Penerapan Pengelompokkan Produktivitas Hasil Pertanian Menggunakan Algoritma K-Means

Abstract

Since ancient times, Indonesia has always been rich in agricultural products such as rice, soybeans, corn, peanuts, cassava, and sweet potatoes. In addition, there are also products from agriculture that are referred to as trade crop agricultural products, namely tea, coffee, coconut, quinine, cloves, sugar cane, rubber, and others. The agricultural sector in 2021 will grow by 1.84% and contribute 13.28% to the national economy. Then in 2022, the agricultural sector will show consistency with a positive growth of 1.37% and contribute 12.98% to the national economy. Then it is necessary to group the productivity of agricultural products using the k-means clustering method to group data on the highest and lowest yield types according to the District in Bojonegoro so that the types of agricultural products that are most productive and less productive can be identified. The method used in this study is K-Means cluster analysis by first determining the number of groups to be formed. In this study, the data used is secondary data on agricultural products originating from One Bojonegoro Data. The food crops in question are rice, shallots, soybeans, large chilies, corn, and so on. From the results of grouping agricultural products based on the year of production, the best types of crops will be known, and which districts will produce the most productive food crops so that the distribution of food crops in Bojonegoro District can be controlled. Productivity grouping of agricultural products can be used as a strategy to increase agricultural yields