Analisis penerapan artificial intellegence (AI) pada manajemen risiko rantai pasok
Keywords:
Artificial Intelligence, Manajemen, Machine Learning, Neural NetworksAbstract
Supply chain management is a network that manages the organization of a company from the top (beginning) to the bottom (end). Global supply chains face various complex and evolving risks, such as logistics disruptions, fluctuations in raw material prices, and natural disasters. This study aims to provide insights into AI in supply chain risk management, supporting better decision-making regarding AI investment, developing implementation strategies, and selecting the right AI solutions. The research uses the Systematic Literature Review (SLR) method to collect, evaluate, and synthesize scientific data relevant to the topic of discussion published from 2019 to 2024. The research data collection strategy resulted in 71 studies, of which 26 primary studies were the basis of this research. The study results show that AI is beneficial in reducing the impact or risk on supply chain management. This study implies that AI matters to improving efficiency and effectiveness in supply chain management. Machine Learning (ML) and Neural Networks (NN) are the most widely used AI models. Appropriate AI models can assist companies in identifying, analyzing, and managing risks in the supply chain according to the company's existing fields.
Abstrak
Manajemen rantai pasok merupakan suatu jaringan yang mengelola organisasi suatu perusahaan dari atas (awal) hingga ke bawah (akhir). Rantai pasok global saat ini dihadapkan dengan berbagai risiko yang kompleks dan terus berkembang, seperti gangguan logistik, fluktuasi harga bahan baku, dan bencana alam. Penelitian ini bertujuan untuk memberikan wawasan tentang AI pada manajemen risiko rantai pasok, mendukung pengambilan keputusan yang lebih baik dalam hal investasi AI, pengembangan strategi implementasi, dan pemilihan solusi AI yang tepat. Penelitian menggunakan metode Systematic Literature Review (SLR) untuk mengumpulkan, mengevaluasi, dan mensintesis data ilmiah yang relevan dengan topik pembahasan yang dipublikasikan pada tahun 2019 hingga 2024. Strategi pengumpulan data penelitian tersebut menghasilkan 71 penelitian dimana 26 penelitian utama menjadi dasar penelitian ini. Hasil penelitian menunjukkan bahwa AI sangat bermanfaat dalam mengurangi dampak atau risiko yang terjadi pada manajemen rantai pasok. Implikasi dari penelitian ini mencakup peningkatan efisiensi dan efektivitas dalam manajemen rantai pasok melalui penerapan teknologi AI. Model AI yang paling banyak digunakan yaitu Machine Learning (ML) dan Neural Network (NN). Penggunaan model AI yang sesuai dapat membantu perusahaan dalam mengidentifikasi, menganalisis, dan mengelola risiko yang dapat terjadi pada rantai pasok sesuai dengan bidang yang ada pada perusahaan
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