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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) MEDIA ELEKTRIKA Elkom: Jurnal Elektronika dan Komputer Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik PROSIDING CSGTEIS 2013 Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Journal of Telematics and Informatics Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer JUITA : Jurnal Informatika Majalah Ilmiah MOMENTUM JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics TRANSISTOR Elektro dan Informatika E-Dimas: Jurnal Pengabdian kepada Masyarakat Journal of Electrical Technology UMY RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Medika Trada Jurnal Rekayasa elektrika International Journal of Information Engineering and Science International Journal of Electrical Engineering, Mathematics and Computer Science International Journal of Mechanical, Electrical and Civil Engineering Green Engineering: Journal of Engineering and Applied Science RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi
Sri Arttini Dwi Prasetyawati
Universitas Islam Sulta Agung
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Social Sciences

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Implementation of Least Mean Square Adaptive Algorithm on Covid-19 Prediction Sri Arttini Dwi Prasetyowati; Munaf Ismail; Badieah Badieah
JUITA : Jurnal Informatika JUITA Vol. 10 No. 1, May 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1238.009 KB) | DOI: 10.30595/juita.v10i1.11963

Abstract

This study used Corona Virus Disease-19 (Covid-19) data in Indonesia from June to August 2021, consisting of data on people who were infected or positive Covid-19, recovered from Covid-19, and passed away from Covid-19. The data were processed using the adaptive LMS algorithm directly without pre-processing cause calculation errors, because covid-19 data was not balanced. Z-score and min-max normalization were chosen as pre-processing methods. After that, the prediction process can be carried out using the LMS adaptive method. The analysis was done by observing the error prediction that occurred every month per case. The results showed that data pre-processing using min-max normalization was better than with Z-score normalization because the error prediction for pre-processing using min-max and z-score were 18% and 47%, respectively.
Neural network training for serial multisensor of autonomous vehicle system Eka Nuryanto Budisusila; Sri Arttini Dwi Prasetyowati; Bhakti Yudho Suprapto; Zainuddin Nawawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5415-5426

Abstract

This study aims to find the best artificial neural network weight values to be applied to the autonomous vehicle system with ultrasonic multisensor. The implementation of neural network in the system required long time process due to its training process. Therefore, this research is using offline training before implementing to online training by embedding the best network weight values to obtain the outputs faster according to desired targets. Simulink were used to train the system offline. Eight ultrasonic sensors are used on all sides of the vehicle and arranged in a serial multisensory configuration as inputs of neural network. With eight inputs, one sixteen-depth hidden layer, and five outputs, it was trained using the back-propagation algorithm of artificial neural network. By 100000 iterations, the output values and the target values are almost the same, indicating its convergency with minimum of errors. The result of this training is the best weights of the networks. These weight values can be implemented as fixed-weight in online training.
IMAGE PROCESSING FOR PERCENTAGE ANALYSIS OF VESSELS FOR VESSELS IN CORONARY HEART DISEASE PATIENTS Agung Satrio Nugroho; Sri Arttini Dwi Prasetyowati; Arief Marwanto
Journal of Telematics and Informatics Vol 8, No 2 (2020)
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v8i2.

Abstract

Cardiovascular disease is the highest cause of death worldwide, for this reason early detection is important to reduce mortality due to heart disease and blood vessels, so that a program is needed to calculate the narrowing that occurs in blood vessels experienced in patients affected by coronary heart disease, so can make it easier for a doctor to analyze and give a medical decision whether to do the ring installation or just administering drugs for blood thinning. This research uses the development of image processing technology from angiographic results by utilizing cropping to determine the area to be analyzed and image segmentation, where image segmentation is in the form of a denoise as a mean filter and increases the transmission of the image to be analyzed and thresholding which is a way of emphasizing the image by changing the image to black and white. Where the narrowing area is obtained from counting the number of logical pixels 1 of the image area that has been blocked and has been reconstructed while the normal area is calculated from the number of pixels having logic 1 plus the pixel area having logic 1, logic pixel 0 is an area of the vessel that is not narrowed. The results showed that the narrowing of the vessels in patients experienced by patients affected by coronary heart can be measured how narrowing is experienced. Of the 11 patient data measured, there were 4 patient data that were compared with the measurement results of the angiography instrument with the highest obtained error value of 3.9% and the lowest error value of 0.1% with an average value of error 1.8% where the error value is still within the tolerance value. Keywords: image processing, vessels for vessels, coronary heart disease
Exploration of Generator Noise Cancelling Using Least Mean Square Algorithm Sri Arttini Dwi Prasetyowati; Bustanul Arifin; Agus Adhi Nugroho; Muhammad Khosyi’in
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14826

Abstract

Generator noise can be categorized as monotonous noise, which is very annoying and needs to be eliminated. However, noise-cancelling is not easy to do because the algorithm used is not necessarily suitable for each noise. In this study, generator noise was obtained by recording near the generator (outdoor signal) and from the room (indoor signal). Noise generator exploration is carried out to determine whether the noise signal can be removed using the Adaptive LMS method. Exploration was carried out by analyzing statistical signals, spectrum with Fast Fourier Transform (FFT) and Inverse FFT (IFFT), and analyzing the frequency distribution of the remaining noise. The results showed that the correlation coefficients were close to each other. Outdoor and indoor signals are at low frequency. The behavior of FFT and IFFT if described in two dimensions, namely real and imaginary axes, formed a circle with a zero center and has parts that come out of the circle. It confirms that noise-cancelling with adaptive LMS can be realized well even though some noise is still left. The residual noise has formed an impulse that showed normally distributed with mean=-0.0000735 and standard deviation =0.000735. This indicates that the residual noise was no longer disturbing.
SISTEM PENDETEKSI KETERSEDIAAN DAN LOKASI TEMPAT DUDUK PADA RUANGAN MENGGUNAKAN MOVABLE PASSIVE INFRA RED (PIR) ARRAY Ari Wibowo; Sri Arttini Dwi Prasetyowati; Suryani Alifah
Elkom : Jurnal Elektronika dan Komputer Vol 15 No 2 (2022): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v15i2.753

Abstract

Based on statistical data, every year there is an increase in population. This also happened to the increasing number of Catholics. The increase member in Saint Aloysius Church of Mojosongo isn’t accompanied by an increase of seating facilities, to solved this, a device was designed which will show seats that have been used or still empty through a viewer that will be placed near the entrance. The research method used in this study is a quantitative method. The number of seats used by in one block is 25 seats, the seat sample is 9 seats. Three (3) PIR sensors are placed above the row to the seat 2, where the direction of the PIR sensor is drived by a stepper motor with an angle is 22.61°. Detection alternated and sequentially starting from row A, row B and row C. In general, the seat detection system based on ATMEGA16 works according to the design. People can find an empty seat position by looking at the viewer (LED) and looking for LED lights that are not lit.
The Impact of Telemetry Received Signal Strength of IMU/GNSS Data Transmission on Autonomous Vehicle Navigation Muhammad Khosyi'in; Sri Arttini Dwi Prasetyowati; Bhakti Yudho Suprapto; Zainuddin Nawawi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.3901

Abstract

This paper presents the effect of received signal strength on IMU/GNSS sensor data transmission for autonomous vehicle navigation. A pixhawk 2.1 flight controller is used to build the navigation system. Straight lines with back-and-forth routes were tested using two types of SiK telemetry: Holybro and RFD. The results of the tests show that when the RSSI value falls close to the receiver's sensitivity value, the readings of the gyro sensor data, accelerometer, magnetometer, and GNSS compass data are disturbed. When the RSSI signal collides with noise, the radio telemetry link is lost, affecting the accuracy of speed data and the orientation of autonomous vehicles. According to Cisco's conversion table, the highest RSSI on Holybro telemetry is -48 dBm, and the lowest is -103 dBm, with a receiver sensitivity of -117 and data reading at a distance of about 427 meters. While the highest RSSI value on RFD telemetry is -17 dBm and the lowest is -113 dBm, even the lowest value is above the receiver's sensitivity limit of -121 dBm with data readings at a distance of approximately 749.4 meters. RFD outperforms Holybro in terms of RSSI and sensitivity at low data rates. When reading distance data to reference distance data using Google Earth and ArcGIS, RFD telemetry has a higher accuracy, with an average accuracy of 98.8%.
Rancang Bangun Kapal Pengukur Volume Sedimen dengan Algoritma PID Muhammad Khoirun Faza; Sri Arttini Dwi Prasetyowati; Bustanul Arifin
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 5, No 2 (2023): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v5i2.1712

Abstract

Penelitian ini merancang sebuah alat berupa kapal pengukur volume sedimen. Alat ini menggunakan algoritma PID yang berfungsi untuk mengontrol pergerakan motor PG45 dan PG28. Nilai yang diukur adalah panjang, lebar, tinggi dan volume. Adjustable infrared sensor switch dan rotary encoder digunakan sebagai acuan pengukuran volume sedimen dengan pemroses data berupa Arduino Mega 2560. Hasil penelitian ini alat mampu membaca volume sedimen. Didapatkan nilai perbandingan antara nilai asli dan nilai hasil pengukuran alat yang implementasikan dalam bentuk persentase nilai error. Dalam 10 kali percobaan didapatkan rata-rata nilai error panjang sebesar 2,13 %, lebar sebesar 7,09 %, tinggi sebesar 0,95 %, dan volume sebesar 4,74 %.
Gas Detection and Classification Using Neural Network Based Gas Sensors Munaf Ismail; Sri Arttini Dwi Prasetyowati
Jurnal Rekayasa Elektrika Vol 19, No 2 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i2.30974

Abstract

Alcoholic beverages, apart from being haram, also cause loss of consciousness. The influence of alcohol while driving is very dangerous and can result in an accident. For this reason, it is necessary to detect the alcohol content in beverages so that their halal status is known and to avoid the dangers of consuming alcohol. This research is to detect the aroma of alcohol using the MQ-3 gas sensor, which consists of an aroma sensor in general with an Artificial Neuron Network (ANN), such as the number of neurons, layers, and epoch. Most of the learning schemes require testing to optimize the model structure. For this experiment, ANN is used as a liquid classification in grouping alcoholic and non-alcoholic liquids. The MQ-3 gas sensor successfully reads liquid vapor in alcohol with levels of 30%, 50%, 70%, and other water-based liquids. An artificial neural network with 2 hidden layers, 10 neurons, and 1000 iterations with the sigmoid activation function can approach a regression score of 1.1545 and sq error score of 0.5781.
Expert System for Autoclave Damage Detection Using the Fuzzy Logic Method Ilham M Rusdiyanto; Sri Arttini Dwi Prasetyowati; Eka Nuryanto Budisusila
International Journal of Information Engineering and Science Vol. 1 No. 4 (2024): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.124

Abstract

As a resource supporting public health services, management of electromedical equipment must be carried out quickly, accurately and integratedly so that function, safety, security and benefits can be optimized. The management of electromedical equipment is regulated in the Republic of Indonesia Minister of Health Regulation Number 65 of 2016 concerning Electromedical Service Standards. The expected result of this research is an expert system that can accurately detect damage to sterile electromedical equipment, especially autoclaves. This expert system can then assist electromedical technicians in finding damage and as an assessment in making decisions for appropriate and validated actions to be taken. From the results of testing and analysis of the expert system for detecting damage to Autoclaves using the fuzzy logic method, the following conclusions were obtained. The damage detection expert system application in the Autoclave has been proven to be able to provide 100% diagnosis results. This system can assess the degree of damage of 11.6235981%. based on the input symptoms provided, thus providing decisions that are close to the actual conditions. The expert system built is able to speed up the damage detection process compared to manual methods. This helps in taking quicker action to prevent further damage to the autoclave.
Analysis of Transformer Service Life Prediction at Traction Substation Cipete Raya MRT Jakarta Based on Temperature and Load Using Linear Regression Method. Bima Sekti Wibawanto; Sri Arttini Dwi Prasetyowati
International Journal of Mechanical, Electrical and Civil Engineering Vol. 1 No. 4 (2024): October : International Journal of Mechanical, Electrical and Civil Engineering
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmecie.v1i4.48

Abstract

PT Mass Rapid Transit Jakarta operates a mass transportation system from Lebak Bulus Station to Bundaran HI. One of the traction substations is located in Cipete Raya, with a voltage rating of 20kV/1.2kV. A critical piece of equipment in this substation is the traction transformer, with a capacity of 4850 kVA/2x2500 kVA. The purpose of this study is to predict the service life of the Cipete Raya traction transformer based on temperature and load using the linear regression method. This study employs direct observation, analyzing load data from traction transformers 1 and 2 at Cipete Raya from January 2022 to June 2024, along with transformer temperature measurements. Secondary data include the technical specifications of the Cipete Raya traction transformer. The linear regression analysis for transformer 1 yields the equation y = 687.42 + 11.97x, indicating a 5.75% annual increase over the next 5 years, with a very strong correlation coefficient of R = 0.919. For transformer 2, the equation is y = 815.4543 + 6.488x, showing a 3% annual increase, with a strong correlation coefficient of R = 0.814. Based on the transformer aging calculations for June 2024, Transformer 1 has a per unit aging value (V) of 0.0014 and an estimated service life (n) of 407.689 years, while Transformer 2 has a V of 0.0012 and an estimated service life of 496.77 years. The aging model evaluation using MAPE shows that the prediction accuracy for transformers 1 and 2 is 6% and 3%, respectively, indicating excellent modeling performance.    
Co-Authors ., Gunawan Achmad Sulchan, Achmad Adhi Susanto Adhi Susanto Agung Satrio Nugroho Agus Adhi Nugroho Agus Adhi Nugroho Alfano Endra Wardhana Ari Wibowo Ari Widiatmoko Arief Marwanto Aries Budiyono Ary Sulistyo Utomo Aulia, Muhammad Rifky Badieah Assegaf Bahrun Niam Basit, Abdul Bhakti Yudho Suprapto Bima Sekti Wibawanto Budiyono, Aries BUSTANUL ARIFIN Bustanul Arifin Bustanul Arifin Darso D Deris Stiawan Diah Arie WK Eka Nuryanto Budi Susila Erwanto, Danang Fajar Yumono Floris Boogaard Gunawan . Hapsari, Jenny Putri Ida Widihastuti Ilham M Rusdiyanto Imam Much Ibnu Subroto Imam Rachmat Widodo Indra Ava Dianta Ismail, Munaf Jati, Budi Pramono Jenny Putri Hapsari La Ode Muhamad Idris Luh Putu Ratna Sundari Luqman Assaffat Mohammad Ilham Adi Saputra Muhamad Haddin Muhammad Kevin Hardiansyah Muhammad Khoirun Faza Muhammad Khosyi'in Muhammad Khosyi’in Muhammad Rifky Aulia Munaf Ismail Munaf Ismail Munaf Ismail, Munaf Munawar A Riyadi Nur Azizah Maghfiroh Pranoto Wibowo Raditya Rahmat Wijaya Riyadi, Munawar A Sauqie Fairoozy Firdaus Slamet Imam Wahyudi Sobri Bagasghani, Iqbal Suhartono Suhartono Suryani Alifah Syakhroni, Akhmad Tole Sutikno Widihastuti, Ida Zainuddin Nawawi