Data Mining untuk Memprediksi Jumlah Penjualan Hasil Pertanian Mengunakan Algoritma Forcasting (Studi Kasus: Dinas Pertanian Kabupaten Banggai)

by Dewi Puspa Lamondjong, Mardi Hardjianto

Abstrak – Data mining technology is very useful in helping predict the number of sales in finding very important information from their data. Data mining explored databases to find hidden patterns, forecast the number of sales which is very useful to support decision making, search for information in predicting what the regional government of Banggai Regency may not see or forget, because it is beyond their expectations. Automated analysis carried out by data mining answers questions on the number of food crops sales, wnamely rice, maize, soybeans and cassava which are sold well and if done in the traditional way requires a lot of time to answer them. The result of this model is to find information from the data on yields and the number of these food plants sales, then it can predict the amount of these crops sales that are sold and the local government can predict the yields of more serious food crops to improve their quality. In this study, to predict the amount of agricultural sales using a calculation method, namely linear regression, then the number output can determine how much the these food crops sales are sold, and will be used as evaluation material for local governments for each total sales of crop yields. It is expected that the model made in predicting the number of sales for each crop yield is in accordance with existing data.

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