Perbandingan Kinerja Algoritma C.45 dan Naive Byes Dalam Menentukan Resiko Ibu Hamil

Setiawan, Reandi (2023) Perbandingan Kinerja Algoritma C.45 dan Naive Byes Dalam Menentukan Resiko Ibu Hamil. Masters thesis, Institut Informatika dan Bisnis Darmajaya.

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Abstract

Along with the development of technology, especially the development of increasingly large data storage. One organization that has a large data storage is the Hospital. Hospital organizations use data to obtain information, especially information about patients. Patient data has many attributes so that we can make predictions such as predictions determine the health risks of pregnant women. Data mining methods in education are classified into five dimensions, one of which is prediction such as predicting output values based on input data. From the results of research conducted from the initial stage to the testing stage, the application of the C4.5 algorithm gets higher accuracy results than naïve bayes because in the classification stage C4.5 processes one by one attribute data Unlike the case with naïve bayes which are influenced by the amount of data used, the comparison of the amount of training and testing data. The feasibility of the model obtained is supported by the level of accuracy, precision, recall and AUC obtained from the two algorithms that have been tested. The C4.5 algorithm has an accuracy rate of 77.72%, precision of 92.86% and recall of 78.08% and an AUC value of 0.823. While Naive Bayes has an accuracy rate of 78.57%, precision 93.29% and recall 98.38% and an AUC value of 0.838 Keywords: pregnancy, prediction, data mining, C4.5, Naive Bayes

Item Type: Thesis (Masters)
Subjects: eTheses
Divisions: Pasca Sarjana > Magister Teknik Informatika
Depositing User: editor 1
Date Deposited: 01 Nov 2023 07:48
Last Modified: 01 Nov 2023 07:48
URI: http://repo.darmajaya.ac.id/id/eprint/14181

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