The Performance Machine Learning Powel-Beale for Predicting Rubber Plant Production in Sumatera
Abstract
This study aims to predict rubber plants in Sumatra; rubber plants have a relatively high economic value; rubber sap must be cultivated because it is a product of the rubber plant, which is the raw material for the rubber industry, so in large quantities. Therefore, rubber sap, the selling value will increase so that it can increase farmers' income. Rubber production in Sumatra experiences ups and downs; therefore, this study aims to predict rubber plants using the Powell-Beale algorithm method, one of the Artificial Neural Network methods often used for data prediction, implemented using Matlab software. That supports it. This study does not discuss the prediction results. Still, it discusses the ability of the Powell-Beale algorithm to make predictions based on datasets of rubber plant production in recent years obtained from the Central Statistics Agency. Based on this data, a network architecture model will be formed and determined, including 6-10-1, 6-15-1, 6-30-1, 6-45-1 and 6-50-1. The best architecture is 6-15-1, with the lowest Performance/MSE test score of 0.00791984.
References
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[2] Andrian, Supriadi, and P. Marpaung, “Pengaruh Ketinggian Tempat dan Kemiringan Lereng terhadap Produksi Karet (Hevea brasiliensis Muell. Arg.) di Kebun Hapesong PTPN III Tapanuli Selatan,” E-Journal Agroekoteknologi, vol. 2, no. 3, pp. 981–989, 2014.
[3] H. Sulistiani, I. Darwanto, and I. Ahmad, “Penerapan Metode Case Based Reasoning dan,” Jurnal Edukasi dan Penelitian Informatika, vol. 6, no. 1, pp. 23–28, 2020.
[4] I. R. Fauzi, “Alternatif Strategi Pengembangan Industri Barang Jadi Karet Di Indonesia,” Warta Perkaretan, vol. 32, no. 2, p. 55, 2013, doi: 10.22302/ppk.wp.v32i2.37.
[5] E. Maria and E. Junirianto, “Sistem Pendukung Keputusan Pemilihan Bibit Karet Menggunakan Metode TOPSIS,” Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer, vol. 16, no. 1, p. 7, 2021, doi: 10.30872/jim.v16i1.5132.
[6] R. Ardika, A. N. Cahyo, and T. Wijaya, “Dinamika Gugur Daun Dan Produksi Berbagai Klon Karet Kaitannya Dengan Kandungan Air Tanah,” Jurnal Penelitian Karet, vol. 29, no. 2, pp. 102–109, 2016, doi: 10.22302/ppk.jpk.v29i2.242.
[7] K. Langkat, J. V. No, and S. Utara, “1 , 2 , 3,” vol. 6, no. 1, pp. 1–10, 2022.
[8] R. Rosaly and A. Prasetyo, “Pengertian Flowchart Beserta Fungsi dan Simbol-simbol Flowchart yang Paling Umum Digunakan,” Https://Www.Nesabamedia.Com, vol. 2, p. 2, 2019.
[9] J. Junaidi, “Transformasi Sistem Pemanenan Latex Tanaman Karet: Review,” Jurnal Budidaya Pertanian, vol. 16, no. 1, pp. 1–10, 2020, doi: 10.30598/jbdp.2020.16.1.1.
[10] I. W. B. W. dan I. G. B. Indrajaya, “Pengaruh jumlah produksi karet, harga , dan investasi terhadap volume ekspor karet indoesia 1996-2010,” Jurnal EP Unud, vol. 53, no. 9, pp. 1689–1699, 2013.
[11] R. Ramdani, E. P. Purnomo, and R. D. P. Ahsani, “Karet Alam Sebagai Basis Pembangunan Pedesaan dan Peningkatan Tarap Hidup Masyarakat yang Berkelanjutan,” Magelang: Universitas Tidar Magelang, vol. 44, no. 1, pp. 21–36, 2018.
[12] H. Prastanto, Y. Firdaus, S. Puspitasari, A. Ramadhan, and A. F. Falaah, “Sifat Fisika Aspal Modifikasi Karet Alam Pada Berbagai Jenis Dan Dosis Lateks Karet Alam,” Jurnal Penelitian Karet, no. October, pp. 65–76, 2018, doi: 10.22302/ppk.jpk.v36i1.444.
[13] D. Syahputra, “Analisis Faktor - Faktor Yang Mempengaruhi Pendapatan Petani Karet Di Kecamatan Seunagan Timur Kabupaten Nagan Raya,” Jurnal Ilmiah Mahasiswa Agroinfo Galuh, vol. 2, no. 4, pp. 85–93, 2018.
[14] G. Claudia, E. Yulianto, and M. K. Mawardi, “Pengaruh Produksi Karet Nilai Tukar Terhadap Volume Ekspor Ka ...,” Jurnal Administrasi Bisnis (JAB), vol. 35, no. 1, pp. 165–171, 2016.
[15] S. Anam, T. Adriyanto, and W. M. K, “Diagnosis Diabetes Mellitus Menggunakan Algoritma Jaringan Syaraf Tiruan Backpropagation dengan Metode Conjugate Gradient Fletcher-Reeves Adaptive Gain,” pp. 47–52, 2017, doi: 10.21063/pimimd4.2017.47-52.
[16] L. F. Syarifa, D. S. Agustina, C. Nancy, and M. Supriadi, “Dampak Rendahnya Harga Karet Terhadap Kondisi Sosial Ekonomi Petani Karet Di Sumatera Selatan,” Jurnal Penelitian Karet, vol. 34, no. 1, p. 119, 2016, doi: 10.22302/jpk.v0i0.218.
[17] S. Damanik, “Pengembangan Karet (Havea brasiliensis) Berkelanjutan di Indonesia,” Perspektif, vol. 11, no. 1, pp. 91–102, 2012.
[18] A. Wanto, A. P. Windarto, D. Hartama, and I. Parlina, “Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density,” IJISTECH (International Journal Of Information System & Technology), vol. 1, no. 1, p. 43, 2017, doi: 10.30645/ijistech.v1i1.6.
[19] R. M. Firzatullah, “Sistem Pendukung Keputusan Penentuan Uang Kuliah Tunggal Universitas XYZ Menggunakan Algoritma Backpropagation,” PETIR, vol. 14, no. 2, pp. 170–180, Sep. 2021, doi: 10.33322/petir.v14i2.996.
[20] A. Desiani, “Kajian Pengenalan Wajah Dengan Menggunakan Metode Face-Arg Dan Jaringan Syaraf Tiruan,” vol. 5, no. 2, pp. 99–111, 2007.
[21] A. F. H. MUNZIR, , ADIWIJAYA, and A. ADITSANIA, “Analisis Reduksi Dimensi Pada Klasifikasi Microarray Menggunakan Mbp Powell Beale,” E-Jurnal Matematika, vol. 7, no. 1, p. 17, 2018, doi: 10.24843/mtk.2018.v07.i01.p179.
[22] A. Wanto, “Optimasi Prediksi Dengan Algoritma Backpropagation Dan Conjugate Gradient Beale-Powell Restarts,” Jurnal Nasional Teknologi & Sistem Informasi, vol. 3, no. 3, pp. 370–380, 2018.
[23] S. Gessawati, F. Ilmu, S. Dan, and I. Politik, “14.104.120.75,” 2017.
[24] J. F. Simanjuntak, R. Winanjaya, and W. Robiansyah, “Peramalan Hasil Produksi Karet di Sumatra Utara dengan Algoritma Backpropagation Forecasting of Rubber Production in North Sumatra with Backpropagation Algorithm,” vol. 1, no. 3, 2022, doi: 10.55123/jomlai.v1i3.917.
Published
2023-03-16
How to Cite
[1]
S. Dani, S. Solikhun, and D. Priyanto, “The Performance Machine Learning Powel-Beale for Predicting Rubber Plant Production in Sumatera”, International Journal of Engineering and Computer Science Applications (IJECSA), vol. 2, no. 1, pp. 31-40, Mar. 2023.
Section
Articles
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