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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 505 Documents
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Lung Sounds Classification Based on Time Domain Features Achmad Rizal; Istiqomah Istiqomah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.24007

Abstract

Signal complexity in lung sounds is assumed to be able to differentiate and classify characteristic lung sound between normal and abnormal in most cases. Previous research has employed a variety of modification approaches to obtain lung sound features. In contrast to earlier research, time-domain features were used to extract features in lung sound classification. Electromyogram (EMG) signal analysis frequently employs this time-domain characteristic. Time-domain features are MAV, SSI, Var, RMS, LOG, WL, AAC, DASDV, and AFB. The benefit of this method is that it allows for direct feature extraction without the requirement for transformation. Several classifiers were used to examine five different types of lung sound data. The highest accuracy was 93.9 percent, obtained Using the decision tree with 9 types of time-domain features. The proposed method could extract features from lung sounds as an alternative.
Arduino MKR Analysis Using the RTC Alarm Method I Gusti Made Ngurah Desnanjaya; I Nyoman Saputra Wahyu Wijaya; Wayan Gede Suka Parwita; I Made Aditya Nugraha
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.23631

Abstract

The researcher analyzed the Real-Time Clock (RTC) alarm readings on the Arduino MKR Zero, Arduino MKR Wan 1300, and Arduino MKR GSM 1400. The Arduino MKR board compared the data with the accuracy of reading the RTC values. To support this research, experimental quantitative research methods were used, and an independent sample t-test was used. The use of this method is very suitable because this method displays numbers as data and also conducts experiments directly on the Arduino MKR board. Comparative measurement of the three MKR using the RTC Alarm get the average time difference. This average indicates the IC capability and accuracy of MKR. From the experimental results, MKR GSM 1400 has the greatest. Arduino MKR GSM 1400 is the Arduino MKR that has the fastest data response among the other two Arduino MKRs. So, to create or develop a project related to real-time data transmission, it is recommended to use the Arduino MKR GSM 1400.
Basketball Activity Recognition Using Supervised Machine Learning Implemented on Tizen OS Smartwatch Rosa Andrie Asmara; Nofrian Deny Hendrawan; Anik Nur Handayani; Kohei Arai
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.23668

Abstract

Basketball Activity Recognition (BAR) in sports teams, especially in basketball, to make statistical analysis of player activity data is currently a very important thing. BAR is one part of sports science that recognizes the movement of players in each activity, such as dribbling, passing, etc. Sport science in the sports business is used as one of the factors of coaches and management to determine strategy, starter line-up, check the condition of players after injury, etc. the current technology to recognize player activity only depends on the object detection method of players' through video recordings of players is considered lacking because it only sees the perspective of the coach to reduce players as starter line-up and there is no logical calculation of why players are not installed as starter line-up. One method for recognizing player activity is using a wearable device that has an accelerometer and gyroscope sensor with high accuracy. The values from those sensors will be classified and recognize their activity, i.e., Dribbling, Passing, and Shooting. Smartwatch is one of those wearable devices that meet those criteria. For the activity classification process, the use of the K-NN classification method is the most appropriate because it has a low computational level that is in accordance with the smartwatch specifications. The results of the classification using accelerometer sensor data and gyroscopes with K-NN as an activity recognition method have an accuracy of 81.62%, and player activity recognition applications using accelerometer and gyroscope sensors can also record the results of player movements for further analysis by management and coaches. This is the advantage of this BAR application compared to the recognition of player activity using object detection on video recordings.
Adapted Generalized Unsharp Masking Algorithm for Sharpness Improvement of Scanning Electron Microscopy Images Zaid Natiq Alsaygh; Zohair Al-Ameen
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24179

Abstract

Scanning electron microscope (SEM) images are highly valuable in different scientific applications because they can depict extremely small entities. SEM images are sometimes obtained blurry, in that such an issue reduces the clarity and hampers the detection of important features in the image. One way of processing the unwanted blurring effect is to use image sharpening, which aims at emphasizing the edges so that the output appears more significant to the observer with better-highlighted details. Many image sharpening methods exist, but not all are efficient as they may introduce artifacts, unnatural appearance, contrast/brightness modifications, or can be complicated and require a high computational cost. One algorithm of interest is the generalized unsharp mask (GUSM), which avoids the generation of artifacts that many sharpening methods own and have a somewhat simple structure. Still, when the GUSM algorithm is applied to different SEM images, it provides an unnatural sharpness and modifies the contrast and brightness as well. This is undesirable because proper sharpening is required for SEM images as they depict important information. Hence, an adapted GUSM algorithm is introduced in this article in that it provides a more natural sharpening without modifying the brightness or contrast of the filtered images. The main contribution of this study is to remove the contrast enhancement procedure and replace the smoothing process to deliver more natural sharpness. The developed AGUSM algorithm is verified with different real-unclear SEM images, its performance is appraised against different image sharpening methods, and the outcomes of comparisons are evaluated by utilizing advanced metrics. For the performed experiments, the AGUSM provided satisfying performances as the outcomes appear to have more acutance and look more natural when compared to the original counterparts and the outcomes of the comparison methods.
Capsicum Apps: Creating Innovation Space of Chili Supply Chain through the Triple Helix Model in Central Java Indonesia Suko Irawan; Sri Astuti; Nanda Mei Istiqomah; Ernoiz Antriyandarti
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.23650

Abstract

The paper aims to clarify the relationship between the Triple Helix concept and the logistic cultivation Distribution of chilli in Central Java. It proposes modelling the education and distribution transformation process through Capsicumm apps in industrial 4.0. This study used a qualitative approach to seeking the truth by discovering the essence. Conducted participant observation approach, the researcher, is directly involved as active agents and sources of information, participates for comprehensively discuss the role of Triple Helix Model which has been developed by the Value Chain Center (VCC) in the development of chilli supply chain management which involves the small farmers to fulfil the global market demands. Chilli is one of the essential commodities in Indonesia, and every region has different conditions of the vegetable trading system. The difference is caused by the additional amount of marketing agencies and supply chain management roles. Central Java is the province that has the longest chain of red chilli distribution. Chilli production that fluctuates annually causes the unstable selling price of chilli commodities, affecting chilli farmers' welfare and inflation. The paper contributes in providing empirical insights about the role of the Triple Helix Concept and how to change information In the industrial 4.0 era to optimize cultivation and logistic Distribution Chilli through Capsicum Apps.
Classification of Gender Individual Identification Using Local Binary Pattern on Palatine Rugae Image Hilman Fauzi; Cynthia Erika; Sofia Sa'adiah; Fahmi Oscandar
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.23636

Abstract

Major disasters caused many casualties with the condition of the damaged bodies. It causes the individual identification process to be ineffective through biometric characteristics (such as lips and fingerprints). However, the palatine rugae can carry the individual identification process. Palatine rugae have unique and individual characteristics and are more resistant to trauma because of their internal location. In this study, an individual identification system is proposed to identify gender using the image of palatine rugae. The proposed system is developed by several algorithms and methods, such as Local Binary Pattern (LBP) as the feature extraction method and K-Nearest Neighbor (KNN) as the classification method. Based on the result of the system performed test, the proposed system can identify the gender of an individual by the combination of recognized palatine rugae patterns. The system achieved an accuracy test result of 100% with a specific configuration of LBP and KNN. The research contribution in this study is to develop the individual gender identification system, which proceeds with the palatine rugae pattern image with unique biometric characteristics as an input. The system applied several methods and algorithms, such as Geometric Active Contour (GAC) as a segmentation algorithm, Local Binary Pattern (LBP) as a feature extraction method, and K Nearest Neighbor (KNN) as a classification method.
Trajectory Tracking and Collision Avoidance on Smart Wheel Chair Munawar Agus Riyadi; Syuja Rizqullah; Sumardi Sumardi; Teguh Prakoso
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24550

Abstract

There have been many developments of wheelchairs as mobility aids, including electric wheelchairs. Wheelchairs sometimes still require manual steering. Therefore, in this research, a smart wheelchair is developed that can move automatically to the destination position from a predetermined position with a trajectory tracking system. The system deploys the odometry method, orientation angle using the output of the IMU-9DOF sensor with Kalman filter, and collision avoidance to avoid collisions with obstacles in front of it. The use of the Kalman filter improves the angle output that is close to the reference. In the trajectory tracking test, the wheelchair can approach the given reference position with a maximum error of 20 cm for the x-axis and 2 cm for the y-axis. The wheelchair collision avoidance test has been able to avoid collisions, as it successfully detects an obstacle less than 40 cm and avoids the collision correspondingly.
Optimize Image Processing Algorithm on ARM Cortex-A72 and A53 Rachmat Muwardi; Mirna Yunita; Harun Usman Ghifarsyam; Hendy Juliyanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24457

Abstract

This work presents a technique to optimize processing image algorithms. The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has the mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM supported by shared memory, is presented with implementation details. The target platform chosen is the NanoPi M4V2. It has a dual-core and quad-core architecture with an ARM Cortex-A72 and Cortex-A53. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template-matching tasks such as face recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core, which runs a popular operating system such as Linux. The algorithms are tested on a variety of images, and performance results are presented, measuring the speedup obtained due to dual-core and quad-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks.
Analysis of Electrical Energy the Effect of Using a Smartphone-Based Water Pump Control System Controller (Case Study of Yulihamri's Rent at Merak Sakti Road) Antonius Rajagukguk; Iman Sahrobi Tambunan; Anhar Anhar; Alfian Ma'arif
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.23659

Abstract

The development of science and technology will increasingly have an impact on human life, especially electronic devices at home. In-home reservoirs, commonly, the owner of the water pump cannot detect the level of the water reservoir in his house due to no automation in the water pump. This study seeks to design a device that can control one water pump for filling three reservoirs, where the reservoir filling path will be regulated by a solenoid valve. It also aims to increase the efficiency of electrical energy in the water pump and be monitored by homeowners. The research was conducted at Yulihamri's rented house on Merak Sakti Road. In testing the measurement of electrical energy without using a control, the results obtained in the first reservoir of 1253.99 Wh, 2072.83 Wh, and 2136.27 Wh in the first, second, and third reservoirs, respectively. Meanwhile, in testing the measurement of electrical energy using the control system, the results obtained on all reservoirs in sequence are 1234.70 Wh, 1754.52 Wh, and 1644.12 Wh. The electric energy efficiency of the water pump after using the control system enhance by 15%. The contribution of this research is to reduce the use of excessive electrical energy due to the filling of water that exceeds the storage capacity so as to make it inefficient for the use of electrical energy as well as the water released. The research also limits the use of electrical energy at the end of the month, which makes this system more efficient compared to other systems.
Fast and Accurate Voice Biometrics with Deep Learning Algorithm of CNN Depthwise Separable Convolution Model and Fusion of DWT-MFCC Methods Haris Isyanto; Ajib Setyo Arifin; Muhammad Suryanegara
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24515

Abstract

Theft of private data became a threat of crime in cyberspace. This issue was in line with rapid development of data technology, especially online transactions. To attenuate this problem, voice biometrics was developed as an answer to keep up security identity. This paper develops the voice biometric framework based on Convolutional Neural Network Depthwise Separable Convolution (DSC) model and the fusion of Discrete Wavelet Transform (DWT) and Mel Frequency Cepstral Coefficients (MFCC). Such a scheme has targeted to increase the high accuracy, to reduce the burden of high computational costs and to speed up the performance of classification process time. We conduct three testing performance, i.e. voice Biometric Training Performance, speaker Recognition Performance (”Who is speaking?”), and Speech Recognition performance (”What keyword is uttered?”).  For each of the testing, the results are compared with CNN Standard performance. The training results has shown that CNN DSC model has reduced the amount of training parameters to 364,506, leading to accelerate the performance of training process time to 5.12 minutes. The results of speaker recognition performance has attained the best performance with an accuracy 99.25%, precision 97.14%, recall 98.17% and F1-score 97.28%. The results of speech recognition performance has been able to improve the best performance with accuracy 100%. It can be concluded that CNN DSC with the fusion of DWT- MFCC has outperformed the CNN Standard. The framework can be applied for the identification and verification of user voices accurately, quickly and efficiently for any applications requiring better security performance.

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