Implementation of Multi-Criteria in Supply Chain Optimization Analysis of the Livestock Sector on Java Island
Keywords:
Multi-Criteria Decision Making (MCDM),, Artificial Intelligence, Livestock Production
Abstract
The rapid development of technology has had a significant impact on various sectors, including the livestock industry. This study examines the application of the Multi-Criteria Decision Making (MCDM) method, especially the Analytical Hierarchy Process (AHP), to optimize the supply chain in the livestock sector in Java. The purpose of this study is to determine the most efficient livestock production area by evaluating criteria such as production quantity, average production, production cost, and percentage increase in production over a certain period. In addition, this research integrates Artificial Intelligence (AI) as a controller to improve data management and monitor the livestock production process. This study uses quantitative methods to analyze supply chain data from Central Java, West Java, and East Java. The findings show that Central Java has the highest livestock production efficiency with an index of 0.4511, contributing significantly to the island's overall production. The study concluded that integrating AI into supply chain management can significantly improve efficiency and productivity in the livestock sector.
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[5] S. R. Karimuna, S. Bananiek, S. Syafiuddin, and W. Al Jumiati, “Potensi Pengembangan Komoditas Peternakan di Sulawesi Tenggara,” J. Ilmu dan Teknol. Peternak. Trop., vol. 7, no. 2, p. 110, 2020, doi: 10.33772/jitro.v7i2.12215.
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[9] P. Ziemba, M. Piwowarski, and K. Nermend, “Software systems supporting remote education – Fuzzy assessment using a multi-criteria group decision-making method,” Appl. Soft Comput., vol. 149, no. April, 2023, doi: 10.1016/j.asoc.2023.110971.
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[12] B. M. Mohsen, “Impact of Artificial Intelligence on Supply Chain Management Performance,” J. Serv. Sci. Manag., vol. 16, no. 01, pp. 44–58, 2023, doi: 10.4236/jssm.2023.161004.
[13] L. Manning et al., “Artificial intelligence and ethics within the food sector: Developing a common language for technology adoption across the supply chain,” Trends Food Sci. Technol., vol. 125, no. April 2021, pp. 33–42, 2022, doi: 10.1016/j.tifs.2022.04.025.
[14] E. Riyandana, M. G. An Ars, and A. Surahman, “Rancang Bangun Aplikasi Game Edukasi Kosakata Baku Dalam Bahasa Indonesia Di Tingkat Sekolah Dasar (Studi Kasus Sd Negeri 1 Way Petai Lampung Barat),” J. Inform. dan Rekayasa Perangkat Lunak, vol. 3, no. 2, pp. 213–225, 2022, doi: 10.33365/jatika.v3i2.2028.
[15] A. T. Cahyono and S. Wibisono, “Sistem Pendukung Keputusan untuk Penilaian Kinerja Pegawai menggunakan Metode AHP dan COPRAS,” J. JTIK (Jurnal Teknol. Inf. dan Komunikasi), vol. 8, no. 1, pp. 58–66, 2024, doi: 10.35870/jtik.v8i1.1292.
[16] C. S. Pramudyo and D. E. H. Purnomo, “Perancangan Sistem Pendukung Keputusan untuk Pemilihan Pemasok Nata de Coco dengan Metode Simple Additive Weighting,” J. Ilm. Tek. Ind., vol. 11, no. 1, pp. 80–90, 2012.
[17] D. Apdian, M. T. B. Hutabarat, R. Jayawiguna, and Y. Suherman, “Sistem Penunjang Keputusan Beasiswa Pada Smk Ristek Karawang Berbasis Web Menggunakan Metode Smart,” J. Interkom J. Publ. Ilm. Bid. Teknol. Inf. dan Komun., vol. 18, no. 4, pp. 17–24, 2024, doi: 10.35969/interkom.v18i4.320.
[18] A. Lusiana and P. Yuliarty, “PENERAPAN METODE PERAMALAN (FORECASTING) PADA PERMINTAAN ATAP di PT X,” Ind. Inov. J. Tek. Ind., vol. 10, no. 1, pp. 11–20, 2020, doi: 10.36040/industri.v10i1.2530.
Published
2025-01-30
How to Cite
Fadiana, F. (2025). Implementation of Multi-Criteria in Supply Chain Optimization Analysis of the Livestock Sector on Java Island. Proceedings of the National Conference on Electrical Engineering, Informatics, Industrial Technology, and Creative Media, 4(1), 938-950. Retrieved from https://centive.ittelkom-pwt.ac.id/index.php/centive/article/view/307
