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Ahmad Azhari
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Signal and Image Processing Letters
Published by Association For Scientific Computing Electrical and Engineering
ISSN : 27146669     EISSN : 27146677     DOI : 10.31763/simple
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
The journal invites original, significant, and rigorous inquiry into all subjects within or across disciplines related to signal processing and image processing. It encourages debate and cross-disciplinary exchange across a broad range of approaches.
Arjuna Subject : Ilmu Komputer (semua kategori) - Pemrosesan Sinyal
Articles 5 Documents
 1 
Search results for , issue "Vol 4, No 2 (2022)" : 5 Documents clear
Implementation of Base Station Communication Systems on Wheels Football Robots Agitasani, Revi; Puriyanto, Riky Dwi
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.39

Abstract

In the wheeled soccer robot contest competition, you have to prepare a strategy to win the race. The strategy used is a communication system. The communication system on the wheeled soccer robot has an important role during the match. This research will discuss the implementation of the GUI on the Base Station using the processing 3 application in its manufacture and using the Java language and analyzing data transmission. The use of the GUI is shown to make it easier to control robots during matches and minimize human work. The communication system used uses multicast with the UDP (User Datagram Protocol) protocol. Based on the results of research using the UDP protocol, the data transmission carried out by the GUI at the Base Station can function as a robot sending data. The resulting average delay is the farther the distance the more the average delay generated. The success rate of delivery is 100%.
Multivariate Time Series Stock Price Data Prediction in The Banking Sector in Indonesia Using Bidirectional Long Short-Term Memory (BiLSTM) Pramesti, Mara Indar; Indikawati, Fitri Indra; Prahara, Adhi
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.33

Abstract

The capital market is a place for individuals or business entities to carry out investment activities, especially in the banking sector, one of the sectors in the LQ45 stock index which is in great demand by investors in Indonesia. In the capital market, one of the investments that can be made is stock investment, but investors will be faced with uncertainty by fluctuations in stock prices caused by several factors, one of which is macroeconomic factors. Therefore, a predictive analysis of stock prices is needed to prevent uncertainty and minimize losses. Accurate prediction models can use deep learning algorithm methods. In the prediction of stock price movements, the data used is historical data on stock prices which is time series type data. This study conducted stock price predictions using the Bidirectional Long Short-Term Memory (biLSTM) method. biLSTM is another variation of the LSTM model. The object of this study uses the variables open, close, adj close, low, high, volume, value, buying rate, selling rate. The data that has been obtained will be preprocessing. Next build a prediction model using hyperparameter tuning with Genetic Algorithm (GA), train the model and evaluate the model. Data testing was carried out using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) with 4 data from the banking sector in Indonesia including Bank BRI, Bank BNI, Bank BCA, and Bank Mandiri. Based on the data testing that has been carried out, the results of the biLSTM algorithm can predict stock prices accurately because it has a relatively low RMSE value with a MAPE value below 10%.
Alarm System and Suitcase Tracker with Arduino Microcontroller Based on the Internet of Things Prihandono, Yudi Renaldi; Baswara, Ahmad Raditya Cahya
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.38

Abstract

Suitcases are prone to criminal crimes, because suitcases are a place to store valuables, especially when traveling. It is difficult to track the availability of suitcases because there are too many of the same suitcases. Research on the manufacture of alarm tools and suitcase trackers is intended to design and build a luggage tracking system using GPS, SIM 800L, Buzzer, Li-Ion 18650 Battery, and Arduino Nano which can provide alerts through smartphones connected to IoT. To find out how the system works well, testing is carried out by measuring the length of time it takes for alarm devices and suitcase trackers to track and the time it takes for the alarm to sound. The successful design of an alarm and suitcase tracker using GPS, SIM 800L, Buzzer, IoT, Li-Ion 18650 Battery, and Arduino Nano. GPS devices can lock signals with an accuracy of 98.53% for operator one and by 35.59% for operator two in a closed room state, by 97.71% for operator one, and by 62.85% for operator two in an open room state. The phone delay time with buzzer has an average delay time value of 14 seconds for operator one and 16.4 seconds for operator two and an accuracy value of 98.78%. Thus using operator one is more efficient than operator two.
Classification of Interests and Talents in Early Adult Phase Based on RMIB Test with Neural Network Azhari, Ahmad; Jaya, Erlangga
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.24

Abstract

The brain in the human body is responsible for regulating the overall work of the human body and mind. The left part of the brain is the center of intelligence or commonly called Intelligence Quotient (IQ).  Intelligence can come from genes received by children from their parents that will continue to develop along with a person's maturity process.  An individual will go through a transition period or transition period, namely in the early adult phase so that individuals in the early adult phase often experience unstable psychic conditions. This labile condition occurs in early adult individuals in this case, namely students who are still not sure what potential interests and talents they have, causing students It felt wrong to take the major. The purpose of this study is to classify interests and aptitudes from EEG data obtained from interviewees with RMIB test stimulus. In this study, testing will be carried out on the object of study where the   object of study is an individual in the early adult phase with an age range between 18-30 years. The test is carried out using a beta signal (12-30 Hz) resulting from an Electroencephalogram (EEG) signal filter generated from recording EEG data with the NeuroSky Mindwave tool and then reduced to get the best value or component with the Principal Component Analysis (PCA) method.  EEG data recording is carried out 3 times with data recording intervals every 14 days. EEG data is   information that we can get from activity waves in the brain, because waves in the brain cannot be observed visually. Testing on this study.  The EEG data obtained will go through the pre-processing stage, namely signal filters and signal reduction   and then will be classified using neural networks with a backpropagation algorithm with Using 1 layer of hidden layer. In this study, the results of the RMIB test carried out by the interviewees were calculated by psychologists (expert judgement) which were used as comparison data or the output produced by the system.   Testing is carried out by cross validation, which is to cross-test each data retrieval. Accuracy testing on the first fetch resulted in an accuracy of 92.8571%, in the second data retrieval it produced an accuracy of 78.571%, in the third data retrieval it resulted in an accuracy of 71.4285% with an average accuracy produced by the system of 80.9523%.
Sub Controller Design on KRSBI Humanoid R-SCUAD Robot Sub Controller Design on KRSBI Humanoid Robot R-SCUAD Mizan, Bahrul; Satya Widodo, Nuryono
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.27

Abstract

The purpose of this research is to design OpenCM9.04 controllers such as Arbotix (Pro) with MPU-9250 sensor as robot balance, as well as controlling the movement of DYNAMIXEL servo angles based on camera input on the robot, the Design of the OpenCM9.04 controller board on the robot consists of 2 main components namely OpenCM9.04 which works as a mini system and OpenCM 485 Expansion Board that works as a conference to the serial that provides interface to buttons and LEDs as well as a power supply circuit , where OpenCM9.04 as the main controller then sends data to OpenCM 485 which will process the MPU-9250 sensor as well as the DYNAMIXEL servo on the robot. The hardware system design consists of an MPU-9250 sensor to maintain balance in the robot so that the robot does not fall when walking or running and servo DYNAMIXEL to move the corners on the robot. The results obtained by the OpenCM9.04 controller have been successfully developed and tested on robots in the KRSBI-H racetrack and the robot has been able to maximize in the game well without any constraints on the microcontroller used.

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