基因方法应用于雅加达STI&K大学信息系统

Linda Wahyu Widiyanti, S. Suyatno
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引用次数: 0

摘要

随着研究项目中科学领域的增多,大学的讲座活动也变得越来越复杂。其中一个复杂的问题是给学生和辅助讲师的课程安排。课程的数量和讲师的数量使得排课过程需要额外的管理。雅加达STMIK是一所计算机领域的学院,在计算机领域有几个研究项目,包括信息系统研究项目、计算机系统和信息管理。在每堂课开始的时候,他们经常会遇到安排课程的困难。需要一个可以处理调度数据的系统是非常重要的,这样它可以帮助最大化过程,使讲座活动更有组织。针对学生和讲师排课过程复杂的问题,本研究采用遗传方法开发了一个排课系统。使用这种遗传方法可以最大限度地减少课程之间、讲师之间和班级之间的时间冲突。本排课系统的开发采用PHP语言和MySQL数据库,可以在线应用,使排课结果直接通知教师和学生。根据所开发的系统的应用,它可以帮助雅加达STMIK的调度部门更快地制定时间表,因为它可以最大限度地减少时间表冲突,更快地通知时间表,使所有教师和学生都能更好地做好准备。人工排程和遗传排程的平均速度分别为69.67和69.72。
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PENERAPAN METODE GENETIK PADA SISTEM INFORMASI PENJADWALAN PERKULIAHAN STMIK JAKARTA STI&K
Lecture activities from a university are increasingly complex along with the number of scientific fields in a study program. One of these complications is the scheduling of courses given to students and supporting lecturers. The number of courses and the large number of lecturers make the scheduling process require extra in managing it. STMIK Jakarta STI&K is a college in the field of computers that has several study programs in the field of computers consisting of the Information Systems Study Program, Computer Systems and Information Management. At the beginning of each lecture, they often experience difficulties in scheduling the lectures. The need for a system that can process scheduling data is very important so that it can help maximize the process so that lecture activities are more organized. Answering the problem of the complicated process of scheduling lectures for students and lecturers, in this study a scheduling system was developed using the Genetic Method. The use of this genetic method can minimize scheduling conflicts between courses, between lecturers and between classes. The development of this scheduling system was developed using the PHP language and MySQL database so that it can be applied online so that the results can be directly informed to lecturers and students. Based on the application of the system developed, it helps the scheduling department of STMIK Jakarta STI&K faster in making schedules because it minimizes schedule conflicts, informs schedules more quickly so that all lecturers and students are better prepared. The comparison of the average speed of making schedules manually and using genetic methods is between 69.67 and 69.72.
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