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ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
Core Subject : Science, Engineering,
Computer Science & IT Engineering
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.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 318 Documents
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Robotics Current Issues and Trends Nurmaini, Siti
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

The ongoing research and development work in the field of robotics have resulted in so many new technological trends. There are revolution which are being achieved with the use of latest technology in robotics, giving birth to new possibilities for automating tasks and enriching human lives for better. One can easily witness the presence of robotics in every sphere of life from industrial robots, service robots to personal robots. It other words, robots have become a part of our world to meet new demands of a new society.DOI: 10.18495/comengapp.21.117120
An Immune Based Patient Anomaly Detection using RFID Technology Rosa, Sri Listia; Shamsuddin, Siti Mariyam; Evizal
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

Detecting of anomalies patients data are important to gives early alert to hospital, in this paper will explore on anomalies patient data detecting and processing using artificial computer intelligent system. Artificial Immune System (AIS) is an intelligent computational technique refers to human immunology system and has been used in many areas such as computer system, pattern recognition, stock market trading, etc. In this case, real value negative selection algorithm (RNSA) of artificial immune system used for detecting anomalies patient body parameters such as temperature. Patient data from monitoring system or database classified into real valued, real negative selection algorithm results is real values deduction by RNSA distance, the algorithm used is minimum distance and the value of detector generated for the algorithm. The real valued compared with the distance of data, if the distance is less than a RNSA detector distance then data classified into abnormal. To develop real time detecting and monitoring system, Radio Frequency Identification (RFID) technology has been used in this system. Keywords: AIS, RNSA, RFID, AbnormalDOI: 10.18495/comengapp.21.121142
Codes correcting and simultaneously detecting solid burst errors Das, P.K.
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

Detecting and correcting errors is one of the main tasks in coding theory. The bounds are important in terms of error-detecting and -correcting capabilities of the codes. Solid Burst error is common in several communication channels. This paper obtains lower and upper bounds on the number of parity-check digits required for linear codes capable of correcting any solid burst error of length b or less and simultaneously detecting any solid burst error of length s(>b) or less. Illustration of such a code is also provided.Keywords: Parity check matrix, Syndromes, Solid burst errors, Standard arrayDOI: 10.18495/comengapp.21.143150  
Proposed Developments of Blind Signature Scheme based on The Elliptic Curve Discrete Logarithm Problem Amounas, F.; El Kinani, E.H.
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

In recent years, Elliptic Curve Cryptography (ECC) has attracted the attention of researchers due to its robust mathematical structure and highest security compared to other existing algorithm like RSA. Our main objective in this work was to provide a novel blind signature scheme based on ECC. The security of the proposed method results from the infeasibility to solve the discrete logarithm over an elliptic curve. In this paper we introduce a proposed to development the blind signature scheme with more complexity as compared to the existing schemes. Keyword: Cryptography, Blind Signature, Elliptic Curve, Blindness, Untraceability.DOI: 10.18495/comengapp.21.151160
Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms Aghaie, Mahdi; Shokri, Fatemeh; Tabari, Meisam Yadolah Zade
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

There are far more cars on the road now than there used to be. Therefore, Controlling and managing the huge volume of traffic is virtually impossible without the use of computer technology. This paper represents design and implement of an intelligent system for license plate recognition based on three main steps. This process includes the detection of license plate location, character segmentation and character recognition. In this study, we used Classifier svm to detect the characters. According to the results, the performance of the proposed system is better compared to similar algorithms such as neural network. It is worth mentioning that Recognition Approach is tested in various conditions and results are described.   Keyword- Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVMDOI: 10.18495/comengapp.21.161174
On Constructing Static Evaluation Function using Temporal Difference Learning Man, Samuel Choi Ping
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

Programming computers to play board games against human players has long been used as a measure for the development of artificial intelligence. The standard approach for computer game playing is to search for the best move from a given game state by using minimax search with static evaluation function. The static evaluation function is critical to the game playing performance but its design often relies on human expert players. This paper discusses how temporal differences (TD) learning can be used to construct a static evaluation function through self-playing and evaluates the effects for various parameter settings. The game of Kalah, a non-chance game of moderate complexity, is chosen as a testbed. The empirical result shows that TD learning is particularly promising for constructing a good evaluation function for the end games and can substantially improve the overall game playing performance in learning the entire game.DOI: 10.18495/comengapp.21.175184
Optimization of Distributed RSA Encryption and Decription Processing Using Process Scheduling Method In Single Board Computer Cluster Architecture (SBC) Arief, Sofyan Nur; Firdaus, Vipkas Al Hadid; Prasetyo, Arief
Computer Engineering and Applications Journal (ComEngApp) Vol. 13 No. 1 (2024)
Publisher : Universitas Sriwijaya

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Abstract

Data security is still a major issue regarding the need for data confidentiality. The encryption process using the RSA algorithm is still the most popular method used in securing data because the complexity of the mathematical equations used in this algorithm makes it difficult to hack. However, the complexity of the RSA algorithm is still a major problem that hinders its application in a more complex application. Optimization is needed in the processing of this RSA algorithm, one of which is by running it on a distributed system. In this paper, we propose an approach with a FIFO process scheduling algorithm that runs on a single board computer cluster. The test results show that the allocation of resources in a system that uses a FIFO process scheduling algorithm is more efficient and shows a decrease in the overall processing time of RSA encryption.
Inter Patient Atrial Fibrillation Classification Using One Dimensional Convolution Neural Network Rifai, Ahmad; Rachmatullah, Muhammad Naufal; Sutarno; Tutuko, Bambang
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 1 (2022)
Publisher : Universitas Sriwijaya

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Abstract

Atrial fibrillation is the most common type of arrhythmia. The process of detecting AF disease is quite difficult. This is because it is necessary to detect the presence or absence of a P signal wave in the ECG signal. However, this method requires special expertise from a cardiologist. Several literatures have proposed an automatic ECG classification system. However, the intra-patient paradigm does not simulate real-world scenarios. One of the challenges in the inter-patient paradigm is the morphological differences between one subject and another. In order to overcome the problems that arise in the automatic classification of ECG signal patterns a deep learning approach was proposed. This study proposes the classification process of atrial fibrillation in the inter-patient paradigm using a one-dimensional convolutional neural network architecture. The test is divided into two cases: two labels (Normal and AF) and three labels (Normal, AF and Non-AF). In the case of two test labels with an inter-patient scheme, the performance was 100% for all test metrics (accuracy, sensitivity, precision, and F1-Score). However, in the three-label case, the model's performance decreased to 85.95, 70.02, 72.50, 71.19 for accuracy, sensitivity, precision and F1-Score, respectively.
Query Reformulation for Indonesian Question Answering System Using Word Embedding of Word2Vec Utami, Alvi Syahrini; Yusliani, Novi; Marieska, Mastura Diana; Abdiansyah
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 1 (2022)
Publisher : Universitas Sriwijaya

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Abstract

Query reformulation is one of the tasks in Information Retrieval (IR), which automatically creates new queries based on previous queries. The main challenge of query reformulation is to create a new query whose meaning or context is similar to the old query. Query reformulation can improve the search for relevant documents for Open-domain Question Answering (OpenQA). The more queries are given to the search system, and the more documents will be generated. We propose a Word Predicted and Substituted (WPS) method for query reformulation using a word embedding word2vec. We tested this method on the Indonesian Question Answering System (IQAS). The test results obtained an E-1 value of 81% and an E-2 value of 274%. These results prove that the query reformulation method with WPS and word-embedding can improve the search for potential IQAS answers.
Identification of Stunting Disease using Anthropometry Data and Long Short-Term Memory (LSTM) Model Amin, Faris Mushlihul; Novitasari, Dian Candra Rini
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 1 (2022)
Publisher : Universitas Sriwijaya

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Abstract

Children with unbalanced nutrition are currently crucial health issues and under the spotlight around the world. One of the terms for malnourished children is stunting. Stunting is a disease of malnutrition found in children aged under 5 years; as many as 70% of stunting sufferers are children aged 0-23 months. There are several ways to diagnose stunting, one of which is using stunting anthropometry. Stunting anthropometry can measure the physique of children so that some of the features that characterize the presence of stunting can be identified. Features resulted from the stunting anthropometry cover age, height, weight, gender, upper arm circumference, head size, chest circumference, and hip fat measurement. The process of identifying stunting can be simplified using an intelligent system called the Computer-Aided Diagnosis (CAD) system. CAD system contains 2 main processes, namely preprocessing and classification. Preprocessing includes normalization and augmentation of data using the SMOTE method. The classification process in this study uses the LSTM method. LSTM is a modification of the Recurrent Neural Network (RNN) method by adding a memory cell so that it can store memory data for a long time and in large quantities. The results of this study compare between the results of models that apply preprocessing and the one without preprocessing. The model that only uses LSTM has the best accuracy of 78.35%; the model with normalization produces an accuracy of 81.53%; the model that uses SMOTE produces an accuracy of 81.66%; and the model that uses normalization and SMOTE produces the best accuracy of 85.79%.

Page 25 of 32 | Total Record : 318

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