mpact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets

Dublin Core

Title

mpact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets

Subject

ADASYN;Class Imbalance; Oversampling; Machine Learning; Naïve Bayes;

Description

This research aims to analyze the impact of the Adaptive Synthetic (ADASYN) oversampling technique on the performance of the Naïve Bayes classification algorithm on datasets with class imbalance. Class imbalance is a common problem in machine learning thatcan cause bias in prediction results, especially in minority classes. ADASYNis one of the oversampling methods that focuses on adaptively synthesizing new data for minority classes. In this study, the performance of the Naïve Bayes algorithm was tested onAnemia Diagnosisdatasets before and after the application of ADASYN. This dataset contains 104 instances, 5 attributes, and 2 classes, and has an imbalance ratio of 3. The evaluation was carried out by comparing accuracy, confusion matrix, precision, recall, and F1-score to obtain a more comprehensive picture of the effectiveness of ADASYNin improving Naïve Bayes.The results of the study show that the performance of the oversampling method depends on the imbalance ratio so it is important to ensure that the oversampling method does not cause overfitting and this can be overcome by using ADASYN which only selects Selected Neighbors.The results showed that ADASYNsignificantly increased accuracy from 0.57 to 0.78, precision from 0.17 to 0.74, recall from 0.20 to 0.88, and F1-Score from 0.18 to 0.80.In this study, we also compared the application of ADASYN and SMOTE on the Naïve Bayes algorithm. The results show that ADASYN outperforms SMOTE across all key metrics—accuracy, precision, recall, and F1-Score—while the accuracy improvements were statistically significant (p-value = 0.00903)

Creator

Muhammad Khahfi Zuhanda1*, Lisya Permata2, Hartono3, Erianto Ongko4, Desniarti

Source

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6031/1013

Publisher

Department of Informatics, Faculty of Engineering, Universitas Medan Area, Medan,Indonesia

Date

27-01-2025

Contributor

FAJAR BAGUS W

Format

PDF

Language

ENGLISH

Type

TEXT

Files

Collection

Citation

Muhammad Khahfi Zuhanda1*, Lisya Permata2, Hartono3, Erianto Ongko4, Desniarti, “mpact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets,” Repository Horizon University Indonesia, accessed January 26, 2026, https://repository.horizon.ac.id/items/show/10480.