Articles
Finite Impulse Response Filter for Electroencephalogram Waves Detection
Melinda Melinda;
Syahrial;
Yunidar;
Al Bahri;
Muhammad Irhamsyah
Green Intelligent Systems and Applications Vol. 2 Iss. 1 (2022)
Publisher : Tecno Scientifica Publishing
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DOI: 10.53623/gisa.v2i1.65
Electroencephalographic data signals consist of electrical signal activity with several characteristics, such as non-periodic patterns and small voltage amplitudes that can mix with noise making it difficult to recognize. This study uses several types of EEG wave signals, namely Delta, Alpha, Beta, and Gamma. The method we use in this study is the application of an impulse response filter to replace the noise obtained before and after the FIR filter is applied. In addition, we also analyzed the quality of several types of electroencephalographic signal waves by looking at the addition of the signal to noise ratio value. In the end, the results we get after applying the filter, the noise that occurs in some types of waves shows better results.
A Model to Investigate Performance of Orthogonal Frequency Code Division Multiplexing
Nasaruddin Syafie;
Melinda Melinda;
Ellsa Fitria Sari
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: July 2012
Publisher : Institute of Advanced Engineering and Science
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OFCDM is an attractive multiple access scheme for high data rate application in Fourth-generation (4G) wireless communication system. Previously, several researches were only investigated the performance of OFCDM based on variable spreading factor. However, there are several system parameters may affected the performance of OFCDM. Therefore, this paper investigates the impact of several parameters on the performance system of OFCDMA over Rayleigh Fading channel as a realistic channel in wireless communications.The simulation system model of OFCDM is introduced. The computer simulation is developed by using MATLAB programming in order to show the impact of several parameters for OFCDM’s performance including number of carriers, size of symbol, symbol rate, bit rate, size of guard interval and spreading factor. The simulation results show that the higher number of carriers, larger size of symbol, higher symbol rate, higher bit rate and larger spreading factor are giving the better system’s performance in terms of Bit Error Rate (BER). However, the larger guard interval is giving the worst system’s performance.So all the parameters should be considered in the implementation of OFCDM for the 4G wireless communication system. DOI: http://dx.doi.org/10.11591/telkomnika.v10i3.621
Optimized Power Allocation for Cooperative Amplify-and-Forward with Convolutional Codes
N Nasaruddin;
M Melinda;
E Elizar
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v12.i8.pp6243-6253
Future wireless communications technology should fulfill the demands of multimedia applications, interactive internet service, high data rates and power efficiency. However, wireless channel is affected by multipath fading that can degrade the system performance. To overcome the problem, cooperative communication has been introduced to be an efficient diversity technique to combat the multipath fading, to improve capacity and the system performance, and to reduce the energy comsumption by using power allocation technique in the network. This paper proposes an optimized power allocation (OPA) for cooperative amplify-and-forward (AF) protocol with convolutional codes (CC). A computer simulation model for the proposed system is developed using Matlab programming. Then, performance of the system is evaluated in terms of the system throughput, bit error rate and amplification coeficient for power allocation. Furthermore, the different rates of CC are also considered in the network. Simulation results show that multi-relay AF network can provide a higher throughput and lower bit error rate. Moreover, the performance of OPA system is better than that of non-OPA system. The using lower rate of CC in the OPA system provides coding gain for multi-relay cooperative AF network. Finally, the different amplification coeficients among relays give a significant improvement to optimize the system performance.
PID Controllers Performance On Dual Axis Tracking With Tetrahedron Based Sensor
Melinda;
Andri Novandri;
Yuwaldi Away
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang
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DOI: 10.22219/kinetik.v7i4.1549
This study compares control systems applied to a dual-axis tetrahedron-based sensor tracker. A tetrahedron-based sensor is a tracking sensor that can detect the coordinates of a light source. This study aims to determine a control system that can control sensors with high accuracy and precision and has a fast-tracking ability. Tests are carried out periodically by providing light at certain coordinates. After carrying out the testing and analysis process, it is concluded that the P controller is a better control system than the other controllers. This controller can control sensors with high accuracy and precision compared to PI, PD, and PID control systems. The P controller can also control the sensor to move towards the light coordinates with a travel time of 1.6 seconds on the X-axis and 3.1 seconds on the Y-axis, with a MAE value of 1.1 on the X-axis and 0.3 on the Y-axis. While the RSME value obtained is 1.33 on the X-axis and 0.55 on the Y-axis.
Implementation of Word Recommendation System Using Hybrid Method for Speed Typing Website
Melinda;
Maulana Imam Muttaqin;
Yudha Nurdin;
Al Bahri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)
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DOI: 10.29207/resti.v7i1.4518
Typing is one of the most frequently done activities in society therefore a medium is necessary to help train typing words that are often mistyped. Methods used in this research are the Content-Based Filtering Algorithm to gather the words that have a similar pattern to the words that are often mistyped based on the user's previous typing records and the Collaborative Filtering Algorithm that uses other users typing pattern to recommend the words. The result of this study shows the Collaborative Filtering Algorithm was able to gather words that are hard to type by the user with an accuracy of 49.2%, dan the Collaborative Filtering able to predict the score on how difficult for the user to type a word with the result of Root Mean Square Error (RMSE) value of 0.82 and with the Root Mean Square Percentage Error (RMSPE) value of 30% from the actual value, and a website which is the combination of the two algorithms with the result of 28% of the total word that is recommended was indeed difficult to type by the user with the typing speed of 103 WPM, and 72.3% for the user that has a typing speed of 39 WPM.
Analisis Kinerja MySQL Cluster Menggunakan Metode Load Balancing
Taufiq Abdul Gani;
Aulia Arafat;
. Melinda
Jurnal Rekayasa Elektrika Vol 11, No 4 (2015)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v11i4.2358
Information system and data is a very important thing nowadays. An information system especially a database is designed with a high data availability. One of the database systems is MySQL cluster. Sometimes, its performance decreased because of the system’s incapablity to handle the data. To overcome this problem, the research of load balancing systems for MySQL cluster is needed. This research is intended to analyze the effect of load balancing clustering methods on MySQL cluster which by default has been set as failover clustering. The analysis is done through data collection and database transactions test to get the number of Transactions per second (TPS) and response time parameter using SysBench. The test is divided into two main scenarios, the simple and complex-mode that running on 4 computers. The tests were conducted by giving workloads from 8 up to 128 threads respectively to the server through a client on default conditions and load balancing. The test results showed the number of TPS at MySQL cluster default is 536.61. In contrast, number of TPS at load balancing is better at 2261.22. Likewise, the response time at MySQL cluster load balancing is 147.55 ms faster than that of the default one at 335.00 ms.
Design Gas LPG Leak Detection System Based on Internet of Things
Erika Lety Istikhomah Puspita Sari*;
I Ketut Agung Enriko;
Melinda Melinda
JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Vol 8, No 3 (2023): Juni, socio-economics, community law, cultural history and social issues
Publisher : Universitas Syiah Kuala
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DOI: 10.24815/jimps.v8i3.24989
Gas leak detection systems are essential for ensuring the safety of people and property. The use of Internet of Things (IoT) technology in gas leak detection systems has become increasingly popular due to its ability to connect devices and collect data from various sources. In this paper, we propose the design and development of an LPG gas leak detection system based on IoT. The system uses LPG gas sensors to detect the presence of gas in the environment, a microcontroller to process the data and send it to the cloud, and a web-based dashboard to display the real-time gas concentration levels and send alerts to users in case of gas leakage. Liquefied Petroleum Gas is a tool that serves to anticipate the safety of a gas leak hazard that can cause explosion and harm to the soul and property. In this final assignment explains how to create a detection system using the MQ-2 gas sensor that is connected to the NODEMCU ESP8266 microcontroller which is then sent to Firebase where the data storage can be viewed in realtime and continued to the Android application, the application used is the MIT App Inventor that has been created to receive notifications in the event of a gas leak. Using a MQ-2 gas sensor with a standard value in the event of gas leakage above 200. This system has fulfilled the rules of the Internet of things because it uses the Internet to connect.
Breast cancer recurrence prediction system using k-nearest neighbor, naïve-bayes, and support vector machine algorithm
I Ketut Agung Enriko;
Melinda Melinda;
Agnesia Candra Sulyani;
I Gusti Bagus Astawa
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO
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DOI: 10.20895/infotel.v13i4.692
Breast cancer is a serious disease and one of the most fatal diseases in the world. Statistics show that breast cancer is the second common cancer worldwide with around two million new cases per year. Some research has been done related to breast cancer, and with the advancements of technology, breast cancer can be detected earlier by using artificial intelligence or machine learning. There are popular machine learning algorithms that can be used to predict the existence or recurrence of breast disease, for example, k-Nearest Neighbor (kNN), Naïve Bayes, and Support Vector Machine (SVM). This study aims to check the prediction of breast cancer recurrence using those three algorithms using the dataset available at the University of California, Irvine (UCI). The result shows that the kNN algorithm gives the best result in terms of accuracy to predict breast cancer recurrence.
Decision tree method to classify the electroencephalography-based emotion data
Teuku Muhammad Mirza Keumala;
Melinda Melinda;
Syahrial Syahrial
JURNAL INFOTEL Vol 14 No 1 (2022): February 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO
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DOI: 10.20895/infotel.v14i1.750
Electroencephalography (EEG) data contains recordings of brain signal activity divided into several channels with different impulse responses that can be used to detect human emotions. In classifying emotions, EEG data needs to be parsed or signal processed into values that can help recognize emotions. Research related to electroencephalography has been carried out previously and has experienced success using the Fuzzy C-Means, Multiple Discriminant Analysis, and Deep Neural Network methods. This study was conducted to classify human emotions from electroencephalography data on 10 participants. Each participant carried out 40 trials of testing using the Power Spectral Density (PSD) and Discrete Wavelet Transform (DWT) methods at the initial stage of classification and the Decision Tree method as the final method that can improve the accuracy of the two methods at the initial stage of classification. The results of this study were the finding of 2 participants (3 trials) who were unmatched from a total of 10 participants (400 trials), which were analyzed using the decision tree method. The decision tree method can correct this error and increase the classification result to 100%. The DWT method is used as a reference in the classification of emotions, considering that the DWT method has an output of arousal and valance values . In contrast, the PSD method only has a combined output.
The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method
Melinda Melinda;
I Ketut Agung Enriko;
Muhammad Furqan;
Muhammad Irhamsyah;
Yunidar Yunidar;
Nurlida Basir
JURNAL INFOTEL Vol 15 No 1 (2023): February 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO
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DOI: 10.20895/infotel.v15i1.874
Autism spectrum disorder (ASD) is a serious mental disorder affecting social behavior. Some children also face intellectual delay. In people with ASD, the signals detected have abnormalities compared to normal people. This can be a reference in diagnosing the disorder with electroencephalography (EEG). This study will analyze the effect of Power spectral density (PSD) on the EEG of autistic children and also compare it with the PSD value on the EEG of normal children using the Welch Periodogram method approach. In the preprocessing stage, the Independent Component Analysis (ICA) method will be applied to remove artifacts, and a Finite Impulse Response (FIR) filter to reduce noise in the EEG signal. The study results indicate differences in the PSD values obtained in the autistic and normal EEG signals. The PSD value obtained in the autistic EEG signal is higher than the normal EEG signal in all frequency sub-bands. From the study results, the highest PSD value obtained by the autistic EEG signal is in the delta sub-band, which is 54.06 dB/Hz, while the normal EEG signal is only 33.14 dB/Hz at the same frequency sub-band. And in the Alpha and Beta sub-bands, the normal EEG signal increases the PSD value, while in the autistic EEG signal, the PSD value decreases in the Alpha and Beta sub-bands. In addition, FIR and ICA methods can also reduce noise and artifacts contained in autistic and normal EEG signals.