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Penelitian ini bertujuan untuk menganalisis kesehatan janin berdasarkan data Cardiotocography (CTG) menggunakan dua pendekatan statistik yaitu Linear Discriminant Analysis (LDA) dan Multinomial Logistic Regression. Data CTG yang digunakan berisi parameter-parameter fisiologis janin dan ibu, yang kemudian diklasifikasikan ke dalam tiga kategori: normal, suspect, dan pathologic. Hasil analisis dibandingkan untuk mengevaluasi performa kedua metode dalam mengklasifikasi kondisi janin secara akurat. Visualisasi dan metrik evaluasi seperti akurasi, precision, recall, dan confusion matrix digunakan untuk memberikan gambaran performa model. Studi ini menunjukkan pentingnya pemilihan metode klasifikasi yang tepat dalam membantu deteksi dini risiko kesehatan janin.

I chose to modify this Portfolio Project because this is a dense amount of data that many people could have different uses for, so I wanted to modify it so people could interact with it to suit their individual needs. I wanted to prioritize allowing for more direct comparisons of different types of disasters, so I wanted to modify my original graph to have side-by-side comparisons. Whereas the static version was too busy with all types visible at all times, because the different disaster types were togglable on and off, this wasn't a concern.

This document applies the Box-Jenkins methodology to model and forecast Mexico’s GDP growth using SARIMA models, which extend ARIMA by explicitly capturing seasonal dynamics.

Project <Day 23_Practice> on the day 24