Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Riski Puji Lestari
Intitut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Classification of the Effectiveness of Balur Therapy on Patients at the Malang Health Center Using the Decision Tree Algorithm Riski Puji Lestari; Mochammad Anshori; Wahyu Teja Kusuma
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12730

Abstract

This study addresses the classification of balur therapy effectiveness as a complementary treatment using a machine learning approach, aiming to develop an accurate, balanced, and transparent model to support clinical decision-making. The methodology employs the Decision Tree algorithm, data imbalance handling using Synthetic Minority Oversampling Technique, and model interpretation through Local Interpretable Model-Agnostic Explanations. The dataset consists of 520 medical records, reduced to 478 after preprocessing, including data cleaning, binning, and outlier removal. The results indicate that the model without data balancing achieved the highest specificity of 0.8276 at a 90:10 split ratio, while the application of Synthetic Minority Oversampling Technique improved sensitivity toward the minority class but reduced specificity. Key influential features include occupation, diagnosis, and therapy duration. The interpretability analysis demonstrates that the model can clearly explain feature contributions to predictions. This study concludes that integrating classification, data balancing, and explainable modeling enhances medical data analysis. The findings imply strong potential for developing objective and transparent clinical decision support systems.
Co-Authors Mochammad Anshori Wahyu Teja Kusuma