IMPLEMENTASI ALGORITMA GENETIKA DALAM OTOMATISASI PENJADWALAN WAWANCARA RESPONDEN BERBASIS WEBSITE PADA PT. MITRA MARKET RESEARCH (MMR)
Article Sidebar
Main Article Content
Abstract
Proses penjadwalan wawancara responden di PT. Mitra Market Research (MMR) selama ini kerap mengalami kendala efisiensi akibat kerumitan variabel yang harus disesuaikan, seperti ketersediaan waktu pewawancara, kriteria dan waktu responden, serta keterbatasan lokasi atau kuota harian. Penjadwalan secara manual tidak hanya memakan waktu lama, tetapi juga rentan terhadap kecenderungan bentrok (schedule conflict). Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem penjadwalan wawancara berbasis website memanfaatkan Algoritma Genetika untuk mengotomatisasi proses penyusunan jadwal secara optimal. Algoritma Genetika digunakan karena kemampuannya dalam menyelesaikan permasalahan kombinatorial kompleks (NP-Hard) dengan mencari kombinasi solusi terbaik berdasarkan kriteria fitness tertentu. Sistem dibangun dengan metode pengembangan perangkat lunak berbasis website, memanfaatkan parameter genetika seperti populasi awal, seleksi, crossover, dan mutasi. Hasil pengujian menunjukkan bahwa sistem berbasis Algoritma Genetika ini mampu menghasilkan kombinasi jadwal wawancara yang optimal tanpa adanya schedule conflict, serta berhasil memangkas waktu proses penjadwalan secara signifikan jika dibandingkan dengan cara manual. Implementasi sistem ini terbukti meningkatkan efisiensi operasional dan akurasi penjadwalan di PT. Mitra Market Research.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
1. Open Access Policy
Articles published in the journal are open-access articles distributed under the terms and conditions of the Creative Commons license. This aligns with international standards for scholarly publishing, ensuring that all research content is freely available online to the global research community without subscription or paywall barriers immediately upon publication.
2. Creative Commons License
Unless otherwise specified, all accepted and published works are licensed under the Creative Commons Attribution-ShareAlike (CC BY-SA) 4.0 International License.
Under this license, users are free to:
Share: Copy and redistribute the material in any medium or format.
Adapt: Remix, transform, and build upon the material for any purpose, even commercially.
Subject to the following terms:
Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
ShareAlike: If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
3. Author Rights & Archiving
Copyright Retention: Authors retain full ownership of the copyright for their published articles without restrictions, granting the journal a non-exclusive license to publish the work as the original publisher of record.
Self-Archiving: Authors are fully permitted to deposit all versions of their manuscript (preprint, accepted manuscript, and final published PDF) into institutional repositories, subject-specific repositories, or on their personal academic websites, provided that proper citation to the journal is maintained.
References
[1] A. Lau, "Penerapan Algoritma Genetika Dalam Penjadwalan Mata Kuliah", Jurnal Repository WICIDA, vol. 1, no. 1, pp. 1–10, 2023.
[2] R. Fan, Y. Zhang, and X. Liu, "Application of Optimal Scheduling Model Based on Improved Genetic Algorithm", IEEE Access, vol. 12, pp. 14502–14512, 2023.
[3] A. B. Prasetyo and D. A. Kristianto, "Sistem Penjadwalan Karyawan dengan Algoritma Genetika", Jurnal Biometrik dan Informatika (JBI), vol. 10, no. 2, pp. 85–94, 2023.
[4] H. Wijaya and M. R. N. Insan, "Penerapan Algoritma Genetika dalam Optimisasi Penjadwalan Sistem Informasi Akademik", Jurnal Sosial Teknologi, vol. 3, no. 2, pp. 103–107, 2023.
[5] D. Nasien and A. Andi, "Implementasi Algoritma Genetika untuk Otomatisasi Sistem Penjadwalan pada Lembaga Bimbingan Belajar", G-Tech: Jurnal Teknologi Terapan, vol. 5, no. 1, pp. 412–420, 2021.
[6] B. Firmansyah, D. S. Permana, N. Evianti, A. M. Wihandar, and A Kurniawan, "Penerapan Algoritma Genetika Dalam Mengatasi Jadwal Mengajar Yang Bentrok Pada Program Studi Informatika IBI Kosgoro 1957 Jakarta Indonesia", Jurnal Sistem Informasi Bisnis (JUNSIBI), vol. 2, no. 2, pp. 106–125, 2021.