Analisis Sistematis Penelitian Terkait Model Optimasi Penugasan Maksimum Menggunakan Metode Systematic Literature Review
Keywords:
maximum assigment problem, optimal task assignment, task allocation optimizationAbstract
Penelitian ini bertujuan untuk menganalisis perkembangan model optimasi penugasan maksimum melalui pendekatan Systematic Literature Review (SLR) berdasarkan panduan PRISMA 2020. Data diperoleh dari basis data Scopus dengan kata kunci maximum assignment problem, optimal task assignment, dan task allocation optimization pada periode 2022–2025. Dari total 351 artikel yang diidentifikasi, sebanyak 161 dihapus karena tidak memenuhi kriteria kelayakan otomatis, dan 40 artikel dikeluarkan karena tidak termasuk dalam jurnal bereputasi Q1–Q2. Setelah proses screening dan penilaian kelayakan, diperoleh 8 artikel utama yang dianalisis lebih lanjut. Hasil kajian menunjukkan bahwa penelitian terkini banyak mengintegrasikan algoritma klasik seperti Hungarian dengan pendekatan metaheuristik dan pembelajaran berbasis graf, guna meningkatkan efisiensi serta akurasi penugasan dalam sistem multi-agen. Selain itu, penggunaan Watase UAKE terbukti efektif membantu proses seleksi literatur secara transparan dan sistematis. Secara keseluruhan, tren penelitian mengarah pada pengembangan model optimasi yang lebih adaptif, terotomasi, dan relevan dengan kebutuhan sistem cerdas modern.
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