<![CDATA[scheduling is very closely related to teaching and learning activities in a school that aims to support, facilitate, enhance the quality of education and improve discipline in the process of teaching and learning activities. The problem faced in making a schedule of subjects is time, the process of making a schedule takes quite a long time in the process of processing the schedule. Of the algorithms used in scheduling problems, algortima Artificial Bee Colony is an algorithm inspired by the behavior of honeybee colonies that work based on the way bees forage for food. Algortima Artificial Bee Colony is known to have advantages over other optimization algorithms that are very efficient in finding optimal solutions. But the Artificial Bee Colony algorithm has its drawbacks that, if the dimensions of the problem increase, the exchange of information is still limited to one dimension. The weakness of Artificial Bee Colony is what makes the opportunity to develop ABC, namely, Hybrid Artificial Bee Colony (HABC) by adding a crossover operator of genetic algorithms. Genetics algorithm's crossover operator inserted into ABC algorithm to improve exchange of information between bees. It can be concluded that the application of HABC methods can do the optimization process quite well in scheduling issues with fairly low schedule clashing results. Based on the results of trials conducted five times, the results that scheduling applications using the HABC Algorithm can produce a schedule of subjects by clashing to a minimum with an average accuracy percentage rate of 98.03%]]>
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