Sistem Informasi Pelaksanaan Proyek Akhir PCR dengan Pembebanan Dosen dan Penjadwalan Sidang Menggunakan Metode Algoritma Genetika
ABSTRAK
Pada saat ini sistem pelaksanaan
proyek akhir pada pembebanan dosen, penjadwalan sidang proposal, dan sidang akhir
yang ada di Politeknik Caltex Riau masih dilakukan secara manual. Sistem
informasi pelaksanaan proyek akhir dengan pembebanan dosen dan penjadwalan
sidang menggunakan Algoritma Genetika dapat memberikan solusi terbaik dari
kemungkinan-kemungkinan masalah human error yang ada. Pada sistem ini
permasalahan yang dapat diselesaikan dengan Algoritma Genetika adalah
pembebanan dosen dan penjadwalan sidang. Adapun data dosen, mahasiswa, judul,
dan waktu yang tersedia merupakan data–data yang akan diproses dengan
memasukkan parameter jumlah generasi, populasi, peluang crossover, dan peluang mutasi. Algoritma Genetika didasarkan pada
proses seleksi, crossover, dan
mutasi. Hasil keluaran sistem menggunakan
Algoritma Genetika yaitu: data pembebanan dosen, penjadwalan sidang proposal,
dan sidang akhir. Sehingga
diperoleh optimasi yaitu kondisi dimana terjadi kombinasi terbaik untuk
pasangan judul dengan dosen pembimbing maupun reviewer serta jadwal sidang yang akan dibuat. Data tersebut dapat membantu koordinator dalam
menyelesaikan tugas pembuatan data pembebanan dan penjadwalan. Pengguna sistem
terdiri dari koordinator, dosen dan mahasiswa. Sistem ini memberikan kemudahan
bagi pengguna untuk mengakses informasi data pembebanan dosen, jadwal sidang
proposal, dan sidang akhir serta data-data pelaksanaan proyek akhir lainnya.
Kata kunci: Penjadwalan, Pembebanan,
Algoritma Genetika, Proyek Akhir.
ABSTRACT
At
this time, final project implementation in
the lecturers’ task, proposal sessions scheduling, and final project at the Politeknik Caltex Riau are still manually implemented. Information
system projects implementation with the lecturers’ task and sessions scheduling
using Genetic Algorithm can provide the best solution from the possibilities of
human error. In this system, problems that can be solved by Genetic Algorithm
are tasking and scheduling. Data of lecturers, students, title, and time
available are data to be processed by entering the parameters such as number of
generations, population, crossover opportunities, and mutation opportunities.
Genetic algorithm is based on the process of selection, crossover, and
mutation. Outputs are : lecturers’ tasking data, proposal sessions, and final
project sessions. Optimization
in order to obtain the best combination of conditions which occur to pairs with
the title of supervisor and a reviewer as well as schedule session that will be
made. The users of sistem are coordinators, lecturers, and students. This
system makes it easy for users to access information such as lecturers’ tasking
data, proposal sessions scheduling, and final project session scheduling as
well as data the other final project implementation.
Kata kunci: Scheduling, Tasking,
Genetic Algorithm, Final Project.
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