The International Halal Science and Technology Conference 2024 (IHSATEC): 17th Halal Science Industry and Business (HASIB)
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Conference Name (dcterms:title)
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The International Halal Science and Technology Conference 2024 (IHSATEC): 17th Halal Science Industry and Business (HASIB)
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Conference Acronym (dcterms:alternative)
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IHSATEC 2024: 17TH HASIB
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Conference Date (dcterms:dateSubmitted)
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December 19-20, 2024
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Proceedings Title (foaf:title)
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Application of Artificial Intelligence in Food and Agriculture: a bibliometric analysis
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presented at (bibo:presentedAt)
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The International Halal Science and Technology Conference 2024 (IHSATEC): 17th Halal Science Industry and Business (HASIB)
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Poster Author(S) (bibo:authorList)
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- Nor Nadiha Mohd Zaki | Universiti Putra Malaysia | Malaysia
- Fatin Fitriah Nordin | Universiti Putra Malaysia | Malaysia
- Amalia Mohd Hashim | Universiti Putra Malaysia | Malaysia
- Yazid Yaakob | Universiti Putra Malaysia | Malaysia
- Awis Qurni Sazili | Universiti Putra Malaysia | Malaysia
- Muhammad Ashraf Fauzi | Universiti Malaysia Pahang | Malaysia
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Conference Title (bibo:shortTitle)
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IHSATEC 2024: 17TH HASIB
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Abstract (dcterms:abstract)
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Background – This paper investigates Artificial Intelligence (AI)’s contributions to the food and agriculture sectors based on the rising urge for sustainable and efficient farming practices.
Purpose – This study attempts to review the literature on AI applications in agriculture and food security based on a bibliometric approach.
Design/methodology/approach – The analysis of bibliometrics involved 369 documents obtained from the Scopus database that highlight the importance of AI in agricultural sectors including resource management and yield optimization. The bibliographic coupling and co-word analysis were performed to visualize topics and authors' interrelations and performance.
Findings – The results show that the contribution of AI to the agriculture and food sectors improves crop productivity and overall food quality. Technology applications such as machine learning, deep learning, and IoT-based systems in these sectors facilitate the optimization of prediction and decision-making processes.
Research limitations – However, there are limitations to this study including data limitations, relatively more costly than traditional cost, and challenges in the adoption of AI in small-scale farmers.
Originality/value – This paper attempts to investigate the application of AI in both food and agricultural sectors, hoping to contribute to a novel understanding of the merger of digitalization into agriculture and foods. The future of agriculture and the food industry heavily depends on the integration of AI tools with traditional farming methods with fewer costs and user-friendly applications.
Keywords: AI, artificial intelligent, agriculture sectors, food sectors
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Publisher Name (dcterms:publisher)
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Yayasan Sinergi Riset dan Edukasi
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Publicantion Date Print (dcterms:date)
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Publication Date Online (dcterms:dateAccepted)
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19-12-2024
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Enter "YES" or "NO" (bibo:isbn)
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NO
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Issue Number (bibo:issue)
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1
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Volume Number (bibo:volume)
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Galley Number (bibo:number)
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