CD Skripsi

Prediksi Produksi Perkebunan Karet Pada Kabupaten Dan Kota Di Provinsi Riau Menggunakan Algoritma Support Vector Regression

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Rubber plantations play a vital role in the economy of Riau Province; however, rubber production is often influenced by various factors such as climate, government policies, and market conditions. This study aims to develop a rubber production prediction system for the regencies and cities in Riau Province using the Support Vector Regression (SVR) algorithm. The data used in this research is secondary data obtained from the Riau Central Statistics Agency, totaling 120 records from 2014 to 2024. SVR was chosen due to its ability to handle non-linear data and minimize the risk of overfitting. In this study, historical rubber production data, climate factors, and other relevant variables were collected and analyzed. The SVR model was evaluated based on Mean Squared Error (MSE) and Root Mean Square Error (RMSE) to determine prediction accuracy. The results show that the model provides accurate predictions of rubber production, with the lowest MSE reaching 0.0692 and RMSE of 0.2632. These findings suggest that the proposed model can contribute positively to the management of rubber plantations in Riau Province and serve as a reference for stakeholders in making better decisions related to rubber production. Furthermore, this research opens opportunities for applying data mining techniques to other agricultural sectors.
Keywords: MSE, Riau Province, Rubber Production Prediction, Support Vector Regression, RMSE.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2003126285

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2003126285

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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