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Nizirwan Anwar
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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 3,452 Documents
 303   304   305   306   307 
Static-gesture word recognition in Bangla sign language using convolutional neural network Kulsum Ara Lipi; Sumaita Faria Karim Adrita; Zannatul Ferdous Tunny; Abir Hasan Munna; Ahmedul Kabir
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 5: October 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i5.24096

Abstract

Sign language is the communication process of people with hearing impairments. For hearing-impaired communication in Bangladesh and parts of India, Bangla sign language (BSL) is the standard. While Bangla is one of the most widely spoken languages in the world, there is a scarcity of research in the field of BSL recognition. The few research works done so far focused on detecting BSL alphabets. To the best of our knowledge, no work on detecting BSL words has been conducted till now for the unavailability of BSL word dataset. In this research, a small static-gesture word dataset has been developed, and a deep learning-based method has been introduced that can detect BSL static-gesture words from images. The dataset, “BSLword” contains 30 static-gesture BSL words with 1200 images for training. The training is done using a multi-layered convolutional neural network with the Adam optimizer. OpenCV is used for image processing and TensorFlow is used to build the deep learning models. This system can recognize BSL static-gesture words with 92.50% accuracy on the word dataset.
Decision-tree-based machine learning for detecting coffee agroforestry using SPOT-7 I Made Khrisna Yoga Devandra; I Nengah Surati Jaya; Tatang Tiryana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 4: August 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i4.27747

Abstract

This study develops a decision-tree-based machine-learning (ML) approach to identify coffee agroforestry plants using SPOT-7 satellite imagery. The algorithm was developed by examining the combination of image indices derived from SPOT-7 and biophysical variables. Detection using spectral variables is often hampered by spectral similarity between vegetation cover classes. This study found that a ML method that combines spectral and biophysical variables can significantly improve overall accuracy, from 60.4% (using conventional spectral variables alone) to 94% (using integrated spectral-biophysical variables). For detecting and identifying agroforestry coffee classes typically found under tree canopies, the addition of the “land cover” variable published by the Ministry of Environment and Forestry contributes significantly to the classification of agroforestry coffee. Important variables identified in this model are normalized difference vegetation index (NDVI), visible difference vegetation index (VDVI), normalized red-green vegetation index (NRGI), elevation, and land cover.
Deep learning-based palm tree detection in unmanned aerial vehicle imagery with Mask R-CNN Agung Syetiawan; Danang Budi Susetyo; Yustisi Lumban-Gaol; Susilo Susilo; Mohammad Ardha; Yunus Susilo; Wahono Wahono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 1: February 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i1.26244

Abstract

Oil palm is highly valuable in tropical regions like Southeast Asia, including Indonesia. Therefore, accurate monitoring of oil palm trees is necessary for operational efficiency and reducing its environmental impact. Geospatial data, such as orthomosaic imagery from the unmanned aerial vehicle (UAV), can facilitate this goal. This research aims to integrate UAV data with deep learning algorithms, specifically Mask region-based convolutional neural network (R-CNN), to detect oil palm trees in Indonesia. We utilized Resnet-50 as the backbone and trained the model using data sampled from the template matching tool in eCognition. Considering factors like cloud shadows and other features, such as other plants, buildings, and road segments, we divided the study area into three containing different feature combinations in each. The Mask R-CNN model achieved an accuracy exceeding 80%, which is sufficient and makes it suitable for large-scale oil palm tree detection using high resolution images from UAV.
One to many (new scheme for symmetric cryptography) Alz Danny Wowor; Bambang Susanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 4: August 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i4.24789

Abstract

Symmetric cryptography will always produce the same ciphertext if the plaintext and the given key are the same repeatedly. This condition will make it easier for cryptanalysts to perform cryptanalysis. This research introduces a one-to-many cryptography scheme, which can produce different ciphertexts even if the input given is the same repeatedly. The one-to-many encryption scheme can produce several ciphertexts with differences of up to 50%. The avalanche effect test obtained an average of 52.20%, better than modern cryptography Blowfish by 25.46% and 6% better than advanced encryption standard (AES). One-to-many can produce different n-ciphertexts, which will certainly make it more difficult for cryptanalysts to perform cryptanalysis and require n-times longer to break than other symmetric cryptography.
Improved maximum distance on-demand routing algorithm routing protocol for vehicular ad hoc network network in an urban environment Dania Mohammed; Muhamad Bin Mansor; Goh Chin Hock
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.19283

Abstract

Vehicular ad hoc network (VANET) is a modern technology that has received great attention in the modern era due to daily road accidents. In VANET network it is difficult to design effective routing protocols due to the speed of movement of nodes and the rapid change in network architecture, and the purpose of routing protocols in the VANET network is to route data between vehicles (V2V), and between vehicles to infrastructure (V2I). Recently researchers have been interested in designing effective routing protocols for the VANET network because not all existing protocols are suitable for all traffic scenarios. Therefore, the focus of this paper will be on the maximum distance on-demand routing algorithm (MDORA) protocol and work on improving the protocol algorithm so that it is compatible with the urban environment. After that, the improved performance of the MDORA-without direction (MDORA-WD) protocol will be compared with the ad-hoc on-demand distance vector (AODV) protocol in terms of communication overhead, packet delivery ratio (PDR) and end to end (E2E) delay. The protocols will be simulated by MATLAB.
Optimized IMC with GWO algorithm and variable switching function for voltage regulation of SEPIC converter Reza Fazeli; Mohammad Haddad Zarif; Mahmoud Zadehbagheri; Tole Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 1: February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i1.27330

Abstract

With the growing application of single-ended primary-inductor converter (SEPIC) converters in power electronic systems, precise output voltage regulation under uncertainties and nonlinear conditions remains a significant challenge. Although internal model control (IMC) effectively addresses issues arising from unstable zeros and fixed time delays in non-minimum phase systems, its performance can degrade under large transient errors or sudden disturbances, leading to control signal saturation and instability. In this study, a modified IMC scheme is proposed, which integrates a variable switching function into the control structure. This addition enhances the robustness of the system by dynamically adapting the control effort to mitigate abrupt changes in the control signal and stabilize the output voltage. Furthermore, it prevents controller saturation during large-signal deviations, thereby improving transient response and maintaining system stability. The design parameters of the controller are optimized using the gray wolf algorithm to achieve an optimal balance between voltage overshoot, settling time, and closed-loop stability. Simulation results under various operating conditions confirm the superior performance of the proposed control method compared to conventional IMC.
Face recognition for smart door security access with convolutional neural network method Dhimas Tribuana; Hazriani Hazriani; Abdul Latief Arda
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 3: June 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i3.25946

Abstract

This study focuses on enhancing office security through a smart door system, designed to protect sensitive documents and critical data. Emphasizing exclusive access for authorized personnel, the system integrates advanced biometric authentication, predominantly facial recognition. The project's aim is to optimize face recognition using convolutional neural network (CNN) techniques, identifying the best preprocessing methods and hyperparameter settings. A significant aspect of the research involves developing a smart door system with remote authentication and control capabilities via internet connectivity. Employing transfer learning with MobileNet V2, the study presents a compact model tailored for the Raspberry Pi platform. The model utilizes a dataset with five facial recognition classes and an additional class for unknown faces, ensuring a diverse representation. The trained model achieved a high accuracy (0.9729) and low loss (0.09). System evaluation revealed an overall accuracy of 0.96, perfect recall (1.00), and a precision of 0.897. These results demonstrate the system's efficacy in secure access control, making it a viable solution for contemporary office environments
An evaluation of scintillation index in atmospheric turbulent for new super Lorentz vortex Gaussian beam Hussein Thary Khamees; Ahmed Saad Hussein; Nadhir Ibrahim Abdulkhaleq
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 1: February 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i1.22221

Abstract

Super Lorentz vortex Gaussian beam (SLVGB) is propagated via the turbulent atmosphere parameters. The benefit key of the SLVGB wave model is that the unlimited bandwidth wave and a spherical wave are involved. Additionally, Huygens Fresnel integral was used for schoolwork to study the propagation of SLVGB in a slant direction via a moderate turbulent medium. On the other hand, applying the crude international telecommunication union (ITU-R) model possible. Moreover, the Kolmogorov turbulent power spectrum model is applied, and the source field is dispersed by the zenith angle to the receiver plane. Additionally, examine the contour of the source field and the SLVGB intensity. To investigate various parameters such as source size, mode, scintillation index, topological charge, and others that are associated with the beam of super Lorentz vortex Gaussian are entirely understood, the outcomes were examined, and obtained other references to build the beam of slant path propagation in turbulent; the form constants are especially in comparison and matching. Our graphical findings indicate that the parameters happened randomly in the scintillation index and intensity of the SLVGB, resulting in a novel beam technical configuration. To summarize, this article is advantageous for remote sensing and uses an optical communications system and laser applications.
Prototype of alternate wetting and drying rice cultivation using internet of things for precision agriculture Akkachai Phuphanin; Metha Tasakorn
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 2: April 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i2.26529

Abstract

This study introduces a semi-automatic system for alternating wet and dry rice cultivation using internet of things (IoT) technology to enhance precision agriculture and address critical challenges in water resource management. The prototype consists of node and master devices powered by ESP32 microcontrollers integrated with sensors to monitor air temperature, humidity, and water levels. Communication between the devices is achieved through the low-latency, low-power encrypted secure protocol-network over wireless (ESP-NOW) protocol, enabling real-time monitoring and remote control of water pumps. Data collected by the system is displayed on ThinkSpeak servers and Nextion touch screens, aiding efficient irrigation and environmental management for farmers. Performance testing demonstrates that the system achieves reliable communication up to 115 meters with efficient energy consumption, operating for approximately two hours with a 3,000 mAh battery. By optimizing irrigation practices, the system reduces water waste while ensuring adequate crop hydration, promoting sustainable farming practices. This scalable IoT solution not only enhances productivity and resource efficiency but also contributes to broader efforts in agricultural sustainability by supporting precise environmental control and minimizing dependency on manual labor.
Zakah Management System Using Approach Classification Zulfajri Basri Hasanuddin; Syafruddin Syarif; Darniati Darniati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.5640

Abstract

The often problematic faced by Muslims are lack of understanding in calculating Zakah and determining the feasibility of compliant recipients based on Islamic Shari'a. This study aimed to establish Zakah management system to support calculation process based on Al Qaradhawi method, helping Board of Zakah in distributing Zakah funds to mustahik. The algorithm used for the classification of Zakah recipients is Naive Bayes. The classification was combination of discrete and continuous data which is conducted by experiments using feasible and unfeasible data as a novelty approach. The results have shown that the Naive Bayes method could solve the problem with 85% of average.

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