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Sausan Nisrina
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Decision Sciences, Operations Research & Management Mathematics

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Klasifikasi Varietas Unggul Padi Menggunakan Metode Bagging, Boosting, dan Extremely Randomized Trees Lukmanul Hakim; Asep Saefuddin; Sausan Nisrina
Statistika Vol. 22 No. 2 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i2.1455

Abstract

Rice is one of the agricultural products which is the main commodity in Indonesia. Supporting factors that play a very important role in efforts to increase rice production are superior varieties. Superior rice varieties have characteristics that are similar to one another. Thus, farmers must choose the varieties used through a classification process to determine the appropriate type of rice. At this stage, three methods are used: bagging, boosting, and extremely randomized trees. From the analysis results, the overall method of extremely randomized trees has more optimal capabilities compared to the bagging and boosting methods. This is indicated by the three parameters, sensitivity, specificity, and accuracy, which have the highest values.
Co-Authors ASEP SAEFUDDIN Lukmanul Hakim