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APTIKOM Journal on Computer Science and Information Technologies (CSIT)
Published by Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer
ISSN : 25282417     EISSN : 25282425     DOI : 10.34306
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Electrical & Electronics Engineering Energy Materials Science & Nanotechnology
APTIKOM Journal on Computer Science and Information Technologies is a peer-reviewed international journal that publish original research article, review papers, short communications that will have an immediate impact on the ongoing research in all areas of Computer Science, Informatics, Electronics Engineering, Communication Network and Information Technologies. The journal is published four-monthly (March, July and November) by the Indonesian Association of Higher Education Institutions in Computer Science and Information Technology (APTIKOM).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)" : 5 Documents clear
SURVEY BASED CLASSIFICATION OF BUG TRIAGE APPROACHES Yadav, Asmita; Singh, Sandeep Kumar
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
Publisher : APTIKOM Publisher

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Abstract

This paper presents a comprehensive survey of bug triaging approaches in three classes namely machine learning based, meta-data based and profile based. All approaches under three categories are critically compared and some potential future directions and challenges are reported. Findings from the survey show that there is a lot of scope to work in cold-start problem, developer- profiling, load balancing, and reopened bug analysis.
WIRELESS SENSOR NETWORK FOR REAL-TIME FLOOD MONITORING BASED ON 6LOWPAN COMMUNICATION STANDARD Nuhu, B Kontagora; Arulogun, O. T.; Adeyanju, Ibrahim Adepoju; M., Abdullahi I.
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Abstract

Riverine flood is a major disaster faced by most countries and has significant adverse effect on long term economic growth of affected regions and their environments. Several systems have previously employed different technologies to monitor riverine flood but are expensive with low accuracy and consumes high amount of energy. In this paper, we proposed an energy efficient and accurate flood monitoring system. The system leverages on Internet Protocol Version 6 over Low Power Wireless Personal Area Network (6loWPAN) technology to construct a Wireless Sensor Network (WSN) comprising of two XM1000 motes and a rule-base water level monitoring application. The motes were configured using NesC programming for flood monitoring with Basestation and water level sensing applications. The water level sensing mote samples and transmits real-time water level information to the Basestation mote which interfaces with a rule-based water level monitoring application. The application compares current water level with a predetermined threat level and alerts relevant agencies when flood is imminent via an email. The results obtained from the emulation of the developed system showed that, it achieved an accuracy of 95.3% in water level monitoring with a Mean Squared Error of 5.1. The power consumed in transmitting a packet of 2 bytes payload plus other overhead was 0.4?J and 0.0396mJ with and without 6loWPAN configuration respectively.
EVALUATING BLIND IMAGE QUALITY USING RBF NEURAL NETWORK Soliga, Abi; Jasil, Godlin
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
Publisher : APTIKOM Publisher

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Abstract

Blind Image Quality Assessment (BIQA) methods are the most part feeling mindful. The BIQA method learns regression models from preparing images with human subjective scores to predict the perceptual nature of test images. The general quality of image and the nature of every image patches are measured by normal pooling. By coordinating the components of normal picture measurements got from different signs, we take a multivariate Gaussian model of picture patches from an accumulation of unblemished regular pictures. The proposed radial bias function neural network method is used to evaluate the quality of images and this method represents the structure of picture distortions with flexibility.
PERFORMANCE ANALYSIS OF REED-SOLOMON CODES CONCATENATED WITH CONVOLUTIONAL CODES OVER AWGN CHANNEL Mergu, Kattaswamy
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Abstract

With rapid growth in today?s technology, digital communication is playing a major role to provide hostile environment to meet various applications. In this communication, Coding plays a prominent role to contribute error free transmission through channel coding which improves capacity of a channel by adding some redundant bit to the original information. One way to provide a better performance of the communication system is by concatenating different types of channel coding techniques. The concatenation can be done either in parallel or serial. The primary aim of this paper is to concatenate the Reed-Solomon codes with Convolutional codes in series, which provides better results comparing with single coding techniques. The performance of the concatenation of Reed-Solomon codes with Convolutional codes can be evaluated by finding bit error rate with various values of signal-to-noise ratio over AWGN channel. The analytical result has been obtained by using MATLAB/OCTAVE.
FUZZY-ANT COLONY BASED ROUTING ON ROAD NETWORKS Saravanan, S.; Jayanthiladevi, A.; Geetha, M.
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
Publisher : APTIKOM Publisher

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Abstract

Route selection is essential in everyday life. We have several algorithms for detecting efficient route on Large Road Networks. This paper introduces the hierarchical community, is presented. It splits large road networks into hierarchical structure. It introduces a multi parameter route selection system which employs Fuzzy Logic (FL) and ant?s behavior in nature is applied to the dynamic routing. The important rates of parameters such as path length and traffic are adjustable by the user. The purposes of the new hierarchical routing algorithm significantly reduce the search space. We develop a community-based hierarchical graph model that supports Dynamic, efficient route computation on large road networks.

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