Prediksi Dini Penyakit Preeklamsia Menggunakan Algoritma C4.5

Authors

DOI:

https://doi.org/10.12928/jstie.v10i3.24187

Keywords:

Data Mining C4.5, Cross Validation, Confusion Matrix, Preeklamsia

Abstract

Berdasarkan data Kemenkes RI tahun 2021menunjukkan angka kematian ibu tinggi yaitu lebih dari 4000 kasus setiap tahunnya dimana salah satu penyebabnya adalah preeklamsia. Pencegahan preeklamsia cukup sulit dikarenakan gejala utamanya belum diketahui pasti. Namun teknologi dapat digunakan untuk membantu pendeteksian preeklamsia. Penelitian ini bertujuan mendeteksi preeklamsia pada ibu hamil menggunakan algoritma C4.5. Tahapan pertama penelitian ini adalah melakukan studi literatur. Kemudian mengumpulkan data di RSKIA Sadewa Yogyakarta dan mengolahnya melalui tahapan preprocessing dengan melakukan seleksi data, transformasi data, membagi data menggunakan 10-fold cross validation. Selanjutnya data dianalisis menggunakan algorima C4.5 dan diimplementasikan ke dalam sistem. Penenelitian ini menggunakan data sebanyak 870 data dengan atribut pendidikan, pekerjaan, usia, usia kehamilan, tekanan darah, berat badan, jenis kehamilan, jumlah kelahiran, riwayat aborsi, riwayat persalinan, riwayat penyakit, dan proteinuria serta kelas klasifikasi negatif, preeklamsia ringan, dan preeklamsia berat. Penelitian ini menghasilkan sebuah sistem prediksi dini penyakit preeklamsia pada ibu hamil. Hasil pengujian menggunakan confusion matrix menunjukkan bahwa sistem prediksi mendapatkan nilai akurasi 81,38%, precision 78,37%, recall 79,69%, dan f1-score 78,73%. Hasil pengujian black box menunjukkan fungsi sistem dapat digunakan dengan baik.

References

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Published

30-10-2022

Issue

Vol. 10 No. 3 (2022): Oktober

Section

Articles

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