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Analisis Pengaruh Luas Area Pertanian Terhadap Prediksi Hasil Pertanian di Kebumen Menggunakan Metode Regresi Linier

Ikhsanuddin, Rohmatulloh MuhamadRusvinasari, Dian
Jurnal Informatika: Jurnal Pengembangan IT (Sinta 3)Vol. 0 No. 030 April 2025
DOI10.30591/jpit.v10i2.8471

Abstrak

Kebumen as an agricultural area whose people mostly play a role in agriculture has an important role in the southern part of Java. The size of the agricultural area will affect agricultural results, especially rice yields. Large agricultural areas will be beneficial for the community in their role as well as food self-sufficiency programs so that dependence on foreign agricultural production is reduced. However, agricultural conditions have not been managed maximally. It is hoped that agricultural yield predictions can help the government in making decisions on the management of agricultural areas in Kebumen. The linear regression method is one of the methods in data mining for data forecasting that relies on historical data so it requires agricultural yield data for the period from 2013 to 2019. The prediction process uses data on the area of the harvest which will influence the harvest in tons. Previous research shows that the linear regression method produces very small error values so it is very suitable for use in prediction cases. The aim of this research is to determine the predicted influence of harvested land area on the amount of harvest in Kebumen as analysis material. The stages in the linear regression method are determining the intercept and coefficient values with the a value of -317.231 and the b value of 6.0123, determining the regression equation to determine predictions, calculating the difference in predicted data, calculating the error value using MAPE with a result of 5,60%.

Kata Kunci

Sains DataPredictionLinear RegressionAgriculture, Land Area.

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Analisis Pengaruh Luas Area Pertanian Terhadap Prediksi Hasil Pertanian di Kebumen Menggunakan Metode Regresi Linier | Jurnal Informatika: Jurnal Pengembangan IT | Publiora