Klasifikasi Data Mining Untuk Menentukan Hasil Produksi Tanaman Jagung Menggunakan Metode Naive Bayes

Saputra, Aldian (2022) Klasifikasi Data Mining Untuk Menentukan Hasil Produksi Tanaman Jagung Menggunakan Metode Naive Bayes. Other thesis, Universitas Islam Riau.

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Abstract

Corn is one of the plants that is currently widely used for everyday life such as the manufacture of cornstarch, animal feed and others. Quality corn will be obtained by proper planting. Proper planting requires the right method and fertilization as well. Such as research by students of the Faculty of Agriculture, Islamic University of Riau (FAPERTA UIR) in a corn planting study that examined the effect of NPK fertilizer and liquid organic fertilizer (POC) on corn growth and production so that a good amount of fertilizer was found for corn plants. but in research conducted by students of the Faculty of Agriculture, there is no system that can classify whether the fertilizer used is in accordance with the expected yields. Based on this fact, this study aims to design a system that can classify whether the fertilizer used will be in accordance with the expected production results. The programming language used in this research is PHP. To test the data, calculations were carried out using the K-fold cross-validation method with an average accuracy rate of 77.35%, while blackbox testing was carried out for system functions. Testing the application to the user that the percentage obtained is 75%, so that this application is expected to become a system that is used by researchers to help classify the results of corn crop production.

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