Genetic algorithm for event scheduling system

Hasan Basari, Abd Samad and Hussin, Burairah and Jalal, Siti Musliza and Mohd Isa, Nabihah (2010) Genetic algorithm for event scheduling system. Journal Of Telecommunication, Electronic And Computer Engineering (JTEC), 2 (2). pp. 81-85. ISSN 2180-1843

Preview

Text JTEC_PaperFinalv2.pdf Download (1MB)

Abstract

UTeM’s Event Alert System (UTeM-EAS) is an improved version of previous Event Alert System in Universiti Teknikal Malaysia Melaka (UTeM) official site that aims to apply Artificial Intelligence (AI) in order to provide its users with events priority. This newer system intend be more user friendly by providing organized management. The improved version is also designed to have the capability of sending Short Message Service (SMS) among UTeM’s staff to notify them of future events. Some researches about another existing Event Alert Sytem are carried to provide more understanding to the system to be developed. UTeM-EAS then is created by exploiting one of AI approach namely Genetic Algorithm (GA) with Crossover Technique. There are four main interfaces that ask for login information, add, edit and view events details. As for the development environment, UTeM-EAS is developed and to run in windows XP with support of Adobe Dreamweaver and MS SQL Server. Ozeki Messager 6 are installed and configured for this system to operate with its SMS function. The functionality, usability and security testing are conducted between UTeM’s staffs and administrators itself to measure the performance and user acceptance of the proposed system. Aside from achieving its development objectives, UTeM-EAS also gain great satisfactions from most of its tested users. The system could be more efficient if password encryption is applied and the system is able to reply the message sent by UTeM’s staff asking for further events details.

Item Type:	Article
Uncontrolled Keywords:	intelligent system, genetic algorithm, artificial intelligence.
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Dr. Abd. Samad Hasan Basari
Date Deposited:	09 Dec 2011 12:55
Last Modified:	01 Jun 2023 11:43
URI:	http://eprints.utem.edu.my/id/eprint/238
Statistic Details:	View Download Statistic

Actions (login required)

View Item