Penerapan Metode Interpolasi Polinom Lagrange untuk Prediksi Teh Kering di PTPN IV Regional 4
DOI:
https://doi.org/10.47662/farabi.v9i1.1414Kata Kunci:
Dried Tea, Lagrange Polynomial Interpolation, Land Area, Production PredictionAbstrak
This study is based on the importance of accurate dry tea production planning to support the sustainability of production activities in the plantation sector. Uncertainty in production volume often poses an obstacle to production management, necessitating a method capable of predicting production based on available historical data. The purpose of this study is to apply the Lagrange polynomial interpolation method in predicting dry tea production at PT Perkebunan Nusantara IV Regional 4 based on land area and production yield data. The Lagrange polynomial interpolation method is used to form a polynomial function that passes through a number of known data points so that it can be used to estimate production values under certain conditions. The data used in this study are land area and dry tea production data for a specific period. The results of this study indicate that the Lagrange polynomial interpolation method can be used to predict dry tea production and provide an overview of the relationship between land area and production yield. The application of this method is expected to support production planning and decision making at PT Perkebunan Nusantara IV Regional 4.
Referensi
Bossarito Putro, M. Tanzil Furqon, & Satrio Hadi Wijoyo. (2018). Prediksi Jumlah Kebutuhan Pemakaian Air Menggunakan Metode ex(Studi Kasus : PDAM Kota Malang). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(11), 4679–4686.
Br Barus, A. A., & Irsal. (2024). Pengaruh Iklim terhadap Produktivitas Tanaman Teh (Camellia sinensis L.) di Perkebunan Bah Butong Tahun 2017-2021. Jurnal Agroteknologi, 12(1), 7–13. https://doi.org/10.32734/ja.v12i1.20566
Collins, S. P., Storrow, A., Liu, D., Jenkins, C. A., Miller, K. F., Kampe, C., & Butler, J. (2021). Numerical Methods for Engineers and Scientists Using MATLAB.
Ferdiansyah, M. R., Zamzami, A., & Purwono. (2023). Evaluasi Metode Pemetikan Teh (Camellia sinensis (L.) O. Kuntze) untuk Memproduksi Teh Hijau di Perkebunan Teh Negara Kanaan, Bandung. Buletin Agrohorti, 10(3), 440–449. https://doi.org/10.29244/agrob.v10i3.46486
Ginting, N. M., Andari, G., & Nurliah, N. (2020). Analisis Faktor-Faktor yang Mempengaruhi Produksi Telur Ayam Ras. Agricola, 10(2), 94–100. https://doi.org/10.35724/ag.v10i2.3266
Hidayah, T. N., Wibowo, A., Islam, U., Raden, N., Said, M., Kelahiran, J., & Excel, M. (2025). JUMLAH KELAHIRAN DI INDONESIA MENGGUNAKAN. 8(1), 35–43.
Ignasius, M., & Lamabelawa, J. (2018). ANALISIS PERHITUNGAN METODE INTERPOLASI. 8(1).
Ilham, R., & Fryonanda, H. (2023). Perancangan Prediksi Produksi Teh Menggunakan Metode Fuzzy Tsukamoto Berbasis Web. 4(1), 16–22.
Mansyur, N. N., Arman, La Gubu, Somayasa, W., & Aswani. (2024). Penerapan Metode Interpolasi Lagrange Dalam Meramalkan Jumlah Pendapatan Pada Percetakan (Studi Kasus: Gevira Advertising). Jurnal Matematika Komputasi Dan Statistika, 4(1), 540–546. https://doi.org/10.33772/jmks.v4i1.80
Pravana, N. K., Piryani, S., Chaurasiya, S. P., Kawan, R., Thapa, R. K., Shrestha, S., Brouwer, I. D., Jager, I. de, Borgonjen, K., Azupogo, F., Rooij, M., Folson, G., Abizari, R., Frempong, R. B., Annim, S. K., Boah, M., Azupogo, F., Amporfro, D. A., Abada, L. A., … WHO. (2017). Pengaruh Pemupukan Nitrogen Terhadap Tinggi dan Percabangan Tanaman Teh (Camelia Sinensis (L.) O. Kuntze) untuk Pembentukan Bidang Petik. Development Studies Research, 3(1), 43. http://doi.org/10.1080/16070658.2018.1448503%0Awww.udsspace.uds.edu.gh%0Ahttps://doi.org/10.1080/20469047.2017.1409453%0Ahttp://dx.doi.org/10.1016/j.heliyon.2017.e00298%0Ahttp://www.gainhealth.org/wpcontent/uploads/2018/03/Ghana-Development-of-Food-based
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Ika Dewini Samosir, Syamsyida Rozi
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
