Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

ComEngApp : Computer Engineering and Applications Journal

comengapp
Website

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 215 Documents

1 2 3 4 5

Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms Mahdi Aghaie; Fatemeh Shokri; Meisam Yadolah Zade Tabari
Computer Engineering and Applications Journal Vol 2 No 1 (2013)
Publisher : Universitas Sriwijaya

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. Â Keyword- Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVMDOI:Â 10.18495/comengapp.21.161174

On Constructing Static Evaluation Function using Temporal Difference Learning Samuel Choi Ping Man
Computer Engineering and Applications Journal Vol 2 No 1 (2013)
Publisher : Universitas Sriwijaya

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:Â 10.18495/comengapp.21.175184

An Analysis of Adaptive Approach for Document Binarization Reza Firsandaya Malik; Saparudin -; Intan Septyliana
Computer Engineering and Applications Journal Vol 2 No 2 (2013)
Publisher : Universitas Sriwijaya

Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatosâ€™s method. Gatosâ€™s method is doing preprocessing, foreground estimation using Sauvolaâ€™s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvolaâ€™s method is final thresholding from Wiener filter image result and source image, and count F-Measure from both of these binary image results. By using optimum constant value on k value, n local window, Ksw and Ksw1, Gatosâ€™s method can produced binary image better than Sauvolaâ€™s method based on F-Measure value. Sauvolaâ€™s method produces average value F=84,62%, Sauvolaâ€™s method with Wiener filter produces average value F=99.06% and Gatosâ€™s method produces average value F=99,43%. Keyword : Degraded Document Image, Adaptive Approcah for Binarization, Gatosâ€™sÂ Method, Sauvolaâ€™s MethodDOI:Â 10.18495/comengapp.22.185194

An Immune Based Patient Anomaly Detection using RFID Technology Sri Listia Rosa; Siti Mariyam Shamsuddin; Evizal Evizal
Computer Engineering and Applications Journal Vol 2 No 2 (2013)
Publisher : Universitas Sriwijaya

Online product reviews is considered as a major informative resource which is useful for both customers and manufacturers. The online reviews are unstructured-free-texts in natural language form. The task of manually scanning through huge volume of review is very tedious and time consuming. Therefore it is needed to automatically process the online reviews and provide the necessary information in a suitable form. In this paper, we dedicate our work to the task of classifying the reviews based on the opinion, i.e. positive or negative opinion. This paper mainly addresses using ensemble approach of Support Vector Machine (SVM) for opinion mining. Ensemble classifier was examined for feature based product review dataset for three different products. We showed that proposed ensemble of Support Vector Machine is superior to individual baseline approach for opinion mining in terms of error rate and Receiver operating characteristics Curve. Â Key words: Opinion, Classification, Machine Learning.

Codes Correcting and Simultaneously Detecting Solid Burst Errors P. K. Das
Computer Engineering and Applications Journal Vol 2 No 2 (2013)
Publisher : Universitas Sriwijaya

Digital images are foremost source for information transfer. Due to advancement of the technology, images are now not treated as reliable source of information. Digital images can be edited according to the need. Adding and deleting content from an image is most easiest and popular way of creating image forgery, which is known as copy-move forgery. Digital Image Forensics is the field that deals with the authenticity of the images. Digital image forensics checks the integrity of the images by detecting various forgeries. In order to hide the traces of copy-move forgery there are editing operations like rotation, scaling, JPEG compression, Gaussian noise called as attacks, which are performed on the copied part of the image before pasting. Till now these attacks are not detected by the single method. The novel approach is proposed to detect image forgery by copy-move under above attacks by combining block-based and keypoint-based method. Keywords: Digital image forensics, copy-move forgery, passive blind approach, keypoint-based, block-based methods

Proposed Developements of Blind Signature Scheme Based on ECC F. Amounas; E. H. El Kinani
Computer Engineering and Applications Journal Vol 2 No 2 (2013)
Publisher : Universitas Sriwijaya

Detecting and gaining clues from the crime scene plays a major role in the process of investigation. Now a days with increase of cybercrime and fraud on the internet, digital forensics gaining importance. It needs to collect information the events happened at crime place. This paper deals with event reconstruction process which is useful for digital crime scene. The process of reconstruction is based on crime event and event characteristics. It also furnishes crime rate guess using some semi-formal techniques. Keyword: Digital Investigation, Digital Forensics, Events, Attack Trees, Reconstruction

In the emerging trends the pervasive nature across the computing environment shows that the system is platform independent and device independent. The system development is designed with the help of Structured Query Language and middleware infrastructure that are used to collect the information from various nodes. An essential feature of this proposed middleware architecture suites the device independent as the major supporting capability to the system. This facilitates to add new device types in the system feels easy through the use of device self-description.Â It mainly focuses on the issues related to the heterogeneity of the different devices composing a pervasive system: This aspect is investigated both at data management and at physical integration levels. Using the nontrivial approach aims at handling the related issues are resolved with the corresponding solution. Keyword: Perla, Cloud Monitoring, Middleware, Declarative Language

On Constructing Static Evaluation Function using Temporal Difference Learning Samuel Choi Ping Man
Computer Engineering and Applications Journal Vol 2 No 2 (2013)
Publisher : Universitas Sriwijaya

An Outlier is a data point which is significantly different from the remaining data points. Outlier is also referred as discordant, deviants and abnormalities. Outliers may have a particular interest, such as credit card fraud detection, where outliers indicate fraudulent activity. Thus, outlier detection analysis is an interesting data mining task, referred to as outlier analysis. Detecting outliers efficiently from dataset is an important task in many fields like Credit card Fraud, Medicine, Law enforcement, Earth Sciences etc. Many methods are available to identify outliers in numerical dataset. But there exist limited number of methods are available for categorical and mixed attribute datasets. In the proposed work, a novel outlier detection method is proposed. This proposed method finds anomalies based on each recordâ€™s â€œmulti attribute outlier factor through correlationâ€ score and it has great intuitive appeal. This algorithm utilizes the frequency of each value in categorical part of the dataset and correlation factor of each record with mean record of the entire dataset. This proposed method used Attribute Value Frequency score (AVF score) concept for categorical part. Results of the proposed method are compared with existing methods. The Bank data (Mixed) is used for experiments in this paper which is taken from UCI machine learning repository. Keyword: Outlier, Mixed Attribute Datasets, Attribute Value Frequency Score

E-mail spam filtering by a new hybrid feature selection method using IG and CNB wrapper Seyed Mostafa Pourhashemi
Computer Engineering and Applications Journal Vol 2 No 3 (2013)
Publisher : Universitas Sriwijaya

The growing volume of spam emails has resulted in the necessity for more accurate and efficient email classification system. The purpose of this research is presenting an machine learning approach for enhancing the accuracy of automatic spam detecting and filtering and separating them from legitimate messages. In this regard, for reducing the error rate and increasing the efficiency, the hybrid architecture on feature selection has been used. Features used in these systems, are the body of text messages. Proposed system of this research has used the combination of two filtering models, Filter and Wrapper, with Information Gain (IG) filter and Complement NaÃ¯ve Bayes (CNB) wrapper as feature selectors. In addition, Multinomial NaÃ¯ve Bayes (MNB) classifier, Discriminative Multinomial NaÃ¯ve Bayes (DMNB) classifier, Support Vector Machine (SVM) classifier and Random Forest classifier are used for classification. Finally, the output results of this classifiers and feature selection methods are examined and the best design is selected and it is compared with another similar works by considering different parameters. The optimal accuracy of the proposed system is evaluated equal to 99%.

Two phase privacy preserving data mining Pooja Gupta; Ashish Kumar
Computer Engineering and Applications Journal Vol 2 No 3 (2013)
Publisher : Universitas Sriwijaya

The paper proposes a framework to improve the privacy preserving data mining. The approach adopted provides security at both the ends i.e. at the data transmission time as well as in the data mining process using two phases. The secure data transmission is handled using elliptic curve cryptography (ECC) and the privacy is preserved using k-anonymity. The proposed framework ensures highly secure environment. We observed that the framework outperforms other approaches [8] discussed in the literature at both ends i.e. at security and privacy of data. Since most of the approaches have considered either secure transmission or privacy preserving data mining but very few have considered both. We have used WEKA 3.6.9 for experimentation and analysis of our approach. We have also analyzed the case of k-anonymity when the numbers of records in a group are less than k (hiding factor) by inserting fake records. The obtained results have shown the pattern that the insertion of fake records leads to more accuracy as compared to full suppression of records. Since, full suppression may hide important information in cases where records are less than k, on the other hand in the process of fake records insertion; records are available even if number of records in a group is less than k.

Page 2 of 22 | Total Record : 215

1 2 3 4 5

Filter by Year

2012 2024

Filter By Issues

All Issue Vol 13 No 1 (2024) Vol 12 No 3 (2023) Vol 12 No 2 (2023) Vol 12 No 1 (2023) Vol 11 No 3 (2022) Vol 11 No 2 (2022) Vol 11 No 1 (2022) Vol 10 No 3 (2021) Vol 10 No 2 (2021) Vol 10 No 1 (2021) Vol 9 No 3 (2020) Vol 9 No 2 (2020) Vol 9 No 1 (2020) Vol 8 No 3 (2019) Vol 8 No 2 (2019) Vol 8 No 1 (2019) Vol 7 No 3 (2018) Vol 7 No 2 (2018) Vol 7 No 1 (2018) Vol 6 No 3 (2017) Vol 6 No 2 (2017) Vol 6 No 1 (2017) Vol 5 No 3 (2016) Vol 5 No 2 (2016) Vol 5 No 1 (2016) Vol 4 No 3 (2015) Vol 4 No 2 (2015) Vol 4 No 1 (2015) Vol 3 No 3 (2014) Vol 3 No 2 (2014) Vol 3 No 1 (2014) Vol 2 No 3 (2013) Vol 2 No 2 (2013) Vol 2 No 1 (2013) Vol 1 No 2 (2012) Vol 1 No 1 (2012) More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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