Employee Work Schedule Presence System Application Design at PT. Tasya Putry Mandiri Uses Genetic Algorithm Method

Employee scheduling planning is a problem faced by many companies that have many employees. The traditional scheduling process is carried out by recording employee data one by one and collecting them in the form of an Excel report which is inefficient and takes a lot of time. Apart from that, to match the schedules, management needs to take great pains to arrange shift times so that they match and do not conflict between one shift schedule and another shift schedule. This method is very inefficient because it takes a long time if it turns out there is an error in the schedule. A popular method for making schedules is to use a genetic algorithm which is able to arrange schedules using a random approach to find schedule solutions that are most effective and do not collide with each other. Research was conducted to create a schedule from a list of existing employees. As a result, the schedule produced using a genetic algorithm was proven to be more optimal and faster.

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Publication Details

Journal
Siber International Journal of Digital Business (SIJDB)
Published
2024-08-20
DOI
https://doi.org/10.38035/sijdb.v2i1.79
Primary Topic
Blockchain Technology in Education and Learning
Type
article
Field-Weighted Citation Impact
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article

Employee Work Schedule Presence System Application Design at PT. Tasya Putry Mandiri Uses Genetic Algorithm Method

Hendarman Lubis, Achmad Noe’man, Hafizah Hafizah, Prio Kustanto et al.
Siber International Journal of Digital Business (SIJDB)
Blockchain Technology in Education and Learning
article

Employee Work Schedule Presence System Application Design at PT. Tasya Putry Mandiri Uses Genetic Algorithm Method

Hendarman Lubis, Achmad Noe’man, Hafizah Hafizah, Prio Kustanto, Mayadi Mayadi, Dian Hartanti, Abrar Hiswara, Denny Rahman Fauzi
article en

Abstract

Employee scheduling planning is a problem faced by many companies that have many employees. The traditional scheduling process is carried out by recording employee data one by one and collecting them in the form of an Excel report which is inefficient and takes a lot of time. Apart from that, to match the schedules, management needs to take great pains to arrange shift times so that they match and do not conflict between one shift schedule and another shift schedule. This method is very inefficient because it takes a long time if it turns out there is an error in the schedule. A popular method for making schedules is to use a genetic algorithm which is able to arrange schedules using a random approach to find schedule solutions that are most effective and do not collide with each other. Research was conducted to create a schedule from a list of existing employees. As a result, the schedule produced using a genetic algorithm was proven to be more optimal and faster.

Siber International Journal of Digital Business (SIJDB)Vol. 2(1)
Universitas Bhayangkara Jakarta Raya (ID)
Openalex Percentile: Top 49%
Blockchain Technology in Education and Learning
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