ISTEM INFORMASI PEMBERIAN BONUS UPAH DAN PENJADWALAN KARYAWAN MENGGUNAKAN METODE ALGORITMA GENETIKA

• Ismail Akbar

  Fakultas Teknik, Teknik Informatika, Universitas Widyagama Malang

• Fitri Marisa

  Fakultas Teknik, Teknik Informatika, Universitas Widyagama Malang

• Indra Dharma Wijaya

  Fakultas Teknik, Teknik Informatika, Universitas Widyagama Malang

By following the development of the market and the needs of the community, it is increasingly needed a technology to improve the quality and results of its production with careful planning, in order to avoid the level of loss and reduce production in the company. This is experienced by companies UD. Muria PS who is engaged in animal husbandry. Which has several problems in scheduling employees to take their products. Which also has an impact on the gap between employees on the bonus wages they receive. By building a scheduling information system and providing bonus wages, this research uses php programming language and website-based programming and applies genetic algorithms in it to more easily manage employee schedules and provide bonus rewards fairly and evenly. This genetic algorithm process has a parameter of the vehicle, coolie, and time in the scheduling process. and schedule parameters in the employee bonus wage process. Based on the results of the user trial, the respondents strongly agree with the existence of this application. Which of the 14 respondents said it was feasible to apply to the company UD. Muria PS with a result of 87.37%. It is expected that with this application, employee scheduling and bonus wage issues can help solve it.

 

Hardianti, Y. & Purwanto, P., 2013. Penerapan Algoritma Genetika dalam Penyelesaian Travelling Salesman Problem with Prefedence Constraints (TSPPC). p. 4.

Imbar, R. V. & Septiano, K., 2013. Sistem HRD Perekrutan, Penggajian, dan Penjadwalan Menggunakan Algoritma Genetika pada Hotel Nirwana. Jurnal Informatika, 9(1), pp. 65-80.

Suhartono, E., 2015. Optimasi Penjadwalan Mata Kuliah dengan Algoritma Genetika (Studi Kasus di AMIK JTC Semarang). INFOKAM, Issue 2, pp. 132-146.

Sutojo, T., Mulyanto, E. & Suhartono, V., 2011. Kecerdasan Buatan. 2011: CV. Andi Offset.

Zukhri, Z., 2014. Algoritma Genetika Metode Komputasi Evolusioner untuk Menyelesaikan Masalah Optimasi. 1 ed. Yogyakarta: CV. Andi Offset.

• PDF (Indonesian)