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

Authors

  • Achmad Noeman Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Denny Rahman Fauzi Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Dian Hartanti Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Abrar Hiswara Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Prio Kustanto Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Hafizah Hafizah Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Mayadi Mayadi Bhayangkara Jakarta Raya University, Jakarta, Indonesia
  • Hendarman Lubis Bhayangkara Jakarta Raya University, Jakarta, Indonesia

DOI:

https://doi.org/10.38035/sijdb.v2i1.79

Keywords:

Scheduling, Genetic Algorithms, PT. Tasya Putri Mandiri, Attendance System

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.

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Published

2024-08-20

How to Cite

Noeman, A., Rahman Fauzi, D., Hartanti, D., Hiswara, A., Kustanto, P., Hafizah, H., … Lubis, H. (2024). Employee Work Schedule Presence System Application Design at PT. Tasya Putry Mandiri Uses Genetic Algorithm Method. Siber International Journal of Digital Business (SIJDB), 2(1), 51–54. https://doi.org/10.38035/sijdb.v2i1.79

Issue

Vol. 2 No. 1 (2024): (SIJDB) Siber International Journal of Digital Business (July - September 2024)

Section

Articles

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Copyright (c) 2024 Achmad Noeman, Denny Rahman Fauzi, Dian Hartanti, Abrar Hiswara, Prio Kustanto, Hafizah Hafizah, Mayadi Mayadi, Hendarman Lubis

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