PERBANDINGAN HASIL PANEN PADI DIPENGARUHI RATA-RATA CURAH HUJAN ATAU IRIGASI DENGAN MODEL REGRESI NONLINIER KUBIK DIKABUPATEN SUKOHARJO

Dhian Dwi Hermawan, Bebas Widada, Retno Tri Vulandari

Abstract


The rice yields in Sukoharjo Regency each year experience unstable ups and downs. The absence of predicted rice yield prediction resulted in lack of information needed to increase rice production in Sukoharjo Regency. The purpose of this research is to apply Cubic Nonlinear Method to predict rice yield in Sukoharjo Regency by comparing irrigation model with rainfall average model to see the accuracy in predicting the rice harvest in Sukoharjo regency. The design method uses UML (Unified Model Language), a program created using vb net programming language and using SQL server database, functionality testing using Black Box Test and validity testing using MSE and MAPE. The computed data is data of 2016. The results show prediction in 2017 with irrigation model has more accurate calculation result. The calculation of MSE and MAPE values manually and applying is the same ie75401808,23 and 3.01862E-14. The Cubic Nonlinear Method with irrigation model can be the initial solution to predict the rice harvest in Sukoharjo District and the output of the program is the prediction of rice harvest from the Cubic Nonlinietic Method method.

Keywords: Prediction, Nonlinear Regression, Cubic, Rice Harvest


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References


E. Purwantini and R. Susetyoko, “Pemodelan Temperatur Ruang Menggunakan Regresi Non Linier Berdasarkan Hasil Estimasi FEM 3-D Linier,” 2016.

A. Suparyanto, T. Wiradarya, and dan H. H Martojo, “Analisis Pertumbuhan Non-Linier Domba Lokal Sumatera Dan Persilangannya,” J. Ilmu Ternak dan Vet., vol. 6, no. 4, pp. 259–265, 2001.

W. Suparta and K. M. Alhasa, “Modeling of Tropospheric Delays Using ANFIS,” no. 2009, pp. 5–19, 2016.

A. F. Nurudin, “Aplikasi Prediksi Hasil Panen Padi Dengan Metode Least Square,” Kediri, 2015.

H. R. T. Bhuana, “Model Prediksi Produksi Panen Komoditas Padi Menggunakan Metode Regresi Linier Berganda,” Salatiga, 2012.

Muldianto, “Penerapan Algoritma Regresi Linier Berganda untuk Prediksi Kebutuhan Air PDAM Kabupaten Sukoharjo,” Surakarta, 2017.

R. T. Vulandari, “Pengaruh Beban Kerja Individu, Beban Kerja Organisasi, dan Kepemimpinan terhadap Kinerja Karyawan,” J. Math. Educ. Sci. Technol., vol. 1, no. 2, pp. 106–121, 2016.

H. Budiadi, “Analisa Dampak Kepemimpinan Karismatik Terhadap Kinerja Karyawan di Pemerintah Daerah Kabupaten Sukoharjo,” J. Ilm. SINUS, pp. 67–79.

Anisa Romandoni, “Penerapan Metode Regresi Linier Berganda Untuk Prediksi Hasil Panen Jagung,” Surakarta.

S. H. F. Widi Setyoko, Muhammad Hasbi and M. Di, “Sistem Pendukung Keputusan Prediksi Kualitas Kredit Calon Debitur menggunakan MJetode KNN,” J. TIKomSiN, vol. Vol 4, No, pp. 61–68, 2016.

R. T. Vulandari, Data Mining: Teori dan Aplikasi Rapidminer. Yogyakarta: CV. Gava Media, 2017.




DOI: http://dx.doi.org/10.30646/tikomsin.v6i1.342

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