Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction

Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction

This study compares three machine learning methods—Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Decision Tree—for analyzing and predicting menstrual cycles. The dataset consists of 1,665 samples with 80 attributes encompassing information related to menstrual health. These...

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Bibliographic Details
Main Authors: Mutiara Khairunisa, Desak Made Sidantya Amanda Putri, I Gusti Ngurah Lanang Wijayakusuma
Format: Article
Language:English
Published: Politeknik Negeri Batam 2025-03-01
Series:Journal of Applied Informatics and Computing
Subjects:
machine learning
menstrual cycle
prediction
lstm
cnn
decision tree
reproductive health
Online Access:https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/9076
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https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/9076

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