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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
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Overall outage event of self-sustaining low-power cooperative relaying networks Hoang-Sy Nguyen; Thanh-Khiet Bui
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.21925

Abstract

This paper investigates the implementation of the household low-power energy harvesting (LoPEH) wireless sensor networks (WSN) over log-normal fading channels. The relays are battery-operated and the stochastic harvested energy flow to the batteries is characterized with the Markov property of energy buffer status. The communication is established with the combination of direct link and cooperative relays. The best relay is chosen based on a relay selection (RS) scheme namely optimal relay selection (OPRS). It can be drawn that within a particular range of signal-to-noise ratio (SNR), the energy harvesting (EH) relay-aided protocol can remarkably boost the overall system performance. On the other hand, the study reports how increasing the log-normal channel variance can degenerate the in-studied EH relaying protocol.
Evaluating learning rate effects on long short-term memory for Indonesian sentiment classification Serly Eldina; Tekad Matulatan; Novrizal Fattah Fahmitra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27398

Abstract

Hyperparameter optimization is a crucial process for enhancing the performance of deep learning models, particularly in the context of Indonesian sentiment classification. This study examines the impact of varying learning rates on a long short-term memory (LSTM) architecture trained with the adaptive moment estimation (Adam) optimizer. The dataset comprises 9,295 Indonesian comments automatically labeled by the Indonesian Bidirectional Encoder Representations from Transformers (IndoBERT) model. Stratified k-fold cross-validation was employed to maintain class balance during training. Learning curves were analyzed to evaluate convergence and identify potential overfitting, while early stopping was applied when performance improvements became insignificant. The one-way analysis of variance (ANOVA) test (p-adj = 0.000575 < 0.05) revealed significant differences among the learning rate variations. Post-hoc analysis indicated the learning rates of 0.0001, 0.001, and 0.002 differ significantly from 0.02. Descriptive statistics showed that a learning rate of 0.001 was the most optimal, achieving the highest validation accuracy while maintaining a relatively low variance. Evaluation across two data categories demonstrated that lower learning rates (0.0001 and 0.002) achieved the best accuracy, 78.71% on in-domain data, whereas higher learning rates (0.01 and 0.02) performed better on cross-domain data with 36% accuracy. These findings highlight the crucial role of learning rate selection in determining model stability and generalization capability.
Unlocking insights from Ministry of Marine Affairs and Fisheries annual reports using LDA: a deep dive into SDG 14 Ahmad Marzuqi; Rezzy Eko Caraka; Prana Ugiana Gio; Rung Ching Chen; Maengseok Noh; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.26063

Abstract

Annual reports serve as vital instruments for government ministries and agencies, enabling transparency and accountability in managing state budgets (APBN) and activities, thereby fulfilling a crucial role in public accountability, particularly in the context of sustainable development goal (SDG) 14. However, due to their extensive nature, it becomes imperative to conduct topic modeling analysis to discern trends and topics within these reports. In this study, latent Dirichlet allocation (LDA), a prominent topic modeling technique, is employed to analyze the annual reports of the Ministry of Marine Affairs and Fisheries (KKP) Indonesia from 2015 to 2022. Utilizing the coherence score as an evaluation metric, we assess the quality of topic models across each report year. Our findings underscore the consistent emphasis on fisheries and marine-related initiatives, emphasizing their relevance to SDG 14 and Indonesia’s maritime landscape. Ultimately, this study offers valuable insights to inform strategic planning and decision-making processes within the KKP, contributing to the advancement of SDG 14 and promoting sustainable development in Indonesia’s fisheries and marine sectors.
Hybrid models for computing fault tolerance of IoT networks Bhupati Chokara; Sastry Kodanda Rama Jammalamadaka
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.v21i2.22429

Abstract

Many Internet of Things (IoT) - based networks are being built to develop applications spanning multiple domains. Many small to large devices connected in various ways increases the risk of IoT networks failing. Small devices in the devices layer frequently fail due to their small size and high usage. Intermittent failures of the IoT networks lead to catastrophes at times. The IoT systems must be designed to be fault-tolerant. Fault tolerance of IoT networks must be computable so that the same can be considered while designing IoT networks. However, the computation of fault tolerance of IoT networks is complex, especially when heterogeneous structures are used for building a specific IoT network. Fault tree-based models are not suitable for computing fault-tolerance of complex models, which requires probability assessment. Hybrid fault tolerance computing models have been presented in this paper that consider both linear and probabilistic methods of computing the fault tolerance considering many complex networking topologies used in each layer of IoT networks. The fault-tolerance computing models are formal methods that can be used to compute the fault tolerance of any IoT network built with any internal processing. The accuracy of fault tolerance computing is 12.9% higher than other methods.
Integration of image processing with 6-degrees-of-freedom robotic arm for advanced automation Paanthong Sroymuk; Paramust Juntarakod; Viroch Sukontanakarn
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.v23i3.26617

Abstract

This paper presents the design, construction, and development of a 6-degrees-of-freedom robotic arm, specifically tailored to the conditions at our university. The arm is powered by stepper motors and controlled via a programmable logic controller, while utilizing image processing data from a Raspberry Pi board. The objective of this research is to study automated pick-and-place operations, specifically targeting the handling of fruits such as oranges and apples. The system integrates advanced motion control techniques with vision-based object recognition to enable precise and reliable manipulation of the fruits. The robotic arm is equipped with an end-effector capable of handling objects with varying shapes and sizes, ensuring safe and efficient grasping and placement. Image processing algorithms are employed to identify and localize the fruits in real time, allowing the robotic arm to perform tasks in dynamic environments with minimal human intervention. Calibration, motion planning, and feedback control strategies are optimized to ensure high accuracy and prevent collisions or damage to the fruits. The system’s performance is evaluated through a series of experiments that demonstrate its capability to effectively pick and place oranges and apples, making it a promising solution for applications in agricultural automation and food processing.
Hoax classification and sentiment analysis of Indonesian news using Naive Bayes optimization Heru Agus Santoso; Eko Hari Rachmawanto; Adhitya Nugraha; Akbar Aji Nugroho; De Rosal Ignatius Moses Setiadi; Ruri Suko Basuki
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.v18i2.14744

Abstract

Currently, the spread of hoax news has increased significantly, especially on social media networks. Hoax news is very dangerous and can provoke readers. So, this requires special handling. This research proposed a hoax news detection system using searching, snippet and cosine similarity methods to classify hoax news. This method is proposed because the searching method does not require training data, so it is practical to use and always up to date. In addition, one of the drawbacks of the existing approaches is they are not equipped with a sentiment analysis feature. In our system, sentiment analysis is carried out after hoax news is detected. The goal is to extract the true hidden sentiment inside hoax whether positive sentiment or negative sentiment. In the process of sentiment analysis, the Naïve Bayes (NB) method was used which was optimized using the Particle Swarm Optimization (PSO) method. Based on the results of experiment on 30 hoax news samples that are widely spread on social media networks, the average of hoax news detection reaches 77% of accuracy, where each news is correctly identified as a hoax in the range between 66% and 91% of accuracy. In addition, the proposed sentiment analysis method proved to has a better performance than the previous analysis sentiment method.
Smart stick for blind people with wireless emergency notification Yasir Hashim; Alaa Ghazi Abdulbaqi
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.v22i1.24972

Abstract

This effort develops and uses a smart stick to help blind individuals walk more safely and avoid hazards. This research paper involved to develop smart stick for blind people to help them to walk safely by avoiding obstructions, and at emergency conditions sent their location to person in charge like a doctor or relatives to help them accordingly. Three ultrasonic sensors are used in the proposed device’s architecture to detect obstructions at three different heights, low, mid, and high obstructions using speaker to alert the blind person. An emergency message with the location of the blind person’s phone is sent through a mobile app to the doctor or person in charge whenever the designed smart stick’s emergency button is touched, or the stick is dropped down. The Arduino Uno platform, Bluetooth model, MPU-6050 3-axis gyroscope as a position sensor, and microSd card module has been used to effectively implement the stick. At the testing stage, the device gave good results. The user received notifications in the form of voice messages and vibrations from the smart stick when it detects things or obstacles in front of them. Additionally, even though they cannot directly activate it, the automated emergency condition has been detection and activated.
Design visual studio based GUI applications on-grid connected rooftop photovoltaic measurement Habib Satria; Syafii Syafii; Rudi Salam; Moranain Mungkin; Welly Yandi
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.v20i4.23302

Abstract

This article describes the design of a data system to integrate energy conversion from photovoltaic measurements connected to the power grid. The software used is visual studio, while the hardware uses polycrystalline photovoltaic (PV) with a capacity of 2.08 kW and several sensors that have been integrated into Arduino. Parameter data in measuring the performance of this PV system consists of temperature and humidity sensors to measure the panel surface, direct current (DC) current sensor, DC voltage sensor. To measure the current and voltage sourced from the electricity network, the module (PZEM-004T) is used. Measurements are designed using a graphical user interface (GUI) on a Visual Studio application that has been interfaced through Arduino programming. The data output on the sensor measurement will simultaneously record the circuit that has been connected to the solar panel and then display it visually in the form of tables and graphs in real time with a delay of 1 minute. The results of PV on grid measurements in sunny weather conditions obtained the maximum value of all measurements with a DC voltage of 221 V, while for an alternating current (AC) voltage of 231.60 V, the DC value reached 1827.17 W while the AC power was 1681 W.
A system modeling approach for business intelligence system design in the Indonesian kite string industry Hendry Anggraito; Rina Fitriana; Dadan Umar Daihani; Emelia Sari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 3: June 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i3.27573

Abstract

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.
Light weight dual polarized horn antenna for polarimetry C-band synthetic aperture radar sensor onboard UAV Agus Hendra Wahyudi; Farohaji Kurniawan; Bambang Setiadi; Agus Wiyono; Satria Arief Aditya; Wahyu Widada; Effendi Dodi Arisandi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.25718

Abstract

Unmanned aerial vehicles (UAVs) can collect earth surface information with synthetic aperture radar (SAR) sensors during night, day, and bad weather. However, UAVs have only limited volume and weight for the SAR payload. A very light dual circularly polarized pyramid horn antenna was developed in order to improve sense capability in UAV dual polarimetry SAR images. The pyramid horn was designed and simulated in computer simulation technology (CST) 2022. The horn was capable of producing two circular polarizations right-hand circular polarization (RHCP) and left-hand circular polarization (LHCP) alternately using a three stepped septum polarizer and coaxial probe feed on two sides of the waveguide. The results show that the horn antenna was capable of having a wide S11 and S22 bandwidth from 4 GHz to 6.7 GHz. The horn was capable of producing two circular polarizations with an axial ratio below 3 dB from 4.4 GHz to 6.4 GHz. This gain horn antenna was relatively stable in the range of 15 dBiC with a reasonably narrow 3 dB beamwidth of 28° both RHCP and LHCP polarisation in E and H fields respectively.

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