PENERAPAN METODE LEARNING VECTOR QUANTIZATION (LVQ) UNTUK MENENTUKAN IRIGASI LAHAN PERTANIAN DI DESA PENGGARUTAN

  • M. Fadli Maslahul Ifan Universitas Peradaban
Keywords: agricultural land irrigation, Learning Vector Quantization (LVQ), QuantumGIS, Python.

Abstract

The development of technology today is increasingly developing, including in the agricultural sector, in Penggarutan Village, Bumiayu District, an area in the Brebes Regency, where most of the population works as farmers in the fields. The area in Penggarutan village is ± 239.70 ha, residential area is ± 47.950 ha, rice field area is ± 141.623 ha. (Source: Penggarutan Village Head Office). In Penggarutan Village, the irrigation pattern carried out by farmers usually harvests 3 times per year. Water is indispensable in the process of cultivating paddy fields because if the water is not enough there will be crop failure, by the Sabab, in this paper, we are looking for a suitable irrigation route pattern to irrigate the rice fields in Penggarutan village by applying the Learning Vector Quantization algorithm ( LVQ) as an algorithm for classifying its irrigation paths. The data used as samples of this study were 62 samples of rice fields and attributes consisting of land area, distance of irrigation paths, quality of rice obtained and crop yields during the last year. The programming language used in this

paper is to use the Python language. The accuracy of this research results in an accuracy of 76%.

Keywords: agricultural land irrigation, Learning Vector Quantization (LVQ), QuantumGIS, Python.

 

Published
2021-08-18