cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ahmad Azhari
Contact Email
simple@ascee.org
Phone
-
Journal Mail Official
simple@ascee.org
Editorial Address
Jl. Raya Janti No.130B, Karang Janbe, Karangjambe, Kec. Banguntapan, Kabupaten Bantul, Daerah Istimewa Yogyakarta 55198
Location
Kab. bantul,
Daerah istimewa yogyakarta
INDONESIA
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 89 Documents
 5   6   7   8   9 
Identification of Infant Crying Using Mel-Frequency Cepstral Coefficient (MFCC) and Artificial Neural Network (ANN) Methods Azhari, Ahmad; Destiyanti, Intan
Signal and Image Processing Letters Vol 4, No 3 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i3.70

Abstract

The crying of infants aged 0-3 months can be classified according to their needs, as identified by Dunstan Baby Language, which consists of specific sounds denoting different needs. These sounds include "eairh" for discomfort caused by fart, "neh" indicating hunger, "heh" representing general discomfort, "owh" signaling tiredness or sleepiness, and "eh" expressing the need to burp. The baby crying sound data was obtained from the Dunstan Baby Language (DBL) database, which includes educational videos about infants and a collection of babies crying sounds. These sounds were converted into *.wav audio format and divided into 5-second segments. A total of 188 audio data segments were collected. The research employed the Artificial Neural Network (ANN) classification method and the Mel-Frequency Cepstral Coefficient (MFCC) feature extraction method. The collected data underwent feature extraction, aiming to identify distinctive characteristics using the librosa library in the Python programming language. This process allowed us to obtain specific information from the acquired sound data. The results of this study achieved an accuracy level of 90%. This research contributes to the understanding and classification of infant crying based on the Dunstan Baby Language, offering insights into their various needs. The implementation of ANN and MFCC techniques showcases the effectiveness of this approach in accurately classifying infant cries and provides a foundation for further research in the field of infant communication.
Designing a Pure Sine Wave Inverter 250 VA Based on EGS003 Pashadewa, Alannafi Husein Bayu; Aji, Wahyu Sapto
Signal and Image Processing Letters Vol 6, No 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v6i1.104

Abstract

The design of a pure sine wave inverter based on the EGS003 aims to improve the efficiency of electrical energy conversion. This inverter development method integrates PWM (Pulse Width Modulation) control with a pure sine wave reference signal. The use of PWM control allows precise adjustment of the pulse width of the output signal, according to the desired sine wave characteristics. Consequently, this inverter is capable of producing pure sine waves without significant harmonic distortion, enhancing the quality of the generated power and reducing energy losses due to harmonic distortion. This research involves the implementation of EGS003 technology, which is a dedicated PWM controller designed for inverter applications. The use of this controller enables the optimization of resource utilization and enhances energy conversion efficiency. Furthermore, the development of the EGS003-based inverter involves the analysis and design of control circuits in line with modern power electronics principles. This includes adjusting PWM control parameters to various load characteristics, allowing the inverter to operate optimally under different usage conditions. The design results demonstrate that the pure sine wave inverter based on EGS003 provides satisfactory performance in delivering output compliant with power quality standards. With the capability to generate pure sine waves without significant harmonic distortion, this inverter has broad application potential in power systems requiring high-quality power. Additionally, the use of PWM control technology in this inverter facilitates ease of operation adjustment and monitoring, enhancing the overall reliability and efficiency of the system.
Vehicle Speed Estimation Using Optical Flow on Traffic Video Under Day and Night Lighting Condition Anggisa, Ahmad Bramdimas; Prahara, Adhi
Signal and Image Processing Letters Vol 3, No 2 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v3i2.30

Abstract

Traffic violation and congestion can happen at day or night. As a preventive measure, CCTV is installed at strategic locations on the road to monitor the traffic violation and congestion. Usually, some speed sensors also installed to measure the speed of vehicles then through a system, it will inform the operator about speedy vehicles or predict a congestion. However, it is not effective because it needs a lot of sensors to be able to monitor the vehicle speed in many locations especially in the highway and before the intersection all the time. This problem leads to the development of intelligent traffic monitoring system using computer vision technology. In this research, an optical flow-based vehicle speed estimation method is proposed. The method takes a CCTV video as an input, defines the road region of interest/ROI, performs orthographic projection transformation to find the ratio of distance, uses optical flow Farneback to track the vehicle movements, and estimates the vehicle’s average speed on the road. The method is tested using CCTV video under day and night lighting condition. From the experiment, the proposed method achieves 9.8% of average RMSE.
Separation of the Purpose of Beam Packages with Barcode Based Arduino Fitriyanto, Febriyan; Mushlihudin, Mushlihudin
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.61

Abstract

In modern times it has experienced a very rapid increase. The industrial world is currently growing and has become an important part. from the world as a whole. Developments in the industrial world today have provided many conveniences and advantages for companies in the process. One example of the use of technology in industry is the process of separating beam packages which is still done manually. If the separation process is still using. Human intervention (manual) will spend a lot of time. In this study, a prototype design of beam package separation that can separate goods automatically with the aim of the zip code already listed in the barcode code, aims to facilitate the performance of beam package separation when. Device design. Hard, namely the Arduino Mega 2560 microcontroller as the command logic storage in the system, two dc motors as conveyor drives, a barcode scanner functions as a barcode code reader, and a servo motor as output. Testing this system uses a package of goods from cardboard media, with a package thickness of 0.2 cm. Based on the results of testing the separation of package beams the tool can work well so that it can increase work effectiveness with an accuracy rate of success of the tool in separating goods packages in each first room with an accuracy of 80% for the purpose of Yogyakarta, then separation of parcels for the purpose of Jakarta with an accuracy of 86.6%, and Separation of beam packages with the destination of goods to Surabaya has an accuracy rate of 86.7%.
Monitoring of River Water Level Based on Internet of Things Liambo, Wahyu Padliansyah; Sunardi, Sunardi
Signal and Image Processing Letters Vol 5, No 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i2.93

Abstract

River water level monitoring is the process of monitoring water in rivers that sometimes overflow and cause flooding. Residents need to know the water level to serve as an early warning. Therefore, it is necessary to have a measurement mechanism and river water level information in order to provide information to the community. Monitoring river water levels in this research uses the HC-SR04 ultrasonic distance sensor and water level sensor. Arduino Uno is used as a microcontroller. This research uses a prototype with water level measurements observed at 3 cm (low), 3-5 cm (medium), and 5 cm (high). The water level can be monitored from anywhere through Blynk. The implementation of the resulting water level has been successful in accordance with the parameter values on the water level sensor which is marked by the display of numbers on the LED, the color of the lights, and different alarm sounds for each water level. HC-SR04 ultrasonic sensor is able to measure and provide water level data in realtime and from any place using Blynk.
K-Fold Cross Validation for Selection of Cardiovascular Disease Diagnosis Features by Applying Rule-Based Datamining Normawati, Dwi; Ismi, Dewi Pramudi
Signal and Image Processing Letters Vol 1, No 2 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v1i2.3

Abstract

Coronary heart disease occurs when atheroclerosis inhibits blood flow to the heart muscle in the coronary arteries. This disease is often the cause of human death. The method for diagnosing coronary heart disease that is often a doctor's referral is coronary angiography, but it is invasive, expensive, and high-risk. This study aims to analyze the effect of k-Fold Cross-Validation (CV) on the dataset to create features based on the rules used to diagnose coronary heart disease. This study uses the Cleveland heart disease dataset, where feature selection is performed using a medical expert-based method (MFS) and a computer-based method, Variable Precision Rough Set (VPRS). Evaluation of the classification performance using the k-fold 10-fold, 5-fold and 3-fold methods. The results showed the number of different attribute selection results in each fold, both for the VPRS and MFS methods, with the highest accuracy score in the VPRS method 76.34% with k = 5, while the MTF accuracy was 71.281% with k = 3.
Mask Detection System at the Entry of a Room Herdiyanto, Erik; Fadlil, Abdul
Signal and Image Processing Letters Vol 5, No 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i1.49

Abstract

This study focuses on automatic mask detection tools that can open doors in a room to minimize violations of health protocols, one of which is the use of masks during the pandemic. The method used in this study is the CNN classification method. Where the CNN calcification method has several stages in it, including pre-processing, training, and testing. In the pre-processing, all image data used will be labeled using Labeling.axe. The training process at CNN uses TensorFlow framework version 1.15. In the testing process, the test and data testing will be carried out in real-time by entering new images and models that are made and then a classification process is carried out on objects caught by the camera, classified images are marked with boxes and names of data classes. This data class is divided into two, namely data on wearing masks and without masks. The results of the test were carried out by entering 200 facial image data. The system can correctly detect as much as 190 times from 200 data tested with an Accuracy rate of 95%. Based on the test results, it shows that the resulting model is good and suitable for the classification process of recognizing mask detection images. However, to produce a better model requires data with more variety and a larger amount of data.
Analysis the Effects of Games on Cognitive Activity of Late Adolescents Using the Electroencephalogram with the K-Nearest Neighbor Method Azhari, Ahmad; Swara, Ajie Kurnia Saputra
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.20

Abstract

The influence of violent video games on child development continues to be a polemic, Various pros and cons also color this problem, because in adolescence not only adopt cognitive abilities in learning activities, but also various strategies related to managing activeness in learning, playing and socializing to improve cognitive abilities.  Adolescents who are addicted to online games are included in the three criteria set by WHO (Word Health Organization), namely that they need games with symptoms of withdrawing from the environment, losing control, and not caring about other activities (Santoso and Purnomo, 2017).  The purpose of this study is to analyze the cognitive activity of late adolescence between learning and playing games and knowing that games can have a good or bad impact on the cognitive activity of adolescents. The application of the K-Nearest Neighbor method to the system created can classify with prediction results on the influence of games on the cognitive activity of adolescents using Electroencephalogram (EEG) data and can also provide information in the form of new predictions on the respondent data obtained. The results of the analysis resulted in a percentage of accuracy in the game stimulus data of 80%, and in the cognitive stimulus data, namely SPM, it got an accuracy of 80% using the same K value in both stimuli, namely 1, 6, and 7. While the expert results on the system the percentage of superior but addicted respondents was 63.3% and the percentage of respondents who were average but addicted was 36.6% with a correlation rate between Games and SPM of 0.089822409. Based on the results of this study, it can be concluded that the percentage obtained from the comparison of the results of the expert to the results of the system and the comparison of the system itself does not have the influence of games on cognitive activity in late adolescence.
Prototype of Automatic Cover Roof Control system for Grain Drying Based on Internet of Things (IoT) Putri, Dadva Pramesty Etsria; Yudhana, Anton
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.76

Abstract

The sun is the largest source of heat energy on earth. Sunlight as an energy source can be used for the drying process in drying grain. Grain drying is done by drying in the open field or often referred to as traditional drying. Drying using sunlight has weaknesses, including if the weather changes, such as sudden rain, it will be difficult to move the grain. As a result, the dry grain becomes wet again so it takes more time to dry. From these problems, this research makes an automatic roof design when it rains, the roof will be closed automatically. If the weather is sunny and it is not raining, the roof will open. The sensors used are rain sensors and LDR sensors as light sensors that can produce several weather outputs such as sunny, cloudy and dark. While the material used is like a motor to be able to move the pulley. And the motor will move after getting instructions from the NodeMCU that the light received from the light sensor is in accordance with the command then the motor will move and the pulley will lift the light and strong plastic roof to be able to cover the roof perfectly after the rain sensor works. System testing shows an error in light of 5.5% while the system error shown at temperature is 0.01% and an error in humidity is 0.11%. The ability of the system to cover the roof when it is cloudy or when it is raining.
Traditional Herbal Medicine Production Information System Based on Prototyping Method Yunitarini, Rika; Fitrianto, Hambali; Mufarroha, Fifin Ayu; Koeshardianto, Meidya
Signal and Image Processing Letters Vol 7, No 1 (2025)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v7i1.112

Abstract

Indonesia is the country with the second largest biodiversity in the world after Brazil. Indonesia's biodiversity is very rich, both on land and at sea, and is one of the most important in the world. The benefits of Indonesia's biodiversity is as a natural resource that plays an important role one of them in the production of traditional herbal medicine. Madura Island in East Java, Indonesia, is famous for its natural resources and respected Madurese herbal medicine, internationally recognized for its efficacy in addressing health and beauty issues. The increasing demand for traditional herbal medicine products motivates the industry to improve production efficiency, prioritizing effective management and optimal utilization of raw material stocks. This research aims to manage the production needs of traditional herbal medicine by identifying information needs and developing a Production Information System using the Laravel framework to meet industry needs. This research will evaluate the impact of the system on the production process and the management of raw material needs in the traditional herbal medicine sector. The expected results include a positive contribution to the industry, better production performance, and improved handling of raw material stocks. The integration of the Laravel framework is expected to improve production performance and provide features for the traditional herbal medicine industry. In conclusion, this research seeks to offer a customized and effective solution for the traditional herbal medicine industry, addressing the increasing market demand through the optimization of production processes and management practices.

Page 8 of 9 | Total Record : 89

 5   6   7   8   9 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol 7, No 2 (2025) Vol 7, No 1 (2025) Vol 6, No 2 (2024) Vol 6, No 1 (2024) Vol 5, No 3 (2023) Vol 5, No 2 (2023) Vol 5, No 1 (2023) Vol 4, No 3 (2022) Vol 4, No 2 (2022) Vol 4, No 1 (2022) Vol 3, No 3 (2021) Vol 3, No 2 (2021) Vol 3, No 1 (2021) Vol 2, No 2 (2020) Vol 2, No 1 (2020) Vol 1, No 3 (2019) Vol 1, No 2 (2019) Vol 1, No 1 (2019) More Issue