Evaluasi Perencanaan Produksi Kubis Di Sumatera Utara Dengan Metode Rantai Markov Waktu Diskrit
DOI:
https://doi.org/10.59581/konstanta.v2i3.3736Keywords:
Markov Chain, Discrete Time, Production Planning, Cabbage, North SumatraAbstract
This research aims to evaluate cabbage production planning in North Sumatra using the discrete-time Markov chain method. Cabbage is one of the horticultural agricultural products that plays an important role in North Sumatra's exports. Proper evaluation of production plans is necessary to ensure sustainability and increase productivity and export volume. The Discrete Time Markov Chain method is used to predict changes in cabbage production conditions over time by considering the factors that influence them. Data on cabbage production and harvested area in North Sumatra from 2020 to 2022 were analyzed using one-step and n-step transition opportunity matrices. The results of the analysis show that in 2023, cabbage production and harvested land area are predicted to experience a significant increase compared to the previous year. This research provides a more accurate and efficient planning strategy for cabbage production, which can ultimately improve agricultural management in North Sumatra.
References
Asyrofi, A., Anggriani, I. and Soemarsono, A. R. (2023) ‘Implementation of Discrete Time Markov Chain Method to Estimate The Transition of Smartphone Brands Usage in Balikpapan’, Jurnal ILMU DASAR, 24(2), p. 159. doi: 10.19184/jid.v24i2.34872.
Fransiska, W., Nufus, R. H., Syafi’i, M., & Hasibuan, L. H. (2022). Penerapan Rantai Markov Dalam Peramalan Cuaca (Studi Kasus: Cuaca Harian di Kota Padang). Buana Matematika: Jurnal Ilmiah Matematika dan Pendidikan Matematika, 12(2), 117-126.
Gifari, F. A., Maulana, M. A. and Maulana, S. (2022) ‘Analisis Rantai Markov Untuk Mengetahui Peluang Perpindahan Konsumen Merek Laptop Pada Mahasiswa Teknik Industri Universitas Indraprasta PGRI’, Bulletin of Applied Industrial Engineering Theory, 3(1), pp. 45–62. Available at: https://repository.uin-suska.ac.id/7575/1/2012_2012127MT.pdf.
Hasibuan, S. N., Siregar, A., & Rafiki, A. (2023). Analisis Faktor-Faktor yang Mempengaruhi Ekspor Sayur Kubis di Provinsi Sumatera Utara. JURNAL AGRICA, 16(2).
Langi, Y. A. R. (2011) ‘Penentuan Klasifikasi State Pada Rantai Markov Dengan Menggunakan Nilai Eigen Dari Matriks Peluang Transisi’, Jurnal Ilmiah Sains, 11(1), p. 124. doi: 10.35799/jis.11.1.2011.54.
Masuku, F. N., Langi, Y. A. R. and Mongi, C. (2018) ‘Analisis Rantai Markov Untuk Memprediksi Perpindahan Konsumen Maskapai Penerbangan Rute Manado-Jakarta Analysis of Markov Chain To Predict Consumer Movement of Airline Route Manado-Jakarta’, Ilmiah Sains, 18(2), pp. 1–5.
Nurman, T. A., & Syata, I. (2021). Prediksi Hasil Panen Kopi di Sulawesi Menggunakan Analisis Rantai Markov. Jurnal MSA (Matematika dan Statistika serta Aplikasinya), 9(2), 120-127.
Sasake, Set, Yopi Andry Lesnussa, dan Abraham Zakaria Wattimena. (2021). Peramalan Cuaca Menggunakan Metode Rantai Markov. Jurnal Matematika. Vol. 11 No. 1, Hal: 01-09.
Syauqi, I. and Murni, D. (2022) ‘Analisis Perencanaan Produksi Padi Terhadap Lahan Panen Di Sumatera Barat Menggunakan Rantai Markov Waktu Diskrit’, 7(2), pp. 1–7.
Zamrodah, Y. (2020). Analisis kelayakan usaha tani kubis (Brassica Oleracea L.) di desa Beji Kecamatan Junrejo kota Batu. AGROMIX, 11(2), 241– 249.
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