📅 30 November 2020
DOI: 10.51903/e-bisnis.v13i2.247
Penerapan Algoritma Random Forest Untuk Menentukan Kualitas Anggur Merah
EBISNIS : JURNAL ILMIAH EKONOMI DAN BISNIS
Universitas Sains dan Teknologi Komputer
📄 Abstract
Abstract
In this study that was used as the object of research in classifying red wine based on the quality influenced by each red wine or red wine based on the content of each type of wine, from each attribute containing the composition in the wine seen which attributes most affect the quality of red wine, so that it will be known ingridents that can improve the quality of the wine, in this study was carried out by the application of Machine learning by comparing three algorithms of mining data that is , Decission Tree, Random Forest and Support Vector Machine (SVM), from the results of research that has been done by comparing the three algorithms, Random Forest produced the best accuracy among other algorithms that have been tested. Random Forest with accuracy results of 0.7468 makes this algorithm best used to classify the quality of red wine. And in the second order Decission Tree with accuracy results of 0.7031, while Support Vector Machine (SVM) get an accuracy result of 0.65. So in the research that has been done to classify the quality of red wine based on its composition Random Forest becomes the best algorithm to use..
In this study that was used as the object of research in classifying red wine based on the quality influenced by each red wine or red wine based on the content of each type of wine, from each attribute containing the composition in the wine seen which attributes most affect the quality of red wine, so that it will be known ingridents that can improve the quality of the wine, in this study was carried out by the application of Machine learning by comparing three algorithms of mining data that is , Decission Tree, Random Forest and Support Vector Machine (SVM), from the results of research that has been done by comparing the three algorithms, Random Forest produced the best accuracy among other algorithms that have been tested. Random Forest with accuracy results of 0.7468 makes this algorithm best used to classify the quality of red wine. And in the second order Decission Tree with accuracy results of 0.7031, while Support Vector Machine (SVM) get an accuracy result of 0.65. So in the research that has been done to classify the quality of red wine based on its composition Random Forest becomes the best algorithm to use..
🔖 Keywords
#Red wine
#Random Forest
#Python; Red wine
#Random Forest
#Python
ℹ️ Informasi Publikasi
Tanggal Publikasi
30 November 2020
Volume / Nomor / Tahun
Volume 13, Nomor 2, Tahun 2020
📝 HOW TO CITE
Supriyadi, Riki; Supriyadi, Riki; Gata, Windu; Maulidah, Nurlaelatul; Fauzi, Ahmad, "Penerapan Algoritma Random Forest Untuk Menentukan Kualitas Anggur Merah," EBISNIS : JURNAL ILMIAH EKONOMI DAN BISNIS, vol. 13, no. 2, Nov. 2020.
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