RANCANG BANGUN APLIKASI PREDIKSI HASIL PANEN BUDIDAYA JAMUR TIRAM MENGGUNAKAN METODE REGRESI LINEAR BERGANDA BERBASIS WEB
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
PRATIKNO, MUKHLIS TRI
ABDURRASYID, ABDURRASYID
JATNIKA, HENDRA
ABDURRASYID, ABDURRASYID
JATNIKA, HENDRA
Subject
Teknik Informatika
Datestamp
2023-06-20 04:42:16
Abstract :
Oyster mushroom is a food mushroom from the Basidomycota group and belongs to the Homobasidiomycetes class with the characteristics of a white to cream fruit body and a semicircular hood similar to an oyster shell with a slightly concave center. According to the data obtained, mushroom production changes every month, a prediction It is very necessary to know the future picture of whether crop yields will increase or decrease. So we need a system that is able to predict mushroom yields so that farmers can find out what their estimated yields will be in the future which of course can help farmers build and develop mushroom farming in Redisari Village Rowokele District. One of the methods used to predict the relationship between variables is Multiple Linear Regression. The RMSE calculation results obtained with the mushroom data used are 0.391. Prediction of oyster mushroom yields in Redisari Village that mushroom supply affects crop yields in that period with the predicted value obtained Y -299.67764958326 + 7.9921935682804 x1+ 1.5201863776265 x2. Then input the value of the variable X obtained from the calculation for the prediction for the next month to get Y 8332,168 Kg. Prediction of the yield of oyster mushroom cultivation using the Multiple Linear Regression method using data on mushroom production, dead mushrooms and yields in the previous month which is then processed to get the final result. in the form of predictions of crop yields for the following month. Based on the results of the RMSE, it can be concluded that if it is in accordance with the nature of the RMSE, if the value obtained is close to 0 then the results obtained are accurate.
Oyster mushroom is a food mushroom from the Basidomycota group and belongs to the Homobasidiomycetes class with the characteristics of a white to cream fruit body and a semicircular hood similar to an oyster shell with a slightly concave center. According to the data obtained, mushroom production changes every month, a prediction It is very necessary to know the future picture of whether crop yields will increase or decrease. So we need a system that is able to predict mushroom yields so that farmers can find out what their estimated yields will be in the future which of course can help farmers build and develop mushroom farming in Redisari Village Rowokele District. One of the methods used to predict the relationship between variables is Multiple Linear Regression. The RMSE calculation results obtained with the mushroom data used are 0.391. Prediction of oyster mushroom yields in Redisari Village that mushroom supply affects crop yields in that period with the predicted value obtained Y -299.67764958326 + 7.9921935682804 x1+ 1.5201863776265 x2. Then input the value of the variable X obtained from the calculation for the prediction for the next month to get Y 8332,168 Kg. Prediction of the yield of oyster mushroom cultivation using the Multiple Linear Regression method using data on mushroom production, dead mushrooms and yields in the previous month which is then processed to get the final result. in the form of predictions of crop yields for the following month. Based on the results of the RMSE, it can be concluded that if it is in accordance with the nature of the RMSE, if the value obtained is close to 0 then the results obtained are accurate.
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