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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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Design and verification of daisy chain serial peripheral interface using system Verilog and universal verification methodology Rajesh Thumma; Pilli Prashanth
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.v21i1.24093

Abstract

Serial peripheral interface (SPI) transfers the data between electronic devices like micro controllers and other peripherals. SPI consists of two control lines: select signal and clock signal, and two data lines: input and output. In single master-single slave, the communication is in between master and slave only which will make the design complex and costly, area will increase. In regular SPI mode, the number of chip-select lines is increased if the number of slaves increases. Due to this, the input data received by the master from the slaves are corrupted at master input slave output (MISO). The proposed daisy chain method is used to overcome this problem. The daisy chain method requires only one chip select line at master compared to the regular SPI mode. When the chip-select line is active low, all the slaves are active, and the clock is initiated to all the slaves to transfer the data from the master to the first slave through the master output slave input (MOSI). In this paper, the daisy-chain SPI is designed and developed using Verilog. The proposed design is verified using system Verilog (SV) and universal verification methodology (UVM) in QuestaSim.
Advanced crop yield prediction using machine learning and deep learning: a comprehensive review Ayush Anand; Kavita Jhajharia
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.v23i2.26621

Abstract

The advancement of machine learning (ML) and deep learning (DL) techniques has significantly improved crop yield prediction, making it more accurate and reliable. In this review, the implementation of ML and DL algorithms for crop yield prediction is thoroughly investigated, focusing on their crucial role in enhancing crop productivity. Along with ML and DL algorithms examine, the review analyses the use of remote sensing technologies, such as satellite and drone data, in providing high-resolution inputs essential for accurate yield predictions. The study identifies the state of art algorithms, most used features, data sources and evaluation metrics, providing a comparison of ML and DL. The findings indicate that DL models are more effective with large datasets, while ML models remain robust for smaller datasets. The future directions are proposed to develop the generalised models for different crops and regions. The review aims to assist researchers by summarising state of art techniques and identifying the present.
The prediction of mobile data traffic based on the ARIMA model and disruptive formula in industry 4.0: A case study in Jakarta, Indonesia Ajib Setyo Arifin; Muhammad Idham Habibie
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.v18i2.12989

Abstract

Disruptive technologies, which are caused by the cellular evolution including the Internet of Things (IoT), have significantly contributed data traffic to the mobile telecommunication network in the era of Industry 4.0. These technologies cause erroneous predictions prompting mobile operators to upgrade their network, which leads to revenue loss. Besides, the inaccuracy of network prediction also creates a bottleneck problem that affects the performance of the telecommunication network, especially on the mobile backhaul. We propose a new technique to predict more accurate data traffic. This research used a univariate Autoregressive Integrated Moving Average (ARIMA) model combined with a new disruptive formula. Another model, called a disruptive formula, uses a judgmental approach based on four variables: Political, Economic, Social, Technological (PEST), cost, time to market, and market share. The disruptive formula amplifies the ARIMA calculation as a new combination formula from the judgmental and statistical approach. The results show that the disruptive formula combined with the ARIMA model has a low error in mobile data forecasting compared to the conventional ARIMA. The conventional ARIMA shows the average mobile data traffic to be 49.19 Mb/s and 156.93 Mb/s for the 3G and 4G, respectively; whereas the ARIMA with disruptive formula shows more optimized traffic, reaching 56.72 Mb/s and 199.73 Mb/s. The higher values in the ARIMA with disruptive formula are closest to the prediction of the mobile data forecast. This result suggests that the combination of statistical and computational approach provide more accurate prediction method for the mobile backhaul networks.
Comprehensive review of the human body communication system for wireless body area network applications Chaitra Soppinahally Nataraju; Desai Karanam Sreekantha; Kanduri V S S S S Sairam
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 6: December 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i6.24982

Abstract

The body area networks (BAN) structure is one of the advancements in health monitoring innovations and the sharp rise in healthcare demand. With the help of a network of constantly running sensors, BAN technology aims to monitor vital physiological and physical features like accessibility, respiration, and blood sugar levels. The achievement of BAN technology depends on wireless communication since it gives the user flexibility and versatility. Most BAN solutions have effectively employed radio frequency (RF) wireless technology, although these systems are battery-intensive, prone to electromagnetic interference, and have security weaknesses. The human body is the signal transmission medium in the alternative wireless communication technology called human body communication (HBC). HBC possesses traits that could logically deal with the problems with RF for wireless body area networks (WBAN) technology. This overview looks at the ongoing research in this field and highlights the principles of the HBC, the most recent studies of HBC, human body coupling approaches, the designs of HBC transceivers, and the unresolved research issues. HBC provides promising future possibilities for making WBAN technologies more useful.
Empirical measurement for path loss characteristics at multiple frequency bands from 2.2 to 14.6 GHz in chamber room Atikah Balqis Basri; Khairayu Badron; Ahmad Fadzil Ismail; Abadi Chanik
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.v20i3.23306

Abstract

Free space path loss (FSPL) is the loss of electromagnetic signal strength. This loss is caused by the line-of-sight path through free space. Even in a line of sight (LoS) indoor single layer, as the distance increases, the path loss in the 1 GHz frequency band also exceeds the free space path loss. This is because the first Fresnel zone is shielded by the floor and ceiling. To improve the measurement results, a fully covered anechoic chamber is used in this empirical measurement. The measurement is based on multiple frequency bands from 2.23201 GHz to 14.685 GHz. This article details how to achieve it. Measurements are made to establish the correlation between the power transmit value and the frequency value. This movement involves the establishment of microwave link transmissions. Use a signal generator to control the transmit power and use a vector network analyzer in the electromagnetic compatibility (EMC) room to measure the received power level. Appropriate analysis that determines the correlation. The logarithm function developed based on the empirical experiment conducted, the result suggested the formulation of . These findings enable people to understand the required FSPL value as the power transmission and frequency change during each measurement.
Design and evaluation of a low‑cost real‑time fluid-level monitoring system for fuel stations Jovianne Birindwa; Stéphane Birindwa Birhashwirwa
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.v24i2.27548

Abstract

Accurate fluid level management in fuel stations is hampered by inventory errors, delayed shortage detection and costly proprietary sensors. We designed and built a low‑cost, open‑source monitoring system using an Arduino Uno, an HC‑SR04 ultrasonic sensor, a NodeMCU ESP8266 and a DHT11 temperature sensor. Validation was restricted to static short-term conditions, with a prototype tested in a 200 cm tank over 62 hours and 32 paired measurements collected at two-hour intervals. Prototype readings were compared with dipstick measurements after temperature compensation. The system achieved a mean error of 0.03 cm, a mean absolute error of 0.91 cm, a standard deviation of 1.06 cm and a root‑mean‑square error of 1.05 cm, with a 95 % confidence interval of ±0.37 cm. These results demonstrate that a calibrated and temperature‑compensated ultrasonic sensor can deliver centimetre‑level accuracy suitable for inventory management in resource‑constrained fuel stations. Future work will extend validation to dynamic transfers, sloshing/vibration, humidity effects, and long-term drift in operational tanks.
Smart hydroponic agriculture using genetic algorithm based k-nearest neighbors Budi Sutrisno; Nico Surantha
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.v22i5.25853

Abstract

In this research, researcher has implemented supervised machine learning, namely k-nearest neighbor (k-NN) which is optimized using genetic algorithms, and the internet of things (IoT) on the nutrient film technique (NFT) hydroponic system. The aim of this research is to improve the accuracy of classification of nutrient and light conditions in NFT system, and evaluating the harvest of hydroponic farming. The dataset was obtained by observing and recording nutritional and light conditions using sensors for 35 days during the growing period of lettuce in the NFT system, thus obtaining 1,680 data. Then, a training dataset is created based on that dataset. The system architecture is divided into 3 parts, namely the sensor system, data processing, and actuator system. The conclusion of this research is the IoT can be used to monitor the nutritional and light conditions of NFT system in real time and automatic control actions can be carried out using actuators controlled by the Raspberry Pi, the impact of applying the k-NN algorithm and the genetic algorithms is the accuracy of classifying nutritional and light conditions is 92%, the lettuce in a NFT system controlled by the system grow better than the lettuce in a NFT system controlled manually.
A bandwidth reconfigurable antenna for devices in low UWB-applications Mohamed Bikrat; Seddik Bri
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.v21i2.24256

Abstract

A reconfigurable simple design planar antenna for ultra-wideband applications is proposed, with E-shaped slot contained four narrow vertical slots that has the capacity of switching using four PIN diodes with a ground plan and a microstrip power line. An additional circularly polarized (CP) band is obtained by changing the on/off states of the PIN diodes. Moreover, the four PIN diodes are attached in the middle of the E-shape slot and used to switch the radiation flow of the patch. For validation, a patch antenna design is offered, based on a distinctive situation analysis. The antenna offers the low-ultra-wideband (UWB) frequencies band. Therefore, the switch of the operating states of PIN diodes gives us a good bandwidth re-configurability. In addition, with this flexible configuration we achieve a good -10 dB bandwidths with the ability to change the bandwith ranges from narrow-band 2.3 GHz to wide-band 3.1 GHz. Also, we achieve a large band for 3 dB AR is 2.57 GHz.
Optimizing signal conversion in uniform FBGs with InGaAs photodetectors for medical sensors Tengku Emrinaldi; Bambang Widiyatmoko; Bunga Meyzia; Sumiaty Ambran; Saktioto Saktioto; Mohamad Syahadi; Agitta Rianaris; Dwi Hanto
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.v23i4.26164

Abstract

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.
Short-term photovoltaics power forecasting using Jordan recurrent neural network in Surabaya Aji Akbar Firdaus; Riky Tri Yunardi; Eva Inaiyah Agustin; Tesa Eranti Putri; Dimas Okky Anggriawan
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.v18i2.14816

Abstract

Photovoltaic (PV) is a renewable electric energy generator that utilizes solar energy. PV is very suitable to be developed in Surabaya, Indonesia. Because Indonesia is located around the equator which has 2 seasons, namely the rainy season and the dry season. The dry season in Indonesia occurs in April to September. The power generated by PV is highly dependent on temperature and solar radiation. Therefore, accurate forecasting of short-term PV power is important for system reliability and large-scale PV development to overcome the power generated by intermittent PV. This paper proposes the Jordan recurrent neural network (JRNN) to predict short-term PV power based on temperature and solar radiation. JRNN is the development of artificial neural networks (ANN) that have feedback at each output of each layer. The samples of temperature and solar radiation were obtained from April until September in Surabaya. From the results of the training simulation, the mean square error (MSE) and mean absolute percentage error (MAPE) values were obtained at 1.3311 and 34.8820, respectively. The results of testing simulation, MSE and MAPE values were obtained at 0.9858 and 1.3311, with a time of 4.591204. The forecasting has minimized significant errors and short processing times.

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