Implementasi Algoritma CART dan Naïve Bayes Untuk Mendeteksi Penyakit Stroke
DOI:
https://doi.org/10.22441/incomtech.v16i1.20209Kata Kunci:
Stroke, CART, Naive Bayes, KlasifikasiAbstrak
Penyakit stroke merupakan penyakit pembuluh darah yang disebabkan oleh kurangnya sirkulasi oksigen dan darah ke otak sehingga menyebabkan kerusakan pada jaringan otak. Stroke dapat menyebarkan perubahan pada fungsi dan fisiologi anatomi yang letaknya jauh dari kerusakan. Penyakit stroke merupakan penyakit penyebab utama kematian setelah penyakit jantung sehingga diperlukan suatu system untuk mendeteksi penyakit stroke sebagai bentuk pencegahan dini agar tidak terserang penyakit stroke. Sistem deteksi menggunakan kecerdasan buatan dengan teknik klasifikasi. Klasifikasi telah digunakan oleh para peneliti untuk mendeteksi penyakit dengan hasil yang memuaskan. Pada penelitian ini menggunakan teknik klasifikasi menggunakan algoritma CART (Clasiification and Regression Tree) dan algoritma Naïve Bayes. Penelitian ini membagi data menggunakan persentase split sebesar 90% data latih dan sisanya berupa data uji dengan dataset dari Kaggle. Berdasarkan penggunaan kedua algoritma dalam mendeteksi penyakit stroke, algoritma CART menghasilkan akurasi sebesar 95.57% sedangkan naïve bayes memiliki akurasi sebesar 85%. Pada sisi presisi model rata-rata yang dihasilkan oleh algoritma CART yaitu 88% sedangkan naïve bayes memiliki presisi 66%. Recall rata-rata yang dihasilkan oleh algoritma CART yaitu 61% sedangkan naïve bayes memiliki recall sebesar 58%. Dari perbandingan antara akurasi, presisi, dan recall yang dihasilkan algoritma CART dan Naïve bayes dapat disimpulkan jika algoritma CART sangat baik dalam mendeteksi penyakit stroke secara dini.
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