Analisis Prediksi Diabetes Menggunakan Decision Tree pada Dataset Diabetes Pima Indians
DOI:
https://doi.org/10.26905/jisad.v4i1.16494Keywords:
Decision Tree;, Prediksi Diabetes;, Pima Indians Diabetes Dataset;, klasifikasi;Abstract
Diabetes melitus merupakan penyakit persisten dengan insidensi yang terus meningkat di seluruh dunia, sehingga strategi deteksi dini yang tepat menjadi sangat penting. Penelitian ini bertujuan untuk memprediksi risiko diabetes menggunakan algoritma Selection Tree yang berbasis pada Pima Indians Diabetes Dataset. Tahapan penelitian meliputi prapemrosesan data, penanganan nilai yang tidak valid, normalisasi, pemisahan data, dan pelatihan model menggunakan kriteria pemisahan gini dan entropi. Pengembangan kinerja dilakukan melalui optimasi hiperparameter menggunakan GridSearchCV dan penyeimbangan data dengan SMOTE. Hasilnya menunjukkan bahwa model Selection Tree yang dioptimalkan memberikan akurasi tinggi, interpretabilitas yang kuat, dan kemampuan untuk mengidentifikasi variabel yang paling berpengaruh terkait dengan risiko diabetes. Temuan ini menegaskan bahwa Selection Tree yang dikombinasikan dengan strategi optimasi dan penyeimbangan data merupakan teknik yang efektif untuk deteksi dini diabetes.
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