Image of PREDIKSI KEJADIAN HUJAN MENGGUNAKAN METODE ENSEMBLE DENGAN ALGORITMA FUZZY NAIVE BAYES, NAIVE BAYES DAN DECISION TREE BERDASARKAN RESAMPLING BOOTSTRAP

Skripsi

PREDIKSI KEJADIAN HUJAN MENGGUNAKAN METODE ENSEMBLE DENGAN ALGORITMA FUZZY NAIVE BAYES, NAIVE BAYES DAN DECISION TREE BERDASARKAN RESAMPLING BOOTSTRAP

Penilaian

0,0

dari 5
Penilaian anda saat ini :  

Precise weather predictions are needed in various fields including agriculture, tourism, aviation, shipping and plantations. The most predictable weather element is rain. This study aims to predict rain events using the ensemble method with fuzzy naïve Bayes, naïve Bayes and decision tree algorithms based on bootstrap resampling. This study uses weather datasets in Australia sourced from the Kaggle website, totaling 145460 data. The level of accuracy obtained in predicting rain events using the fuzzy naïve Bayes method produces an average value of accuracy, precision, recall and fscore of 78.19%, 50%, 51.34% and 50.66%. The naïve Bayes method produces an average value of accuracy, precision, recall and fscore of 77.13%, 48.63%, 37.77% and 42.52%. The decision tree method produces an average value of accuracy, precision, recall and fscore of 76.66%, 48%, 50.90% and 49.41%. The ensemble method produces an average value of accuracy, precision, recall and fscore of 79.29%, 54.48%, 45.61% and 49.65%. The results show that the ensemble method produces better prediction accuracy because it produces higher accuracy and precision values compared to the other three methods. However, the naïve Bayes fuzzy method has a better recall and fscore than the other three methods.

Availability
Inventory Code Barcode Call Number Location Status
2307002219T110723T1107232023Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1107232023
Publisher
Indralaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Sriwijaya.,
Collation
xiv, 76 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
511.307
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Fuzzy
Jurusan Matematika
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

File Attachment
Comments
You must be logged in to post a comment