PREDIKSI HASIL PANEN MENGGUNAKAN ALGORITMA
REGRESI LINIER BERGANDA BERBASIS WEB
(STUDI KASUS :DINAS PERTANIAN KABUPATEN SUMBAWA)
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Institusion
STMIK Bumi Gora
Author
YUSRIANI, YUNI
Subject
T Technology (General)
Datestamp
2021-08-30 08:34:39
Abstract :
Rice is a food crop commodity that produces rice which plays an important role in the economic life of Indonesia. Namely rice as a staple food is very difficult to replace by other staples. Among them are corn, tubers, sago and other carbohydrate sources. So that the existence of rice becomes the main priority of the community in meeting the needs of carbohydrate intake which can be filling and is the main source of carbohydrates that are easily converted into energy. Sumbawa Regency is one of the suppliers of food in the form of rice to various areas such as Bali, Lombok and Java Island, but each year rice production in Sumbawa Regency is always changing. To overcome these problems the authors build an application using one of the algorithms of data mining, namely the multiple linear regression algorithm. In making predictions, there are several influencing factors, namely land area, productivity and rainfall. With this multiple linear regression method, the root mean square error (RMSE) of 62.02 is obtained with training data from 2010-2016. The multiple linear regression equation obtained is Y = -21772.95152 + 5.015449757x1 + 438.1471317x2 + -0.079509826x3. So, based on the results of research and testing conducted. Prediction results generated using multiple linear regression algorithm in good category.
Rice is a food crop commodity that produces rice which plays an important role in the economic life of Indonesia. Namely rice as a staple food is very difficult to replace by other staples. Among them are corn, tubers, sago and other carbohydrate sources. So that the existence of rice becomes the main priority of the community in meeting the needs of carbohydrate intake which can be filling and is the main source of carbohydrates that are easily converted into energy. Sumbawa Regency is one of the suppliers of food in the form of rice to various areas such as Bali, Lombok and Java Island, but each year rice production in Sumbawa Regency is always changing. To overcome these problems the authors build an application using one of the algorithms of data mining, namely the multiple linear regression algorithm. In making predictions, there are several influencing factors, namely land area, productivity and rainfall. With this multiple linear regression method, the root mean square error (RMSE) of 62.02 is obtained with training data from 2010-2016. The multiple linear regression equation obtained is Y = -21772.95152 + 5.015449757x1 + 438.1471317x2 + -0.079509826x3. So, based on the results of research and testing conducted. Prediction results generated using multiple linear regression algorithm in good category.
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