue: 3
Page: 1058-1067
Publish at: 2026-06-01

A system modeling approach for business intelligence system design in the Indonesian kite string industry

10.12928/telkomnika.v24i3.27573
Hendry; Universitas Trisakti Anggraito , Rina; Universitas Trisakti Fitriana , Dadan Umar; Universitas Trisakti Daihani , Emelia; Universitas Trisakti Sari
Kite strings in Indonesia are crafted by local artisans who have learned from their predecessors, but the industry struggles to deliver quality products that meet customer standards. A Systematic approach to this problem could involve designing a business intelligence (BI) system to improve decision-making. Based on the main premises of the kite string industry, this paper focuses on developing a causal loop diagram (CLD) model as a first step toward designing an effective BI system for the kite string industry. The CLD model captures the relationships between core variables and brain areas, offering crucial insights into customer perceptions, production quality, and market dynamics. Based on data up to October 2023, the study uses a systematic approach to pinpoint the feedback loops enabling product quality and business performance. This framework can be used as a strategic approach to assist in decision-making, refine operational processes, and enhance overall product quality. This research provides a new perspective to the literature by combining systems thinking into BI system design under the context of traditional industries as an elaboration of findings aimed to gain a competitive advantage in Indonesian kite string business practices.
Volume: 24
Issue: 3
Page: 816-824
Publish at: 2026-06-01

TikTok store affiliate performance sentiment analysis using support vector machine and gradient boosting machine methods

10.12928/telkomnika.v24i3.27473
Fersellia; Ma’arif Nahdlatul Ulama University Fersellia , Fahmi; Universitas Gadjah Mada Fachri , Afdhal; Ma’arif Nahdlatul Ulama University Fauzan , Nihayatus; Universitas Gadjah Mada Zaen
The development of social media-based e-commerce, particularly, opens new opportunities for digital affiliate systems. This study examines public perception of affiliate performance through comment sentiment analysis (positive, negative, neutral) using support vector machine (SVM) and gradient boosting machine (GBM). Data was collected from TikTok Shop comments, processed through text preprocessing, manual labeling, and then analyzed using Python. Evaluation using accuracy, precision, recall, and F1-score metrics showed that the combination of the synthetic minority oversampling technique (SMOTE) with SVM and GBM improved classification performance, although negative sentiment remained challenging. SVM achieved the highest accuracy (84%) with a ratio of 90:10, while GBM excelled in detecting neutral sentiment (F1 0.91). These findings are useful for sentiment-based marketing strategies and natural language processing (NLP) development for Indonesian-language texts on TikTok Shop.
Volume: 24
Issue: 3
Page: 883-890
Publish at: 2026-06-01

Design and development of a portable electromagnetic coil accelerator for advanced defense applications

10.11591/ijpeds.v17.i2.pp823-834
M. Priyadharsini , Sunil Kumar Gupta , Manoj Gupta
In this work, a prototype of a six-stage coil gun was designed and developed to accelerate and propel a ferromagnetic projectile as an alternative technology to traditional firearms, which rely on explosive power for defense applications. The electromagnetic coils were arranged along the length of the barrel and were energized one at a time, sequentially, from one end of the barrel to the other to accelerate and propel the projectile forward. This paper presents the design, simulation, and optimization of the barrel and projectile, including details of the electromagnetic coils, triggering and switching circuits, and pulsed current sources. Simulations were conducted using COMSOL Multiphysics software with both single-coil and multiple-coil configurations. The prototype model incorporates a non-ferromagnetic barrel to minimize the retarding magnetic field and hysteresis, which could otherwise reduce the projectile’s velocity. The barrel is equipped with IR sensors to detect the projectile’s movement and activate or deactivate the corresponding electromagnetic coils, ensuring efficient forward propulsion. Utilizing a capacitor bank and rapid charging circuits, the developed prototype unit is capable of propelling the projectile at a velocity of 419 m/s measured at a 10-meter distance and could fire every 2 milliseconds successfully. The prototype unit developed is a handheld rifle using a polyvinyl chloride (PVC) barrel and uses a projectile with dimensions meeting the defense application.
Volume: 17
Issue: 2
Page: 823-834
Publish at: 2026-06-01

Performance study of a real photovoltaic power station under desert conditions: case study

10.11591/ijpeds.v17.i2.pp1369-1381
Fatma Bouchelga , Abderrahmane Khelfaoui , Abdeldjalil Dahbi
This work focuses on studying and analyzing the photovoltaic power plant of Oued Nechou located in the South of Algeria, in order to create its simulation model. This later can estimate its power production. To achieve this, all system parameters were introduced in the model according to the real data. Then, the characteristics of the photovoltaic panels were tested and plotted under different temperature and irradiation values to understand their influences on the electrical performances. In order to ensure the maximum energy production, photovoltaic panels were associated with converters controlled by a maximum power point tracking (MPPT) algorithm. Two different thin- film technologies of the PV panels (Amorphous silicon (a-Si) and cadmium telluride (CdTe) technologies) were simulated and tested under standard test conditions (STC) and compared with the real characteristics. The results show good accuracy. Subsequently, the real data of four seasons of the same year were introduced in the created model of Oued Nechou station. The obtained results of the simulation show that the performance of the produced energy is affected by the desert climatic conditions, especially the temperature and the solar radiation. However, the positive solar effect is higher than the negative thermal effect, which encourages investment by installing other photovoltaic stations in these areas known by the high and long duration of irradiance.
Volume: 17
Issue: 2
Page: 1369-1381
Publish at: 2026-06-01

Implementation of sliding control with washout filter in boost and buck converters

10.11591/ijpeds.v17.i2.pp1188-1198
Esteban Flórez Urrego , Fredy E. Hoyos , John E. Candelo-Becerra
This paper presents the analysis, design, and implementation of a two-stage power conversion system consisting of a boost converter and a buck converter. Both converters were controlled using a sliding-mode control based on a washout filter. The system was supplied with an alternating current (AC) voltage source that was rectified using a diode bridge. The main objectives are to improve the power factor (PF) in the boost stage and regulate the output voltage in the buck stage. In the first stage, sliding-mode control is applied to shape the input current according to the rectified voltage, increasing the PF and reducing harmonic distortion. In the second stage, the same control approach is used to maintain a constant output voltage under load variations and disturbances. This study includes the mathematical modeling of both converters, control design, and simulation results in PSIM. The results show that the proposed sliding-mode control strategy effectively enhances energy efficiency, stabilizes the output voltage, and significantly improves the PF, making it suitable for robust and efficient power conversion systems.
Volume: 17
Issue: 2
Page: 1188-1198
Publish at: 2026-06-01
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