Goldestan, Gandes (2018) Pengembangan Perangkat Lunak untuk Prediksi Tingkat Produksi Padi Menggunakan Gaussian Copula Marginal Regression - Software Development To Predict The Level Of Paddy Production Using Gaussian Copula Marginal Regression. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pengambilan keputusan yang tepat dalam manajemen produksi padi sangat dibutuhkan untuk mendukung upaya ketahanan pangan nasional, terutama di Jawa Timur yang merupakan provinsi penghasil padi terbesar di Indonesia. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan berbasis web untuk memprediksi tingkat produksi padi di lima kabupaten sentra penghasil padi di Jawa Timur, yaitu Lamongan, Ngawi, Banyuwangi, Bojonegoro, dan Jember. Sistem pendukung keputusan berbasis web dibuat agar informasi mudah diakses dan dipahami. Metode yang digunakan dalam penelitian ini adalah Gaussian Copula Marginal Regression (GCMR), yaitu regresi berdasarkan Copula. Variabel prediktor (curah hujan) dan variabel respon (luas panen) diidentifikasi hubungannya dengan korelasi Copula, kemudian dilanjutkan dengan menyusun model luas panen menggunakan model GCMR. Hasil penelitian menunjukkan bahwa model GCMR mampu memodelkan luas panen padi di lima kabupaten sentra penghasil padi di Jawa Timur. Selanjutnya, sistem juga mampu memprediksi tingkat produksi padi dalam jangka pendek sebagai pendukung keputusan untuk membantu pihak berwenang memberikan pertimbangan dalam mengambil kebijakan terkait dengan hal pertanian dan ketahanan pangan di Jawa Timur.
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Appropriate decision making in rice production management is needed to support national food security efforts, especially in East Java which is the largest rice production province in Indonesia. This study aims to develop a web-based decision support system to predict rice production levels in five districts of rice production centers in East Java, covering districts : Lamongan, Ngawi, Banyuwangi, Bojonegoro, and Jember. A web-based decision support system is constructed to make information accessible and understandable. The method used in this study is Gaussian Copula Marginal Regression (GCMR), which is regression based on Copula. Predictor variables (rainfall) and response variables (harvested area) are identified their correlation using Copula correlation. Estimation of harvested area is constructed using GCMR model. The results showed that the GCMR model used was able to model the area of rice harvest in five districts of rice production centers in East Java. Furthermore, the system is also able to predict the level of rice production in the short term as decision support to help the authorities give consideration in taking policy related to agriculture and food security in East Java.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSMa 519.535 Gol p 3100018076410 |
| Uncontrolled Keywords: | Curah Hujan, Luas Panen, Gaussian Copula Marginal Regression, Sistem Pendukung Keputusan, Sistem Prediksi, Tingkat Produksi Padi |
| Subjects: | Q Science > QA Mathematics > QA76.76.A65 Application software. Enterprise application integration (Computer systems) |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Goldestan Gandes |
| Date Deposited: | 15 Jan 2019 07:21 |
| Last Modified: | 04 Feb 2021 07:18 |
| URI: | http://repository.its.ac.id/id/eprint/58545 |
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