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Contact Name
Nizirwan Anwar
Contact Email
nizirwan.anwar@esaunggul.ac.id
Phone
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Journal Mail Official
telkomnika@ee.uad.ac.id
Editorial Address
Ahmad Yani st. (Southern Ring Road), Tamanan, Banguntapan, Bantul, Yogyakarta 55191, Indonesia
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Daerah istimewa yogyakarta
INDONESIA
TELKOMNIKA (Telecommunication Computing Electronics and Control)
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
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)
Articles 3,452 Documents
Analysis comparison, calibration, and application of low-cost soil moisture in smart agriculture based on internet of things Beny Agustirandi; Inayatul Inayah; Nina Siti Aminah; Maman Budiman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 5: October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i5.25703

Abstract

The gravimetric method is one of the most accurate for determining soil water content (SWC). Several low-cost sensors have been developed to simplify measuring water content in soil by measuring soil moisture. However, the sensor must be calibrated to determine soil moisture parameters accurately. In this research, comparative analysis, and calibration of resistive and capacitive low-cost sensors were carried out. The calibration method for each sensor uses the gravimetric water content (GWC) and volumetric water content (VWC) methods. Measuring changes in SWC using sensors is performed in real time based on internet of things (IoT). Based on the measurements of the capacitive, resistive type 1, and resistive type 2 sensors with three repetitions, the linear regression R2 values were obtained at 0.980, 0.827, and 0.942, respectively. Furthermore, a stability test is carried out to see how stable the sensor is when making measurements over a long period. The result is that the capacitive, resistive type 1, and resistive type 2 sensors have errors 1.971×10-4, 7.001×10-4, and 6.270×10-4. Based on the results obtained, capacitive sensors have the highest level of accuracy and stability. Furthermore, capacitive sensors are applied to IoT-based agriculture with long range (LoRa) as communication data.
Enhance iris segmentation method for person recognition based on image processing techniques Israa A. Hassan; Suhad A. Ali; Hadab Khalid Obayes
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23567

Abstract

The limitation of traditional iris recognition systems to process iris images captured in unconstraint environments is a breakthrough. Automatic iris recognition has to face unpredictable variations of iris images in real-world applications. For example, the most challenging problems are related to the severe noise effects that are inherent to these unconstrained iris recognition systems, varying illumination, obstruction of the upper or lower eyelids, the eyelash overlap with the iris region, specular highlights on pupils which come from a spot of light during captured the image, and decentralization of iris image which caused by the person’s gaze. Iris segmentation is one of the most important processes in iris recognition. Due to the different types of noise in the eye image, the segmentation result may be erroneous. To solve this problem, this paper develops an efficient iris segmentation algorithm using image processing techniques. Firstly, the outer boundary segmentation of the iris problem is solved. Then the pupil boundary is detected. Testes are done on the Chinese Academy of Sciences’ Institute of Automation (CASIA) database. Experimental results indicate that the proposed algorithm is efficient and effective in terms of iris segmentation and reduction of time processing. The accuracy results for both datasets (CASIA-V1 and V4) are 100% and 99.16 respectively.
Recognition and understanding of construction safety signs by final year engineering students Frank Kulor; Elisha D. Markus; Michael W. Apprey; Divine Novieto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 3: June 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i3.27076

Abstract

This study assessed the recognition and understanding of construction safety signs among final-year Higher National Diploma, Building Technology (BT) and Electrical/Electronic Engineering (EE) students at a technical university in Ghana. The purpose was to evaluate their awareness of safety signs, addressing gaps in existing research and providing updated data to enhance occupational safety training. A descriptive statistical methodology was employed, utilizing purposive sampling to survey 137 students via structured questionnaires. Data were analyzed using SPSS v16 and compared against ISO 3864 and ANSI Z5353 standards. Results revealed varying comprehension rates: prohibition signs (61.71%), general warning signs (71.08%), mandatory signs (78.32%), emergency escape signs (81.4%), firefighting signs (86.9%), and chemical labeling signs (77.98%). While mean scores exceeded benchmark thresholds, low response rates for specific signs indicated significant knowledge gaps. The study concludes that unfamiliarity with safety signs persists due to insufficient training and curricular emphasis. Recommendations include revising academic syllabi under Ghana Tertiary Education Commission and National Board for Technical Examinations guidelines to integrate safety education, alongside industry partnerships for practical training during internships. These measures aim to reduce workplace accidents and improve safety compliance among future engineers.
Comparing random forest and support vector machines for breast cancer classification Chelvian Aroef; Yuda Rivan; Zuherman Rustam
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14785

Abstract

There are more than 100 types of cancer around the world with different symptoms and difficulty in predicting itsappearance in a person due to its random and sudden attack method. However, the appearance of cancer is generally marked by the growth of some abnormal cell. Someone might be diagnosed early and quickly treated, but the cancerous cell most times hides in the body of its victim and reappear, only to kill its sufferer. One of the most common cancers is breast cancer. According to Ministry of Health, in 2018, breast cancer attacked 42 out of every 100.000 people in Indonesia with approximately 17 deaths. In addition, the Ministry recorded a yearly increase in cancer patients. Therefore, there is adequate need to be able to determine those affected by this disease. This study applied the Boruta feature selection to determine the most important features in making a machine learning model. Furthermore, the Random Forest (RF) and Support Vector Machines (SVM) were the machine learning model used, with highest accuracies of 90% and 95% respectively. From the results obtained, the SVM is a better model than random forest in terms of accuracy.
Synthesis of reduced graphene oxide decotate Cu2S nanoparticles for cathode of quantum dot solar cell Le Doan Duy; Le Thi Ngoc Tu; Le Tien Dat
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 1: February 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i1.25238

Abstract

In this paper, the results of making a reduced graphene oxide cathode electrode with Cu2S nanoparticles are shown so that it can be used as a counter electrode in quantum dot solar cells to replace other counter electrodes. An rGO-Cu2S paste obtained by hydrolysis was scanned onto the surface of the fluorine-doped tin oxide (FTO) conductive substrate when bound to Cu2S nano by a screen-printing process, then calcined at 350 °C to crystallize the film. Following calcination, the film was examined for structure using energy-dispersive X-ray (EDX) and X-ray diffraction (XRD) spectroscopy, as well as for type and particle size using scanning and transmission electron microscopy and transmission electron microscopy, respectively. Mott-schottky measurement is used to determine the semiconductor and carrier concentrations in the film, and an electrochemical device is used to assess the electrodes redox capacity in a polysulfide electrolyte solution. The operability of the rGO-Cu2S cathode at the peak of the current density in the C-V curve was 24 mA/cm2, a 30-fold increase compared to that of the Cu2S electrode. This result shows that the efficiency, Voc, FF, Jsc are 4.92%, 0.525 V, 0.418, and 22.4 mA/cm2, respectively.
Resource placement strategy optimization for IoT oriented monitoring application Saad-Eddine Chafi; Younes Balboul; Mohammed Fattah; Said Mazer; Moulhime El Bekkali; Benaissa Bernoussi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 4: August 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i4.23762

Abstract

Cloud computing and the low power wide area network (LPWAN) network represent the key infrastructures for developing intelligent solutions based on the internet of things (IoT). However, the diversity of use cases and deployment scenarios of IoT in the different domains makes optimizing IoT-based cloud solutions a major challenge. The cloud solution’s cost increases with the increase in central processing unit (CPU) resources and energy consumption. The optimal use of edge material resources in industrial solutions will reduce the consumption of resources and thus optimize cloud infrastructure costs in terms of resources and energy consumption. The article presents the network and application architecture of an IoT monitoring solution based on cloud services. Then, we study the integration of IoT services based on application placement strategies on the fog cloud compared to the traditional centralized cloud strategy. Simulations evaluate the scenarios with the iFogSim simulator and the analyzed results compare the traditional strategy with the cloud-fog. The results show that cost and energy consumption in the cloud can be significantly reduced by processing the application at the end devices level with respect to the possible limit of CPU processing power for each IoT end device. Latency and network usage respect quality of service constraints in cloud-fog placement for this type of monitoring-oriented IoT application.
Energy scavenging-aided NOMA uplink communications: performance analysis Huu Q. Tran; Khuong Ho-Van
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 4: August 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i4.26822

Abstract

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.
Genomic repeats detection using Boyer-Moore algorithm on Apache Spark Streaming Lala Septem Riza; Farhan Dhiyaa Pratama; Erna Piantari; Mahmoud Fahsi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14883

Abstract

Genomic repeats, i.e., pattern searching in the string processing process to find repeated base pairs in the order of Deoxyribonucleic Acid (DNA), requires a long processing time. This research builds a big-data computational model to look for patterns in strings by modifying and implementing the Boyer-Moore algorithm on Apache Spark Streaming for human DNA sequences from the Ensemble site. Moreover, we perform some experiments on cloud computing by varying different specifications of computer clusters with involving datasets of human DNA sequences. The results obtained show that the proposed computational model on Apache Spark Streaming is faster than standalone computing and parallel computing with multicore. Therefore, it can be stated that the main contribution in this research, which is to develop a computational model for reducing the computational costs, has been achieved.
An approach for liver cancer detection from histopathology images using hybrid pre-trained models Nuthanakanti Bhaskar; Jangala Sasi Kiran; Suma Satyanarayan; Gaddam Divya; Kotagiri Srujan Raju; Murali Kanthi; Raj Kumar Patra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.25588

Abstract

Histopathological image analysis (HIA) plays an essential role in detecting cancer cell development, but it is time-consuming, prone to inaccuracy, and dependent on pathologist competence. This paper proposes an automated HIA that uses deep learning to improve accuracy and efficiency in liver cancer cell growth. The model uses whole slide image (WSI) input, open computer vision (OpenCV) libraries for image preprocessing, ResNet50 for patch-level feature extraction, and multiple instances learning for image-level classification. The suggested approach accurately distinguishes liver histopathological pictures as cancerous or non-cancerous. Assisting in the early detection of liver cancer cell development with potential invasion or spread.
Advanced signal transformation techniques to improve spectral efficiency in visible light communication systems Shahir Fleyeh Nawaf; Ammar Bouallegue; Sameh Najeh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 6: December 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i6.26835

Abstract

Visible light communication (VLC) offers high-speed wireless communication using the visible light spectrum. Achieving high spectral efficiency while maintaining a low bit error rate (BER) remains a challenge. This paper explores the use of quadrature amplitude modulation (QAM) combined with orthogonal frequency division multiplexing (OFDM) to address these challenges. Matrix laboratory (MATLAB) simulations show that QAM-OFDM achieves a BER of 0.001 at comparable signal-to-noise ratios (SNR), outperforming traditional hermitian symmetry (HS), complex signal mapping (CSM), and quad-light emitting diode (LED) complex modulation (QCM) techniques. Unlike CSM, and QCM, which increase complexity, and BER, QAM-OFDM efficiently utilizes available bandwidth, reducing errors, and enhancing spectral efficiency. The study concludes, that QAM-OFDM happens to be the optimal solution for the future VLC systems, offering better performance within both efficiency, and reliability.

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