KLASIFIKASI DATASET MENGGUNAKAN METODE NAIVE BAYES

PASARIBU, JABES PUTRA PAULUS and Utami, Alvi Syahrini and Miraswan, Kanda Januar (2020) KLASIFIKASI DATASET MENGGUNAKAN METODE NAIVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

In this study, a system was built to do dataset classification using Naive Bayes method. The study aims to look at the classification performance of Naive Bayes whether it is influenced by dataset characteristics. The study used three data sets with a fairly different number of attributes, instantaneous numbers and data types. Split validation 70% and K-fold Cross validation with k = 10 used as evaluation method. The results of this study showed that data type, number of attributes and instant number influenced classification results. Accuracy results tend to get better when more and more dataset attributes. Soybean with 35 attributes and 683 intant numbers as the largest dataset, is classified quite well and produces an accuracy of 92.79%. The study also showed that testing with k-fold cross validation value k=10 resulted in a better classification than testing with a split validation ratio of 70%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	data mining, classification, Naive Bayes, dataset
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 10260 not found.
Date Deposited:	28 Jan 2021 04:12
Last Modified:	28 Jan 2021 04:12
URI:	http://repository.unsri.ac.id/id/eprint/41019

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