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Eko Fajar Cahyadi
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Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Institut Teknologi Telkom Purwokerto Jl. D. I. Panjaitan, No. 128, Purwokerto 53147, Indonesia
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Jurnal INFOTEL
Published by Universitas Telkom
ISSN : 20853688     EISSN : 24600997     DOI : https://doi.org/10.20895/infotel.v15i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published online in 2012. The aims of Jurnal INFOTEL are to disseminate research results and to improve the productivity of scientific publications. Jurnal INFOTEL is published quarterly in February, May, August, and November. Starting in 2018, Jurnal INFOTEL uses English as the primary language.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 473 Documents
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Sistem radar lokasi koheren multi-pasif untuk jangkauan deteksi dan resolusi range-doppler di Tarakan Syahfrizal Tahcfulloh; Muhammad Jeki; Antonius Antonius
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1008

Abstract

The presence of many radio frequency illuminators in an area provides an opportunity to be used as a transmission source for a passive radar system called a passive coherent locator (PCL). Unlike the active radar, the passive radar provides advantages such as low cost without an active transmitter, potential for broad range measurements, portable in construction, anti-detectable by active radar or electronic counter measures (ECM), etc. Just like other areas where there are many PCL in Tarakan such as FM radio transmission (RRI), many base-stations (BTS) from 4G-LTE network, digital TV transmission, access-point (AP) from wireless fidelity (WiFi), and so on. This paper will present and analyze all of these PCLs which include predictions of performance and ambiguity function (AF). Performance prediction is related to range detection which provides information about target detection range, radar cross section, and range-velocity resolution. While AF analyzes the transmit waveform of all PCL which gives a limit of resolution to the range and Doppler of adjacent targets. The results of the evaluation and analysis of performance predictions show that FM radio transmission (RRI) has a range and velocity resolution of 1 km and 12 m/s, respectively and the detection range at a maximum SNR of 15 dB is around 4 km. While the results of the AF evaluation on the PCL obtained range and Doppler resolution of around 2.73 km and 500 Hz, respectively.
Analysis of voltage and frequency stability of electric power system network with photovoltaic-based generation penetration Rusilawati Rusilawati; Irfan Irfan; Gusti Eddy Wirapratama; Istiyo Winarno
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1022

Abstract

The operation of Distributed Generation (DG) with renewable energy sources integrated with distribution networks through microgrids poses challenges in terms of operation and control. If this is left unchecked, it can have a negative impact on system security and reliability in terms of voltage and frequency stability that will be disrupted because of frequent variations in power production and loading levels. This study investigates voltage and frequency stability in microgrids because of the penetration of DG with photovoltaic (PV) renewable energy sources in the power system using the Virtual Synchronous Generator (VSG) control technique. The VSG is a control alteration that enhances the capabilities of the power system so that voltage and frequency stability can be preserved and improved. The VSG control method with additional damping controllers that increase inertia with additional virtual inertia is used to simulate the speed of restoration of voltage and frequency stability of the power system due to the penetration of PV-based power plants. The simulation results show that at the time of penetration of PV-based power plants in the power system, there is a momentary instability in voltage and frequency, but it is immediately dampened by VSG control and can be quickly restored so that the stability of voltage and frequency is maintained.
Combining inception-V3 and support vector machine for garbage classification Intan Nurma Yulita; Firman Ardiansyah; Muhammad Rasyid Ramdhani; Mokhamad Arfan Wicaksono; Agus Trisanto; Asep Sholahuddin
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1027

Abstract

The global volume of trash has increased due to population growth and consumption, with a growing variety of materials and materials being generated. Inadequate garbage disposal practices, particularly in plastics, have led to environmental contamination and pollution in various regions. Artificial Intelligence (AI) technologies, particularly in machine learning, have demonstrated significant potential in trash sorting, particularly in the realm of machine learning. The Inception-V3 model and Support Vector Machines (SVM) are used in this study to extract relevant features and classify garbage categories. The Inception-V3 and SVM combination exhibits superior performance, with greater accuracy and F1 score compared to other methods. The radial basis function (RBF) kernel is the most optimal model of SVM, but it faces challenges in accurately categorizing the "trash" category due to limited data and resemblance to the "paper" class. The system developed in this study has a high level of effectiveness, with superior accuracy and F1 scores of 0.876 and 0.874, respectively.
Foveal Avascular Zone Image Encryption using Pixel Scrambling Combination Technique for Medical Image Security Purnamasari, Dewi; Herlinudinkhaji, Didin; Dewi, Astrie Kusuma; Mauludin, Muhammad Zairon
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.1029

Abstract

Data theft from year to year has increased in the era of big data and society 5.0. One area that requires data security is patient medical data. Medical image data security must be done to protect medical data security from data theft by third parties so that they cannot access the data. The development of Diabetic Retinopathy (DR) is also increasing every year. Determining the severity of DR is done by detecting the Foveal Avascular Zone (FAZ). Encryption is the process of changing a plain image into a cipher image. In this study, we compared the results of image quality and encryption time between the Vigenere Cipher method and a combination of pixel scrambling. The average encryption time of the tested FAZ images is 3.20 seconds. This result proves that the pixel combination method has a faster encryption time than the Vigenere Cipher. Vigenere Cipher encryption time is 4.96 seconds. The existence of the FAZ area with the pixel combination randomization method of the encryption process is also invisible, so third parties will not know about its existence.
Data preprocessing approach for machine learning-based sentiment classification Sunneng Sandino Berutu; Haeni Budiati; Jatmika Jatmika; Fornieli Gulo
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1030

Abstract

Public sentiment regarding a particular issue, product, activity, or organization can be measured and monitored with an application based on artificial intelligence. The data come from comments circulating on social media. However, the rules for writing comments on social media have yet to be standardized, so non-standard words often appear in these comments. Non-standard words affect the determination of sentiment into positive, negative, and neutral categories. Therefore, this study proposes a data preprocessing approach by inserting the Rabin-Karp algorithm to improve non-standard words. This research consists of several stages, namely crawling data, data preprocessing, feature extraction, model development (based on Naïve Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT) methods), and analysis of the results. The experimental results showed that the proposed approach influences the determination of the sentiment category composition. Then, model testing results showed that all models obtain the highest value in the Positive category for the precision parameter with a value 1. All models in the Neutral category obtain the highest value for the recall parameter, almost reaching 1. All models in the Neutral category achieve the highest value of the f1-score parameter, with an average value of 0.95. In general, the results of the performance analysis of the classification model showed that the NB and SVM-based models have better performance than the DT method.
The intelligent decision model for determine the best path of transportation on smart city using random forest algorithm and bayesian optimization (RF-BO) Ahmad Fali Oklilas; Milda Kamilia; Abdurahman abdurahman; Bita Parga Zen; Ari Widodo
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1036

Abstract

This study investigates various approaches and algorithms in the context of object detection and best path determination for managing vehicular traffic in an urban environment, particularly in Palembang city. This research is a step towards the development of smart city concept. In the object detection analysis, we applied the YOLOv3 method on video footage to identify vehicles, resulting in mAP accuracy rates between 72.72% to 79.35% for both motorcycle and car categories. The total detection accuracy of the model reached 76.03%. Next, we adopted the Random Forest algorithm to classify traffic conditions into three classes: smooth, moderate, and congested. After optimizing the algorithm with Bayesian Optimization, the model accuracy increased from 89% to 92%, while the classification accuracy increased from 91.66% to 92.36%. Results from the application of the A* Heuristic Search algorithm revealed that lane 5 (from SMK PGRI 1 Palembang to Bom Baru Jl Perintis Kemerdekaan Arah Charitas (STMIK MBC)) was selected most frequently in 9 out of 12time trials. The selection of this route was based on an evaluation of traffic levels that tended to be "smooth" and the shortest travel distance compared to other alternative routes. The decision in choosing the optimal path also considers the road width factor, where wider roads have the potential to reduce traffic density and the risk of congestion.
LSTM forecast of volatile national strategic food commodities Herlina Jayadianti; Vynska Amalia Permadi; Partoyo Partoyo
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1037

Abstract

Using the Long Short-Term Memory (LSTM) forecast, this study suggested a short-term projection model for national critical food pricing commodities. The model was trained using historical time-series data from each commodity price over the previous three years. The results demonstrated that the proposed LSTM architecture model was generalizable to all commodities and performed well in the majority of cases. This result indicates that the model is resilient and can be used to forecast commodity prices and offer accurate forecasts for most of the ten volatile national strategic foods, with an error value of less than 0.01 and an accuracy value of >95%. The model, however, failed to recognize the pricing pattern in cooking oil and beef commodities, both of which had increasing trend patterns. This shows that the model may be unable to effectively estimate commodity prices in the face of fast price fluctuations. The magnitude and quality of the dataset hampered the investigation. The time period selected also influenced the study. Future research should employ a more extensive and diversified dataset to increase the model's performance, allow it to learn more patterns and make more accurate predictions, and could use a more extended lookup date to improve forecast accuracy. This would enable the model to account for more recent pricing changes. Despite the limitations, the results of this study are promising and could be used to develop a more accurate and reliable food price prediction model. Policymakers and stakeholders could use the model to make informed food prices and inflation decisions.
Microcontroller-based smart foot as an educational tool for teaching reflexology nerve points to visually impaired massage trainers and trainees Dina Fitriana Rosyada; Krida Tri Wahyuli; Muhammad Hasani; Nur Rokhman
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1042

Abstract

The limited sense of sight makes it difficult for blind people to get a decent job. One of the jobs performed by the blind is a reflexology massager. Becoming a reflexology masseuse with visual limitations has several obstacles in learning reflexology. The purpose of this research is to make reflexology educational aids that are easily understood by blind masseurs so that blind masseurs can improve reflexology competence and determine the appropriate massage nerve points. The making of teaching aids is carried out using the Research and Development method with five stages, namely information gathering, planning, development, trials with students and coaches, and evaluation. The results of this study are a prototype in the form of a microcontroller-based smart demonstration leg called Smart Massage Tools. The output of the Smart Massage Tools prototype is sound which is suitable for use by blind people who want to study reflexology independently. Smart Massage Tools have higher time effectiveness and understanding than massage training using manual props.
Controlling the output current of a SEPIC H-bridge inverter Roy Fada Krisna Wisnu Mahendra; Leonardus Heru Pratomo
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.1048

Abstract

The rapid depletion of fossil fuels and humanity's increasing dependence on electricity drive us to adopt renewable energy-based power generation. However, using renewable energy requires a system to maximize the results of converting renewable energy into electrical energy. An inverter is a DC-to-AC power conversion device. Inverters have two types: buck and boost. In closed-loop control, it can be controlled using current or voltage control. Current-controlled inverters sent to the grid have constraints, such as the inverter input voltage value must exceed the voltage on the grid. This study suggests using an H-bridge inverter and an AC-AC SEPIC to generate a voltage value more significant than the input voltage value. The proposed converter uses a single DC source and bases grid current injection on the regulated output current approach. The proposed converter satisfies the IEEE Std 519-2014 requirement of less than 5% and has a Total Harmonic Distortion (THD) of 4.6%.
Strategi Resampling dan Pengaruhnya terhadap Fitur Variabilitas Denyut Jantung pada Data Elektrokardiogram Berfrekuensi Sampling Rendah Zakariyah, Muhammad; Zaky, Umar; Nurjaman, Muhammad; Istikmal, Agil Ghani; Widianto, Hafizh Athallah
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.1049

Abstract

Heart rate variability (HRV) is a parameter to measure fluctuations in the interval between heartbeats. HRV provides essential insights into the cardiovascular function and autonomic nervous system. Electrocardiograms (ECG) on wearable devices are often recorded at low sampling rates, limiting temporal resolution and information. Resampling is a technique of changing the sampling rate from a high sampling rate to a lower sampling rate and vice versa. This research aims to evaluate the effect of resampling ECG data with a low sampling rate on HRV features. ECG data consists of 50 Hz and 100 Hz sampling rates. Data with a 50 Hz sampling rate is up-sampled up to 100 Hz, while 100 Hz data is down-sampled up to 50 Hz and up-sampled up to 250 Hz using the Fast Fourier Transform Interpolation Method. Upsampling from 50 Hz to 100 Hz shows unsatisfactory results, except for some HRV features such as NN20, pNN20, and CVI. Better results were found when up sampling from 100 Hz up to 250 Hz, with some HRV features showing good concordance values. However, downsampling from 100 Hz up to 50 Hz is unsuitable for HRV feature analysis. To obtain accurate HRV analysis results in all domains, it is highly recommended to use a sampling rate above 100 Hz.

Page 38 of 48 | Total Record : 473

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