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Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer
Published by Politeknik Negeri Banjarmasin
ISSN : 25983245     EISSN : 25983288     DOI : -
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
We are the Editor of Jurnal ELTIKOM, invites Mr. / Ms Lecturer, researcher and practitioner to be able to publish your paper on topics covering Electrical Engineering, Electronics Engineering, Telecommunications Engineering, Computer Engineering, Information Technology.
Arjuna Subject : -
Articles 11 Documents
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Search results for , issue "Vol. 7 No. 2 (2023)" : 11 Documents clear
Prediksi Cepat Gangguan Jaringan Tegangan Menengah Menggunakan Metode Knowledge Growing System (KGS) Syamsiana, Ika Noer; Yohana, Puspa Ayu Yohana; Sirajuddin, Indrazno; Sumari, Arwin Datumaya Wahyudi; Sulistio, Andhika
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.573

Abstract

With the increasing demand for electrical energy in the household and industrial sectors, reliability in the distribution of electrical energy is very important. Disturbance in electricity distribution is a routine problem that will always occur in the field. To improve the quality of service, readiness in overcoming distribution disturbances is needed, for example by knowing the disturbances that will occur in the field. This study was conducted to solve this problem by applying the Knowledge Growing System (KGS) method in predicting the type of electricity distribution disturbance that occurred in the PLN unit. In this study, the scope of the research object is limited to PLN units in the South Surabaya area. This prediction is done by recognizing the pattern of disturbances that occur every month based on data taken in 2020. This method was chosen because it is an intelligent agent that can generate its knowledge through observing certain phenomena so that it can produce its own knowledge in making predictions. In this study, 5 patterns of electrical disturbances were used at the location of the electricity distribution. From the results of calculations and analysis using the KGS method, it was found that the prediction of electrical distribution disturbances in the form of animal disturbances with the highest degree of confidence value (DoC) occurred at the Sukolilo substation of 34.77%. Predictions of other disturbances in the form of "material" disturbances occur in Rungkut, Waru, and Darmo Grand feeders with DoC values ​​of 28.33%, 29.72%, and 34.72%, respectively.
Unpacking Public Perceptions of Qris with Twitter Data: A Vader And LDA Methodology Ulya, Dzakiya Ishmatul; Kunaefi, Anang; Rolliawati, Dwi; Nugroho, Bayu Adhi
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.742

Abstract

QRIS, a mobile payment transaction system standardized by Bank Indonesia, has become the subject of extensive public discourse on Twitter. Employing VADER for sentiment analysis and LDA for topic modeling, this study aims to capture the nuanced perspectives of the Indonesian public toward QRIS. Our methodology includes real human validation for tweets that have been initially labeled by VADER. Our unique contributions lie in employing a mixed-methods approach for comprehensive sentiment and topic analysis, as well as making our dataset publicly available for future research. We achieve a sentiment labeling accuracy of 81.66%, uncovering that 67% of the sentiment towards QRIS is positive, 28.2% negative, and 4.17% neutral. Positive tweets mostly cover six dominant topics with a value of 0.488037, whereas negative sentiments are concentrated around three dominant topics with a   value of 0.383938. These findings not only affirm the generally positive public response towards QRIS but also highlight areas requiring attention for its continued success. Our study translates these insights into actionable recommendations, aiming to provide a multidimensional understanding that stakeholders can leverage for system enhancement. This study serves as a foundation for future works in sentiment analysis and public opinion mining related to financial technologies, particularly in the Indonesian context.
Time Segment Analysis of Heart Rate Variability to Evaluate Daily Stress using Wearable Device Technology Sahroni, Alvin; Sofyan, Pramudya Rakhmadyansyah
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.747

Abstract

Present studies have successfully evaluated psychological properties such as mental health and stress by using physiological data from the cardiovascular system. Most studies established specific interventions and ambiguous heart rate properties according to homeostatic conditions. We proposed a study evaluating mental stress based on daily activities dataset. Twenty-two healthy men were observed in this study. We employed two approaches based on the time segments, while extracting the HRV parameters. We discovered that there was no significant difference between the parameters corresponding to the daily stress score groups (low- and high-stress) when we used whole-day recording in one segment HRV parameter measurement (p > 0.05). However, by extracting the HRV parameters based on multi time segments (phases 1, 2, and 3), we found parameters that were able to properly distinguish the two groups (low- and high-stress). The frequency domain parameters are the most sensitive features, especially the LF and HF (p < 0.01), followed by the total power (p < 0.05). In the time domain measurement, the RMSSD, StdHR, SD1, and SD2 are able to differentiate the participants based on the daily stress scores (p < 0.05). As a result, this study proposed that by continually monitoring biological signals based on time segment and employing the given parameters, it is possible to appropriately and meaningfully measure the daily stress condition for future classification studies.
Model Analysis of Gated Recurrent Unit for Multivariate Rice Price Forecasting Ananda, Muhammad Ikhsan
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.770

Abstract

Food security, especially in the agricultural sector in the form of food price stability of rice as a national food ingredient is a strategic issue for Indonesia. Rice price forecasting is needed to mitigate rising rice food prices. Rice price fluctuations can be caused by internal factors such as bad weather or external factors such as the low selling price of rice, resulting in losses for farmers. This study aims to carry out multivariate rice price forecasting in DKI Jakarta by involving rice prices, weather, economic, and health factors using the Gated Recurrent Unit (GRU) algorithm where the accuracy test is based on the MAPE value between forecasting results and actual data. As a result of the GRU algorithm for multivariate rice price forecasting, the MAPE for training and testing is 0.964% and 2.628%, indicating that all models in the measurement category are very well represented.
Wind Power Frequency Control in Doubly FED Induction Generator Using CFMPC-FOPID Controller Scheme M S, Bershiya; Melba, Jasphin; Bright, Shibu J V; Jeba, Evangelin
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.777

Abstract

Because the majority of wind turbines operate in maximum output power tracking mode, power system frequency cannot be supported. However, if the penetration rate of wind power increases, the system inertia related to frequency modulation may decrease. In addition, frequency stability will be severely affected in the event of significant disturbances to the system load. Due to the high penetration of wind power in isolated power systems, this study suggests a coordinated frequency management approach for emergency frequency regulation. In order to prevent the phenomenon of load frequency control in doubly fed induction generators (DFIGs), a unique efficient control scheme is developed. The Cascaded Fractional Model Predictive Controller coupled with Fractional-Order PID controller (CFMPC-FOPID) is developed to provide the DFIG system with an efficient reaction to changes in load and system parameters. The proposed controller must have a robust tendency to respond quickly in terms of minimum settling time, undershoot, and overshoot. Nonlinear feedback controllers are designed using frequency deviations and power imbalances to achieve the reserve power distribution between generators and DFIGs in a variety of wind speed conditions. It makes upgrading quick and easy. In Matlab/Simulink, a simulation model is built to test the viability of the suggested approach.
Random State Initialized Logistic Regression for Improved Heart Attack Prediction Wibowo, Kevyn Alifian Hernanda; Putri, Salma Aprilia Huda; Jumanto, Jumanto; Muslim, Much Aziz
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.822

Abstract

One of the primary causes of death in Indonesia is heart attacks. Therefore, an effective method of pre-diction is required to determine whether a patient is experiencing a heart attack. One efficient approach is to use machine learning models. However, it is still rare to find machine learning models that have good performance in predicting heart attacks. This study aims to develop a machine learning model on Logistic Regression algorithm in predicting heart attack. Logistic Regression is one of the machine learning meth-ods that can be used to study the relationship between a binary response variable [0,1] and a set of pre-dictor variables, and can be used directly to calculate probabilities. In this study, a random state is ini-tialized in the Logistic Regression model in order to stabilize the training of the machine learning model and increase the precision of the proposed method. The results of this study show that the proposed model can be a method that has good performance in predicting heart attack disease.
The Hybrid Cryptographic Algorithms for Secure RFID Data Protection in The Internet of Things Maulidzart, Alief Vickry Thaha; Harahap, Robby; Sukowati, Antonius Irianto; Nur’ainingsih, Dyah; Widyastuti, Widyastuti
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.860

Abstract

RFID is often used by companies to identify employees and company assets, as well as in supermarkets to identify goods when shopping. In this increasingly sophisticated era, IoT technology has wide applications. The use of RFID technology in IoT networks may pose vulnerabilities to security and privacy because it contains sensitive information, and RFID data transmitted over communication channels is vulnerable to attacks. IoT technology has characteristics such as high autonomous data capture rate, network connectivity, and interoperability for services and applications. Therefore, this research aims to improve the security of RFID data by taking into account the characteristics of IoT. The method used is hybrid cryptography by combining AES (Advanced Encryption Standard) and ECDH (Elliptic-curve Diffie-Hellman) keys. AES, as a commonly used symmetric cryptography, is chosen to protect the data, while ECDH, as the latest asymmetric cryptography, is used for a faster and more efficient process compared to previous asymmetric methods. This study utilizes the Python programming language on Jupyter Notebook. The initial step of the study involved scanning the RFID data to be secured and configuring the key on ECDH. The subsequent process included encryption and decryption of the data. The study successfully tested the success of encryption and decryption on RFID UIDs. The test data includes the result display of the hybrid encryption, the encryption and decryption processing time, and the file size of the encryption (ciphertext) and decryption (decodetext). These results show an excellent level of security for RFID UIDs. Only those with a specific key can know the contents of the cipher. It should be noted that this study was only conducted at the program level and was not implemented on hardware. Therefore, the results can be a valuable reference for future research.
Optimization of 4G LTE Network Bad Spot Area using Automatic Cell Planning Method Yuhanef, Afrizal; Aulia, Siska; Jasmanto, Jasmanto
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.896

Abstract

The 4G LTE technology is widespread in almost all regions in Indonesia, including Solok City in West Sumatra, where this study was conducted. Based on the results of the 1800 MHz frequency drive test, the RSRP value was in the good category (81.44%), but the SINR value was in the poor category (56.96%). Furthermore, the results of the 2100 MHz frequency drive test showed that the RSRP value was in the poor category (58.11%), and the SINR value was also in the poor category (54.62%). These results indicate that the area had poor network quality. Therefore, this study aimed to optimize the Bad Spot Area in Solok City using the Automatic Cell Planning (ACP) method. The ACP method optimization results show that at the 1800 MHz frequency, the value of the ten cells is in the interval -127.84 ≤ RSRP ≤ -99.34. Meanwhile, at the 2100 MHz frequency, the value of the seven cells is in the poor category, which is in the interval -136.39 ≤ RSRP ≤ -111.03. In the 2100 MHz frequency, there is a decrease in RSRP value in the poor cate-gory from 43.27% to 41.85%. SINR parameter optimization results of 2100 MHz frequency, the percentage of a very good category is higher with a value of 51.40% than 44.16% at 1800 MHz frequency.
Automatic Tube Counter Monitoring System using Infrared Sensor based on NODEMCU ESP8266 Nawawi, Nawawi; Rusilawati, Rusilawati; Lisdawati, Ayu Novia; Winarno, Istiyo
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.921

Abstract

Technology is needed in every industry because it can simplify the production process, improve production quality, and enhance the company's reputation in the sight of consumers. The cylinder counting activity at PT Batuah Energi Indonesia is still done manually, involving time and standardized estimation of LPG cylinder loads, which faces inaccuracy issues. In fact, PT Batuah Energi Indonesia has facilities that handle many LPG cylinders from various users and providers of LPG cylinders. While accurate cylinder counts are beneficial to the industry, companies need technology that can automatically calculate the number of filled LPG cylinders. Therefore, this study was carried out to demonstrate to students how to develop automatic tube counters using an infrared E18-D80NK as a tube detector, NodeMCU microcontrollers ESP8266 as controllers, Arduino IDE for developing programs, and IoT for remote monitoring. The developed device approach, specifically using the E18-D80NK infrared proximity sensor based on the NodeMCU ESP8266, can be coded using the Arduino IDE compiler. For the detection of the number of tubes, the E18-EN80K infrared sensor is used and data transmission wirelessly utilizes the Blynk application. The results of the automatic tube counter monitoring tool were successfully tested with a 100% accuracy rate, utilizing the E18-D80NK infrared sensor and NodeMCU microcontroller ESP8266, and can be monitored remotely using Blynk.
Range and Velocity Resolution of Linear- Frequency-Modulated Signals on Subarray-Mimo Radar Sabaria, Sabaria; Tahcfulloh, Syahfrizal
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.940

Abstract

The most important radar system performance is determining the range-velocity of the detected target. This performance is obtained from processing an ambiguity-function (AF) between signals from target reflections and radar radiation signals. Selection of the appropriate waveform transmitted by the radar is a key factor in supporting high resolution radar performance in the AF. There are many waveforms that have been studied in radar systems, especially for multi-antenna radars, i.e., subarray-MIMO (SMIMO) radar which can form phased array (PA) and MIMO radars simultaneously, in the form of linear-frequency-modulated (LFM) signals. In this paper, we examine the use of LFM waveforms combined with SMIMO radar to produce plots of three-dimensional AF as a function of time delay and Doppler shift. The results of the comparison with the Hadamard signal determine the effectiveness of the observed AF performance on parameters such as magnitude, range-velocity resolution, peak sidelobe level ratio, and integrated sidelobe ratio by taking into account the factors of the number of Tx antennas on the PA radar and the number of Tx subarrays on the MIMO radar. The evaluation results of the SMIMO radar configuration (M = 6) with the number of Tx-Rx antenna elements the being 8 provide the best mainlobe magnitude, sidelobe magnitude, range resolution, velocity resolution, PSLR, and ISLR of AF LFM signals compared to conventional radars are 235.2dB, 7.54dB, 37.5m, 75km/s, 29.89dB, and 29.8dB, respectively. Meanwhile, the LFM signal is far superior to the Hadamard signal which has PSLR and ISLR 1.16dB and -3.36dB, respectively.

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