Estimating the Distribution of Paddy Growth Stage in Karawang, West Java Based on Gradient Boosting Algorithm

Nurul Izza Afkharinah, Elisabeth Gunawan, Nadira Fawziyya Masnur, A. Agustan, S. Yulianto, K. Mutijarsa, Abdul Karim
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Abstract

Paddy is an important and strategic commodity to supply food needs in Indonesia. Karawang Regency in West Java Province is well known as rice producer due to its natural resources and farming system. This study aims to estimate the distribution of paddy growth stage in Karawang Regency based on the classification results using the Gradient Boosting algorithm. The classification was carried out to conduct training on monthly data so as to produce predictions of the distribution of paddy growth stage area. There are 8 classifications defined, including water bodies, early vegetative, late vegetative, generative, harvesting & land preparation, not paddy fields, others, also settlements and roads. As validation material, Area Frame Sampling (Kerangka Sampling Area or KSA) data of Karawang Regency 2020 was used and comparisons were made using the Rainy Season Paddy Cropping Calendar for the October 2020-March 2021 period of Karawang Regency as an evaluation of the results. The results of the accuracy test for estimation of the distribution of paddy growth stage using the Gradient Boosting algorithm show that this algorithm has a good level of suitability and confidence level between rows and columns in the process of estimating the paddy growth stage in Karawang Regency as evidenced by the overall accuracy dominant value is >75% and the kappa statistics dominant value is > 0.7.
基于梯度提升算法估算西爪哇卡拉旺水稻生育期分布
稻谷是满足印尼粮食需求的重要战略商品。西爪哇省的卡拉旺县因其自然资源和农业系统而闻名于世。本研究旨在利用梯度提升算法,基于分类结果估计卡拉旺县水稻生育期的分布。进行分类是为了对月度数据进行训练,从而对水稻生育期面积分布进行预测。它定义了8个分类,包括水体、早期营养、晚期营养、生殖、收获和土地准备、非水田、其他、居民点和道路。采用卡拉旺县2020年区域框架采样(Kerangka Sampling Area, KSA)数据作为验证材料,并与卡拉旺县2020年10月至2021年3月的雨季水稻种植日历进行比较,对结果进行评价。利用梯度增强算法估计水稻生育期分布的精度检验结果表明,该算法在估计卡拉旺县水稻生育期的过程中具有良好的适宜性和行与列之间的置信水平,总体精度优势值>75%,kappa统计优势值> 0.7。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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