WINE QUALITY PREDICTION USING ADABOOST AND RANDOM FOREST

RAHARJO, GILBERTUS SURYO (2023) WINE QUALITY PREDICTION USING ADABOOST AND RANDOM FOREST. Other thesis, Universitas Katholik Soegijapranata Semarang.

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Abstract

This project aims to test the accuracy of the AdaBoost and Random Forest methods of the two methods to test the level of good alcohol content in wine. In this study using the data taken is alcohol, and from the data processed and sampled data then the two methods get prediction output results and from the two methods can determine which results are better in determining predictions. From the results of the AdaBoost and Random Forest research in the dataset looking for the best alcohol quality levels in wine, it can be concluded that the AdaBoost method gets more accurate and suitable results than the Random Forest method.

Item Type:	Thesis (Other)
Subjects:	000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	mr AM. Pudja Adjie Sudoso
Date Deposited:	04 Apr 2023 06:01
Last Modified:	04 Apr 2023 06:01
URI:	http://repository.unika.ac.id/id/eprint/31396

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