Literature Reveiew : Penerapan Machine Learning Pada Supply Chain Management
DOI:
https://doi.org/10.55338/justikpen.v5i2.427Keywords:
Machine Learning, Supply Chain Management, Forecasting, Prediksi, AnalysisAbstract
Meskipun pemanfaatan Machine Learning (ML) dalam Supply Chain Management (SCM) kian masif, literature yang tersedia saat ini cenderung terfragmentasi. Belum ditemukan sintesis sistematis yang secara tajam mematikan efektivitas ML dalam menghadapi volatilitas ekstrim pada periode 2020-2025. Studi ini hadir untuk mengisi kekosongan tersebut melalui Systematic Literature Review (SLR) berbasis protokol PRISMA dan analisis tematik VOSviewer terhadap literatur kunci dari ScienceDirect. Temuan kami menunjukan dominasi supervised learning, dengan algoritma ensemble mampu mencapai akurasi luar biasa (R2 hingga 0,99) Lebih jauh riset ini mengungkapkan pergeseran paradigma dari sekedar prediksi angka menuju analitik perspektif dan mitigasi risiko demi membangun resiliensi rantai pasok. Kontribusi utama penelitian ini terletak pada konsolidasi metrik evaluasi lintas sektor serta rekomendasi transisi menuju sistem pengambilan keputusan lebih adaptif. Dengan demikian, SLR ini memposisikan ML sebagai instrumen strategis untuk navigasi ketidakpastian yang ada, sekaligus menutup celah kerangka kerja integratif yang selama ini terabaikan pada penelitian sebelumnya.
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Copyright (c) 2026 Muhammad Fauzani Akbar, Ita Damaris Br Munthe, Albert Julian Marito Silaban, Ahmad Dwi Abiyyu, Artha Putri Br Karo
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