Skripsi

KLASIFIKASI DATASET MENGGUNAKAN METODE NAIVE BAYES

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Penilaian

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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%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002723	T41019	T410192021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T410192021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xiv, 69 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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