PENERAPAN DATA MINING UNTUK PREDIKSI NILAI TUKAR PETANI TANAMAN PANGAN DI INDONESIA DENGAN METODE LINEAR REGRESSION DAN SUPPORT VECTOR MACHINE

Authors

  • Akhmad Budi Teknik Informatika Institut Bisnis dan Informatika Kwik Kian Gie

Abstract

Development of technology and information systems use data mining as a method of data processing is growing, due to the large amount of data available and growing every day, especially agricultural data. One of the benefits that can be obtained by applying information technology, among others, is to conduct the analysis and prediction of large amounts of data. The exchange value of food crop farmers (NTPP) is a factor of economic welfare measurement in Indonesia, but quite difficult to predict because there has not been a proper measurement prediction method for predicting the data (NTPP) in the future. This research will be carried out to measure the accuracy of data prediction results using the Linear Regression and Support Vector Machine, with the aim of obtaining the results of the level of accuracy offered by the two methods.

Key Words: Prediction, Farmers Exchange Rate, Food Crop Farmers Exchange Rate, Data Mining, Linear Regression, Support Vector Machine, Rapidminer.

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Published

2019-03-29