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Contact Name
Siti Nurmaini
Contact Email
comengappjournal@unsri.ac.id
Phone
+6285268048092
Journal Mail Official
comengappjournal@unsri.ac.id
Editorial Address
Jurusan Sistem Komputer, Fakultas Ilmu Komputer, Universtas Sriwijaya, KampusUnsri Bukit Besar, Palembang
Location
Kab. ogan ilir,
Sumatera selatan
INDONESIA
ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
ComEngApp-Journal (Collaboration between University of Sriwijaya, Kirklareli University and IAES) is an international forum for scientists and engineers involved in all aspects of computer engineering and technology to publish high quality and refereed papers. This Journal is an open access journal that provides online publication (three times a year) of articles in all areas of the subject in computer engineering and application. ComEngApp-Journal wishes to provide good chances for academic and industry professionals to discuss recent progress in various areas of computer science and computer engineering.
Articles 318 Documents
A Vector Potential Function-Based Collision Avoidance Control for Differential-Steered Robots Anugrah K Pamosoaji
Computer Engineering and Applications Journal Vol 7 No 3 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.323 KB) | DOI: 10.18495/comengapp.v7i3.265

Abstract

A collision avoidance control that tracks a vector potential field-based velocity plan of a differential-steered robot is designed. Vector potential function (VPF) is a type of potential function used for motion planning. The plan resulted by the VPF is the desired velocity vector of the robot on all points in collision-free space. The problem to address in this paper is velocity tracking control in the environment of a circular obstacle. A controller is designed to track the VPF-based velocity plan. A concept of collision cone will be used to evaluate the ability of the controller to avoid collision between the robot and the obstacle. The stability of the controller is verified by using the Lyapunov stability analysis. Simulations of the controller’s performance are presented.
Real-Time Lighting Control System with Fuzzy-Mamdani for Smart Home Application Dimas Budianto; Siti Nurmaini; Bambang Tutuko; Sarifah Putri Raflesia
Computer Engineering and Applications Journal Vol 7 No 3 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1014.261 KB) | DOI: 10.18495/comengapp.v7i3.267

Abstract

The use of pervasive computing in the context of home automation equipment will greatly facilitate life. Several building still use manual switch to turn on or turn off the lighting system. It becomes ineffective if the house has a lot of lights, due to it sometimes forget to turn off. Hence, the real-time control system for automatic lighting processing is desirable. An automatic control system will allow to control the illumination and it will decrease the energy costs. In this paper, the Fuzzy logic system-based Mamdani style is used to adjust the intensity of the lights. Based on simple algorithm the controller board is working in a real-time condition. As a result found, the implementation is successfully to control the lighting system with good performance. Thus, the fuzzy system can be built smart home concept that facilitate the human life.
Classification Method of Hand Gestures Based on Support Vector Machine Wahyu Caesarendra; Mohamad Irfan
Computer Engineering and Applications Journal Vol 7 No 3 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (630.599 KB) | DOI: 10.18495/comengapp.v7i3.269

Abstract

This paper presents the EMG signal classification based on PCA and SVM method. The data is acquired from the 5 subjects and each subject perform 7 hand gestures includes the tripod, power, precision closed, finger point, mouse, hand open, and hand close. Each gesture is repeated 10 times (5 data as training data and the 5 remaining data as testing data). Each of training and testing data are processed using 16 features extraction in time–domain and reduced using principal component analysis (PCA) to obtain new set of features. Features classification using support vector machine classify new set of features from each subject result 85% - 89% percentage of training classification. Training data classification is tested using testing data of EMG signals and giving accuracy reach 80% - 86%.
Optimization distance learning computer of network with hierarchical token bucket Per Connection Queue (PCQ) Queue Tree Sutanto, Imam
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (330.243 KB) | DOI: 10.18495/comengapp.v8i1.271

Abstract

Implementation Distance Learning (DL) lecture at High School of Police Science namely Sekolah Tinggi Ilmu Kepolisian (STIK-PTIK) consisted of 32 Polisi Daerah (POLDA) in lecture Distance Learning (DL) throughout Indonesia. System bandwidth management using the method of simple queue, the simple queue is lacking both in bandwidth allocation. Optimization against computer networks in improving Quality of Service (QoS) using the method Per Connection Queue (PCQ) Queue Tree with four classes to model. Scale model of a priority bandwidth specifically as a model of optimization of computer networks with an average percentage of delay of 6.01%, packet loss decreased 0.26%, jitter of 13.56% and increased throughput became of 9.5%. The research is supported by the level of satisfaction by CSI towards PJJ / DL students, the methods of customer satisfaction index with the service quality (Servqual) questionnaire as against with levels of satisfaction the use of DL student participants with the result satisfaction levels of 74%. Keywords: hierarchical token bucket, per connection queue, queue tree, QoS parameters.
Feature Extraction for Retina Image Based on Difference Approaches Erwin Erwin; Saparudin Saparudin; Arum Cantika Putri; Hidayat Hidayat; Fifi Hariyani
Computer Engineering and Applications Journal Vol 7 No 3 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1151.994 KB) | DOI: 10.18495/comengapp.v7i3.275

Abstract

Automatic disease diagnosis using biometric images is a difficult job due to image distortion, such as the presence of artifacts, less or excessive light, narrow vessel visibility and differences in inter-camera variability that affect the performance of an approaches. Almost all extraction methods in the blood vessels in the retina produce the main part of the vessel with no patalogical environment. However, an important problem for this method is that extraction errors occur if they are too focused on the thin vessels, the wide vessels will be more detectable and also artificial vessels that may appear a lot. In addition, when focusing on a wide vessel, the extraction of thin vessels tends to disappear and is low. Based on our research, different treatments are needed to extract thin vessels and wide vessels both visually and in contrast. This study aims to adopt feature extraction strategies with different techniques. The method proposed in segmentation and extraction with three different approaches, namely the pattern of shape, color, and texture. Testing segmentation and feature extraction using STARE datasets with five classes of diseases namely Choroidal Neovascularization, Branch Retinal Vein Occlusion, Histoplasmosis, Myelinated Nerve Fibers, and Coats. Image enhancement on Myelinated Nerve disease Fiber is the best result from the image of other diseases with the highest value of PSNR of 35.4933 dB and the lowest MSE of 0.0003 means that the technique is able to repair objects well. The main significance of this work is to increase the quality of segmentation results by applying the Otsu method. Testing of segmentation results shows improvements with the proposed method compared to other methods. Furthermore, the application of different feature extraction methods will get information on disease classification features based on patterns of suitable shapes, colors, and textures.
Neural Network Controller Application on a Visual based Object Tracking and Following Robot Risma, Pola; Dewi, Tresna; Oktarina, Yurni; Wijanarko, Yudi
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (611.088 KB) | DOI: 10.18495/comengapp.v8i1.280

Abstract

Navigation is the main issue for autonomous mobile robot due to its mobility in an unstructured environment. The autonomous object tracking and following robot has been applied in many places such as transport robot in industry and hospital, and as an entertainment robot. This kind of image processing based navigation requires more resources for computational time, however microcontroller currently applied to a robot has limited memory. Therefore, effective image processing from a vision sensor and obstacle avoidances from distance sensors need to be processed efficiently. The application of neural network can be an alternative to get a faster trajectory generation. This paper proposes a simple image processing and combines image processing result with distance information to the obstacles from distance sensors. The combination is conducted by the neural network to get the effective control input for robot motion in navigating through its assigned environment. The robot is deployed in three different environmental setting to show the effectiveness of the proposed method. The experimental results show that the robot can navigate itself effectively within reasonable time periods.
PCA-Based on Feature Extraction and Compressed Sensing for Dimensionality Reduction Desiani, Anita; Maiyanti, Sri Indra; Miraswan, Kandak Januar; Arhami, muhammad
Computer Engineering and Applications Journal Vol 8 No 2 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.541 KB) | DOI: 10.18495/comengapp.v8i2.281

Abstract

Compressive sensing reduces the number of samples required to achieve acceptable reconstruction for medical diagnostics, therefore this research will implement dimensional reduction algorithms through compressed sensing for electrocardiogram signals (EKG). dimensional reduction is performed based on the fact that ECG signals can be reconstructed with linear combination coefficients with a bumpy base of small measurements with high accuracy. This study will use PCA for feature extraction on ECG signals. The data used are the ECG patient records on the website page www.physionet.org as many as 1200 with each attribute as many as 256 attributes. The total data dimension used is 1200x256, which means the data has 1200 rows and has as many as 256 columns. To show the accuracy of the dimensional reduction result, so it is performed classification on data using KNN and Naive Bayes. The classification results show that KKN can classify well with 84,02% accuracy rate and the Naive Bayes accuracy is 65,78%. for 100 dimensions The conclusion is those dimensional reductions for ECG data that have large dimensions, it still able to provide valid information like it uses the original data. Principle Component Analysis is a good method for reducing data dimensions by selecting certain features, so the dimensions of the data become smaller but still able to provide good accuracy to the reader.
Identification of Significant Proteins Associated with Diabetes Mellitus Using Network Analysis of Protein-Protein Interactions Usman, Muhammad Syafiuddin; Kusuma, Wisnu Ananta; Afendi, Farit Mochamad; Heryanto, Rudi
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.82 KB) | DOI: 10.18495/comengapp.v8i1.283

Abstract

Computation approach to identify significance of proteins related with disease was proposed as one of the solutions from the problem of experimental method application which is generally high cost and time consuming. The case of study was conducted on Diabetes Melitus (DM) type 2 diseases. Identification of significant proteins was conducted by constructing protein-protein interactions network and then analyzing the network topology. Dataset was obtained from Online Mendelian Inheritance in Man (OMIM) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) which provided protein data related with a disease and Protein-Protein Interaction (PPI), respectively. The results of topology analysis towards Protein-Protein Interaction (PPI) showed that there were 21 significant protein associated with DM where INS as a network center protein and AKTI, TCF7L2, KCNJ11, PPARG, GCG, INSR, IAPP, SOCS3 were proteins that had close relation directly with INS.
Technical Foundations of GIS for the planning and management of the educational sector in the city of Nasiriyah Dakhil, Ali fattah
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (557.767 KB) | DOI: 10.18495/comengapp.v8i1.284

Abstract

The local government of the city of Nasiriyah has always appealed for a number of problems which it described as the difficult problems facing the reality of education in the city of Nasiriyah in Iraq, pointing to a large shortage of school buildings and educational staff and overcrowded classrooms. In order to improve the status of education in general and in the city of Nasiriyah in particular, the researcher presented in this paper a number of methods and modern techniques, which are considered as the basis of the context of the unit of GIS in the Directorate of Education Dhi-Qar to study the current reality of the educational institution and to identify the foci of these problems to control and solve them in an effective and rapid manner. In this research, the programming, analytical and statistical methods of the ArcGIS program and Python programming language were used. The researcher concluded that following these principles leads to locating the focal points of the problems of the educational sector in the city of Nasiriyah, located in the Eastern Ring and the southeast of the city. Several recommendations have been made in this research to solve these problems.
Review of Optimization Techniques for Sizing Renewable Energy Systems Abubakar, Abdulkarim
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (364.526 KB) | DOI: 10.18495/comengapp.v8i1.285

Abstract

The growing evidence of the global warning phenomena and the rapid depletion of fossil fuels have drawn the world attention to the exploitation of renewable energy sources (RES). However standalone RES have been proven to be very expensive and unreliable in nature owing to the stochastic nature of the energy sources. Hybrid energy system is an excellent solution for electrification of areas where the grid extension is difficult and not economical. One of the main attribute of hybridising is to be able to optimally size each RES including storages with the aim of minimizing operation costs while efficiently and reliably responding to load demand. Hybrid RES emerges as a trend born out of the need to fully utilize and solve problems associated with the reliability of RES. This paper present a review of techniques used in recent optimal sizing of hybrid RES. It discusses several methodologies and criteria for optimization of hybrid RES. The recent trend in optimization in the field of hybrid RES shows that bio-inspired techniques may provide good optimization of system without extensive long weather data.

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