Penerapan Algoritme Linear Regression untuk Prediksi Hasil Panen Tanaman Padi

  • Heru Wahyu Herwanto Universitas Negeri Malang
  • Triyanna Widiyaningtyas Universitas Negeri Malang
  • Poppy Indriana Universitas Negeri Malang
Keywords: Algoritme Linear Regression, Tanaman Padi, Prediksi, Hasil Panen

Abstract

Rice yields are very influential in meeting the basic food needs of rice. Because the needs of rice are always rising, it is necessary to predict crop yields to estimate the future planting to meet the basic food needs. The method used in this paper is linear regression algorithm, which can predict the yield of rice plants. The steps in this research are as follows: (1) data collection through surveys to farmers in Lamongan by giving questionnaires to respondents; (2) pre-processing the data, which is data cleaning; (3) applying linear regression to determine the strength of the relationship between one dependent or dependent variable and a set of independent or independent variables; and (4) results of the validation. Testing accuracy is carried out by measuring Root Mean Squared Error (RMSE). The average value of accuracy of the RMSE is 0. 432. This indicates that the variation of values produced by a forecast model is close to accurate, and results in the compatibility of the Multiple Linear Regression Model, with a reliability level of 94.51%.

References

M. Muslihudin dan T.F. Abdillah, “Sistem Pendukung Keputusan untuk Menentukan Kualitas Bibit Padi (Kasus Petani Podosari),”Jurnal TAM (Technology Accept. Model), Vol. 2, hal.26-32, Jul. 2014.

E.E. Pratiwi, A.W. Widodo, dan W.F. Mahmudy, “Penerapan Algoritme Genetika pada Kasus Optimasi Penentuan Bibit dan Pemerataan Subsidi pupuk (Studi Kasus: Desa Pandansari, Kabupaten Kediri),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., Vol. 2, No. 5, hal. 1803–1812, Sep. 2017.

C.V. Donggulo, I.M. Lapanjang, dan U. Made, “Pertumbuhan dan Hasil Tanaman Padi (Oryza sativa L) pada Berbagai Pola Jajar Legowo dan Jarak Tanam,” J. Agrol., Vol. 24, hal. 27–35, April 2017.

G. Ramadhona, B.D. Setiawan, dan F.A. Bachtiar, “Prediksi Produktivitas Padi Menggunakan Jaringan Syaraf Tiruan Backpropagation,” J. Pengemb. Teknol. Inf. dan Ilmu Komputer, Vol. 2, No. 12, hal. 6048–6057, 2018.

W.N. Tenggara, “Kajian Pengembangan Varietas Unggul Baru Padi Sawah dengan Pendekatan Pengelolaan Tanaman Terpadu di Dompu Nusa Tenggara Barat," Penelit. Pertan. Tanam. Pangan, Vol. 2, No. 2, hal. 95–99, 2018.

Z.A. Matondang, “Sistem Pendukung Keputusan Forecasting Harga Emas Lelang pada Pegadaian dengan Metode Single Moving Average,” J. Tek. Inform. Unika St. Thomas, Vol. 3, No. 1, hal. 72–77, Jun. 2018.

I.M. Kamal, T. Hendro P., dan R. Ilyas, “Prediksi Penjualan Buku Menggunakan Data Mining di PT. Niaga Swadaya,” Semin. Nas. Teknol. Inf. dan Multimedia, 2017, hal. 49–54.

F. Anis dan Suprayogi, “Estimasi Luas Panen Padi di Kabupaten Rembang Menggunakan Algoritma Linear Regression,” Skripsi, Universitas Dian Nuswantoro, Semarang, Indonesia, 2015.

B. Irwan. dan N.A. Artesya, “Aplikasi Data Mining Menggunakan Multiple Linear Regression untuk Pengenalan Pola Curah Hujan,” Jurnal Ilmiah KLIK, Vol. 2, No. 1, hal. 34–44, 2015.

M.F. Saputri dan S. Slamet, “Analisa Data Penjualan Menggunakan Metode Regresi Linier untuk Prediksi Persediaan Barang pada TB.Kawankita,” Skripsi, Universitas Dian Nuswantoro, Semarang, Indonesia, 2016.

A. Fikri, “Penerapan Data Mining untuk Mengetahui Tingkat Kekuatan Beton yang Dihasilkan dengan Metode Estimasi Menggunakan Linear Regression,” Skripsi, Universitas Dian Nuswantoro, Semarang, Indonesia, 2009.

T. Chai dan R.R. Draxler, “Root Mean Square Error (RMSE) or Mean Absolute Error (MAE)? -Arguments Against Avoiding RMSE in the Literature,” Geosci. Model Dev., Vol. 7, No. 3, hal. 1247–1250, 2014.

P. Choirunisa dan Kariyam, “Perbandingan Metode Triple Exponential Smoothing dan Metode Seasonal ARIMA untuk Peramalan Inflasi di Kota Tamjung Pandan," Prosiding Sendika, Vol. 5, No. 2, hal. 76–83, 2019.

Published
2019-11-20
How to Cite
Heru Wahyu Herwanto, Triyanna Widiyaningtyas, & Poppy Indriana. (2019). Penerapan Algoritme Linear Regression untuk Prediksi Hasil Panen Tanaman Padi. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 8(4), 364-370. Retrieved from https://dev.journal.ugm.ac.id/v3/JNTETI/article/view/2563
Section
Articles